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BUGSSAS Explore 2022 Papers - Index
81 papers. Source: SAS Explore conference proceedings.
| # | Title× | Authors× | Abstract× | Keywords× | Extras | Pages |
|---|---|---|---|---|---|---|
| 1 | A BasePlus Package for SAS | Bartosz Jabłoński | Video recording: A SAS Package is a self-contained set of SAS programs extending functionality of the SAS system. The 'BasePlus' package implements more than 40 useful functions, macros and formats I miss in the Base SAS, including the delDataset() function, %functionExists() macro, %RainCloudPlot() macro, arrFill() subroutine, or %zipLibrary() macro. The presentation will introduce the package, show how to use it and present its capabilities. | sas base, sas packages | source youtube |
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| 2 | AI Based Reservoir Model Using SAS | Sanskar Jain | Video recording: AI based reservoir modeling is an alternative approach to build a reservoir model using machine learning techniques to forecast production from a reservoir and find optimum new drilling locations. This method uses past production data, injection data, well properties and known reservoir properties to build a model of the reservoir. A forecast is made for full production, and an infill location is also suggested. This is a new way to build the reservoir simulation model, and Oges is the first company in the world which is doing this work with SAS. The workflow is proprietary to Oges, and we developed it to achieve better history matching and better prediction. | source | ||
| 3 | AI Governance and ModelOps: Monitoring Performance, Economics and Social Responsibility | Jacqueline K. Long | Video recording: AI and ML have introduced new economic benefits to organizations, but with that comes additional responsibility. Organizations have traditionally monitored their modeling efforts based on accuracy, system performance and business value. Now it's time to include checks and balances around fairness in modeling. As modeling has become fully integrated into operational processes, there is heightened awareness and increasing regulation around social responsibility. There is also a need to quantify the investment in modeling resources. The implementation of enhanced decisioning processes helps surface inequities and support organizational strategies and objectives. Success involves achieving a balance between profitability and social responsibility. | source | ||
| 4 | Aircraft Landing Problem: An Optimization Solution | Jay Laramore | Video recording: Commercial service airports implement systems designed to achieve two main objectives: ensure passenger safety and promote on-time flight services for all flights. One of the bottlenecks often impeding on-time flight service is the number of available runways, which if not managed efficiently, can result in unnecessary delays. The aircraft landing problem (alp) is an analytical solution that optimally assigns each inbound airplane to one of the airport's designated runways, while simultaneously sequencing the landing order at each runway, so that all airplanes arrive as close to their designated landing time as possible, if not earlier! This presentation describes the mixed-integer linear programming formulation for the deterministic aircraft landing problem and solves it using the OPTMODEL procedure in SAS Viya. A thorough description of the modeling approach is included, along with the data requirements and results from an example using SAS IML and SAS Optimization, so that anybody with an interest or background in this area can utilize this approach. This presentation concludes by showing how this model can be repurposed to accommodate routing and scheduling problems in other industries. |
linear programming, sas viya, odds ratio | source youtube |
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| 5 | Analytics Innovation in AML | Beth Herron | Video recording: Next-generation AML is coming to the forefront as the financial services industry goes through massive digital transformation and as regulators expand their definition of reasonable control and governance. Robotics, semantic analysis and artificial intelligence, particularly machine learning, will be central to this evolution. Instead of reacting to past information, machine learning delivers a forward-looking advantage. You can distill new data elements that weren't previously available for AML models. Let the computer uncover patterns the human eye would never see. Validate those insights and feed the results back into modeling efforts. The more training a model gets with feedback data, the smarter it becomes and the less tuning it requires. Not ready to give up your trusted rules? Adopting machine learning doesn't mean you have to abandon established ways of working. The right route for an organization's AML modeling might be a complementary approach, a hybrid of rules and predictive models. | machine learning, artificial intelligence, financial services | source youtube |
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| 6 | Assess Your SAS9 Content and Plan Your Migration to SAS Viya | James Holman | Video recording: Designed just for SAS9 users, the SAS9 Content Assessment is a set of applications to help you easily identify key details and insight so you can plan your migration to SAS Viya. During this session, see how the applications support migration planning, migration preparation and how results contribute to a guided migration experience. | sas viya | source youtube |
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| 7 | Automate SAS Workflows by CI/CD Pipelines | Anand Bisen | Video recording: Modern analytics engineering is more pervasive than ever. The analytics pipelines are also increasing in complexity - often requiring many individual steps involving different point solutions for data preparation, model development and deployment. | data wrangling | source youtube |
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| 8 | Automated Deployment of SAS Viya 4 Using Infrastructure as Code (IaC) | Sally Yeung, Thomas Pangborn |
Video recording: To better help customers and providers with rapid, automated deployment of SAS Viya 4, SAS has created Infrastructure as Code (IaC) tooling available as an open-source project. IaC enables a fully scripted, automated deployment of SAS Viya 4 on cloud providers and supported container platforms. In this session, SAS R&D IaC leaders Sally Yeung and Thomas Pangborn will discuss IaC background, features, capabilities, the roadmap and provide an IaC demonstration. Gain an understanding of what IaC is, why it exists and where it is going. | sas viya | source youtube |
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| 9 | Banking Hyperautomation with Microsoft Power Platform and SAS Intelligent Decisioning | Morgan Pettis | Video recording: Data and AI is changing the nature of our world. SAS has been a globally- recognized leader in AI for years. Through our partnership with Microsoft, the power of reality-tested AI can be delivered with leading RPA and cloud services in a single package. This represents a truly unique market offering often referred to as hyperautomation. In the aiBANK project, we bring together learnings and best practices from around the world with a focus on integration of the award-winning SAS banking solutions like risk, fraud and CI so we can build an industry-enhanced hyperautomation offering. We also built a composable ecosystem of banking services by integrating fintech and third-party services to build a composable ecosystem of banking services. The project also delivers a multi-modal system to enable the enterprise-wide organization for digital change by integrating of no-code, low-code and high-code. The accelerated delivery model SAS aiBANK Garage helps create change from day 1. Learn more during this session. | source | ||
| 10 | Be Better Prepared Against Natural Disasters With Disaster Response AI | Raymond Outar, Soham Suvarnkar, Ray Yu |
Video recording: Natural disasters cause more than 15,000 deaths annually and amount to over $170 billion globally. With high unpredictability and potential for massive destruction, it becomes challenging for governments and organizations to allocate resources effectively, optimize funding distribution, and place preventative measures in advance. We need a way to identify these vulnerable regions, forecast disaster risk ahead of time and make informed decisions about where to allocate resources and funding so we can be better prepared when a disaster occurs. This is where Disaster Response Ai (DRAi) comes in. DRAi is built using SAS Viya and aims to advise governments, insurance agencies and organizations about these vulnerable regions across the country for optimized allocation of resources and funding, insurance modelling and effective disaster response planning. DRAi features an array of tools, including a national vulnerability map, disaster prediction engine and community resilience rating. | sas viya | source | |
| 11 | Building Advanced Dashboards Using SAS Visual Analytics for SAS Viya | Dominique Weatherspoon | Video recording: This presentation covers techniques to build advanced, flexible dashboards that empower users to filter information according to their specific needs. Dominique Weatherspoon will demonstrate these techniques through a real-world case study of a dashboard that allows the managers of an international online learning platform to analyze course evaluations submitted by past students. Through this example, viewers will witness how the following SAS Visual Analytics features can enhance their reports/dashboards: joining and aggregating tables, mapping data items across multiple data sources, using parameters, using prompt and object containers, formatting objects, and hiding pages. In addition, Dominique will give tips for inheriting and exploring unfamiliar reports. | sas viya | source youtube |
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| 12 | Building Analytical Applications: SAS Visual Analytics and Azure Static Web Apps | Yury Shkoda, Stefan Dimitrov Stoyanov |
Video recording: Digital transformation and widespread adoption of analytics are often curtailed by the lack of effective user access to data and analytical insights. Using SAS Visual Analytics and Azure Static Web Apps, organizations can easily and quickly build analytical web applications to embed data and analytics into everyday processes that help improve decisioning. SAS VA reports and objects can easily be embedded into interactive enterprise web applications using SAS SDK, Azure DevOps and Azure Static Web Apps. Organizations will benefit from the proven and secure enterprise analytics platform SAS Viya, Azure Static Web Apps automation and development acceleration features, and the Azure DevOps collaboration and deployment best practices. The analytical web applications will empower end users to filter, visualize, extract, and download data-driven insights of interest. By embedding SAS VA objects or reports into Azure Static Web Apps, organizations can provide better data access and user experience to their employees, partners and clients through a modern and simple design and a unified layout across operations and departments. This will optimize development and maintenance efforts and costs and will allow organizations to prove business benefits quickly. | sas visual analytics, analytics platform, sas viya | source youtube |
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| 13 | Creating Reports Again and Again... and Again with Macro | Brittany Jones | Video recording: We know that we can create a flexible report with SAS using macro variables, but what about when it comes to multiple reports? What about sending the report to Microsoft EXCEL? This presentation focuses on using %if/%then logic and %do loops to enable you to create multiple EXCEL reports. The macro definitions that create the reports are flexible, customizable, and, best of all, able to be run repeatedly without your needing to manually change anything! |
excel, macro loop, do loop | source youtube |
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| 14 | Data Catalog: Ignite Your Analytics Journey | Kumar Thangamuthu | Video recording: Data and information governance is a core component of an overall data management strategy in any organization. Regardless of whether it is to search and discover data or explore data quality or to cleanse and prepare or to further act using the data to build dashboards, model and decisions. In this session, see how SAS information governance along with other SAS Viya components to crawl and catalog data from multiple data sources including some cloud sources especially from Microsoft Azure. Discover analytic assets such as reports, models, decisions using catalog search. Explore data (profile results, column analysis, metrics, semantic types and information privacy classification, take action on the data).Learn how to transform and cleanse data, to create a report or model, look at lineage of all the related asset elements, and finally, schedule a job to crawl and catalog to automate this process. | sas viya, data governance, data cleaning | source youtube |
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| 15 | Data Preparation in SAS Viya | Nicole Ball | Video recording: Data preparation is at the heart of any analytic effort. You can't produce meaningful results until you have the necessary data in the appropriate format. You may need to combine, aggregate, modify or filter your existing data sources to create the data needed for your analysis. SAS Viya supports all stages of the analytics lifecycle from data preparation to discovery to deployment. In fact, SAS Viya has many tools you can utilize for preparing your data: you can write code in SAS Studio, create plans in SAS Data Studio or prepare data within reports in SAS Visual Analytics. Each of these tools has its own features and functions. This presentation explores the data preparation features available in SAS Studio, SAS Data Studio, and SAS Visual Analytics and explains when you might want to use each application. Basically, the tool you choose will boil down to two factors: 1. Simplicity and 2. Control. Learn about the amount of coding you'll need to do and the options available. | sas viya, sas studio, data wrangling | source youtube |
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| 16 | Digitalization of the Customer-Facing Insurance World | Başak Yüzbaşıoğlu | Video recording: To cope with the ever-changing world, need for digitalization is becoming a constant. While technology is advancing, it's essential that they create business value. During this session, Team Linktera will highlight key steps of business process design and define their 4D Business Process Excellence Framework. Once business processes are defined and the solution design is created, it's important to achieve a fully flexible, robust, adjustable, customer-centric and easy to integrate solution for transformation needs in a fast and affordable way. The team will discuss their business case from the 2022 SAS Hackathon. They focused on the digitalization of the customer-facing aspect of insurance: underwriting and claims management automation and digitalization. Analyzing and decisioning is a time-consuming process. With SAS Viya Intelligent Decisioning and Visual Analytics, user can give inputs and let machines do the rest.. Low-code platforms like Neula enable users to build workflows, user interfaces, task lists, databases and rule sets from scratch in no time. | sas viya | source | |
| 17 | E2E Connected Supply Chain Planning, Execution and Integrated Simulation Solution | Camille Walker | Video recording: Today's global commercial supply chain is more complex, fast moving and volatile than ever. Technology is driving supply chain optimization, and supply chain optimization is driving corporate revenue growth and profitability. Technology is advancing at exponential rates. Companies are reconciling with the fact that they can no longer manage an optimized internal organic technological infrastructure. Companies must make intelligent decisions, faster, with more real-time and forward-looking predictive precision. Enterprise decisioning platforms must be able to ingest more data easily and seamlessly. The modern decisioning platform can consider multiple scenarios make intelligent automated decisions with clear visualization, and deliver end-to-end planning interconnectivity so that all internal and external planning and decisioning stakeholders are kept informed and aligned. Tomorrow's modern, automated and advanced supply chain planning ecosystem is available today. | source youtube |
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| 18 | E2E Connected Supply Chain Planning, Execution and Integrated Simulation Solution | Camille Walker | Video recording: Today's global commercial supply chain, regardless of the industry, is more complex, fast moving and volatile than at any other point in history - and is accelerating. Technology is driving supply chain optimization, and supply chain optimization is driving corporate revenue growth and profitability. Technology is advancing at exponential rates. Companies are reconciling with the fact that they can no longer manage an optimized internal organic technological infrastructure. Companies must make intelligent decisions, faster, with more real-time and forward-looking predictive precision. Enterprise decisioning platforms must be able to ingest more data, more easily and seamlessly. The modern decisioning platform can consider multiple plausible scenarios, make intelligent automated decisions, more agilely and with clear visualization, with end-to-end planning interconnectivity so that all internal and external planning and decisioning stakeholders are kept informed and aligned. Tomorrow's modern, automated, advanced supply chain planning ecosystem is available today. | source youtube |
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| 19 | Embed Data Visualizations in Webpages and Delivered at Scale | Brad Morris | Video recording: Information is best received when it's presented to you where you already are, from your corporate portal, online hospital performance monitor, school system report card, or other public and private websites. Having companion content for purpose-built reports can provide engaging ways to deliver information through custom websites targeted at specific audiences. A primary goal of the SAS Viya SDK for JavaScript is to expand the delivery options for data visualizations you've added to your reports in SAS Visual Analytics. The SAS Viya SDK lets you embed visualizations in your websites to support scenarios that require the most up-to-date information through an authenticated connection to SAS Viya. It also supports scenarios that demand scaling to support public access for hundreds of thousands of end users. The SAS Viya SDK also provides HTML elements that allow navigation of your SAS Viya content from within custom web pages. Join this breakout session to see how you can expand the reach of the insights you've gained in SAS Visual Analytics with the SAS Viya SDK for JavaScript. | sas viya, data visualization | source youtube |
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| 20 | Empowering Data Analytics Teams to Fight Medicare Fraud: From Data to Decisions | Al Cordoba, Manuel Figallo, John C. Brocklebank |
Video recording: The Data Analytics Team (DA) at CGS Administrators is exploring SAS Viya to develop a surveillance strategy that will utilize modeling and predictive statistical techniques on large volumes of administrative data to identify providers for review. We use historical data set to evaluate trends/patterns among providers, services and outcomes to continuously improve the design of the surveillance strategy. The data analytics goal is to quickly identify areas of vulnerability, areas of opportunity and effective provider impact. | sas viya | source | |
| 21 | Feature Store on the SAS Viya Platform | Cezary Glowinski | Video recording: This session will discuss details of the feature store concept implemented on the SAS Viya platform during proof of concept for big telecommunications company in partnership with SAS Poland and the Microsoft team on SAS Viya platform during proof of concept Data scientist teams who are working on ML models need to solve data preparation and feature engineering problems. The solution could be feature store. Feature store allows users to collect raw data, transform them into ML features, build training tables based on those features, serve scoring tables for MLOps production processes (both batch and online) and monitor ML features. We will present the architecture and functionality of feature store implemented on SAS Viya platform and deployed on Microsoft Azure. | sas viya, proof of concept, data wrangling | source | |
| 22 | Game Changing Decision Engine: SAS Container Runtime | Paata Ugrekhelidze | Video recording: What if you could develop a SAS language function and immediately run it anywhere in the cloud or on your local site even without access to a SAS Viya installation? What if you could integrate that function into any standard web service application or framework? What if your IT staff could use industry-standard, open source tools to manage the deployment process? What if you could reduce the size of your production runtime environment? The solution is here. SAS Container Runtime (SCR) is a new SAS language execution option for SAS Viya 4. An SCR is a standard docker container that includes all the program files and executable files needed to run SAS and Python code. Each new SCR image is produced by using SAS Viya software. This image is entirely self-contained, immutable and will run the same on any Open Container Initiative (OCI) system. This breakout session will show users and developers how to develop, test and integrate SCR images into their runtime applications. We will show applications using SAS and Python code running within the container. The result is a game changer for SAS applications. | sas viya, web service | source | |
| 23 | Green AI: Travel Greener and Better! | Stefanus Wiguna | Video recording: Learn how we used a suite of SAS Viya 4 products during the SAS Advanced Analytics R&D hackathon to analyze travel data and gain insights for better and greener travel alternatives. You'll hear an overview of raw data visualization to get preliminary insights, the ways we built predictive models to determine preferred hotels, and the tuning and comparison of these models for results and performance. You will also see example analysis of hotel rates and volatility, and ways to determine preferred hotels. We'll also discuss the carbon footprint analysis of these trips. | sas viya | source youtube |
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| 24 | Hiding Sensitive Parameters Connecting to BigQuery Using OAuth Authentication | Sebastian Tobar | Video recording: While SAS has a Google BigQuery interface, authentication can be an issue if you want to use it. You have the option of using a service account or using OAuth authentication. If you use OAuth authentication, you have to provide the client ID, secret and refresh token to the LIBNAME statement. In order to hide the client secret from our users, and avoid having them handling refresh tokens, we developed a set of encrypted macros that can get the refresh token for the user and use it to create a regular library or a CAS library. This allows our users to access the same data they can access directly on BigQuery, without having to handle authorization directly on the SAS environment. |
google bigquery, libname statement | source youtube |
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| 25 | I Got 99 Problems & Biased AI is #1 | Reggie Townsend, Allie DeLonay |
Video recording: AI is becoming more pervasive in all parts of our lives. It's being used to autonomously drive our cars, to create new virtual realities, and to tell us whether we should grab an umbrella on our way out the door in the morning. AI is helping us to work and live more efficiently, but while AI comes with benefits, it also comes with risks. People have biases they either intentionally or unintentionally carry with them, and these biases get baked into the data people collect. When data is biased, AI systems created from that data are also biased, which can cause unintended harm to vulnerable populations. As AI regulatory requirements come down the pipeline, organizations need to understand how to prevent and/or mitigate the biases that can get laced into an AI system. Understanding these biases will help organizations develop more responsible AI applications, avoid penalties and reduce the possibility of harm. In this breakout session, we will discuss how and where different types of bias can get unintentionally laced into an AI system. We will also demonstrate some of the features included in SAS Model Studio that can help a user to detect the discussed bias types and to weigh the accuracy and fairness of a model. | source youtube |
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| 26 | Implementing a Whole Company Analytics Environment With SAS Viya | Gianantonio Carli | Video recording: The relationship between Comelit and SAS is a long-term one. We chose SAS 10 years ago for the cutting-edge technology, high grade of stability and continuous support. The use of the SAS software has an impact on all the functions across the company, with120 SAS users worldwide, in various departments. We created BI group reports and analytics reports and KPIs in many areas like accounting, sales, working capital, product quality, purchase, logistic and warehouse. We also carried out consolidated financial statements, sales budget and forecast, analysis of variances, cost analysis and sales delivery performance analysis. We're using SAS to study and analyze topics like returns and related reasons, warehouse product rotation, supplier rating analysis. Comelit is also using analysis to build company and group data warehouse with ETL jobs, SAS Viya VA KPI and reports, merging data coming from ERP, CRM and surveys. We recently migrated our SAS Visual Analytics 3.5 architecture to the new SAS Viya 4 platform in GCP Cloud. We can testify that the passage to Viya on cloud is easy: the data and report migration is simplified thanks to the use of JSON files and a simple export and import web interface. Comelit plans to evaluate the SAS Visual Forecasting on SAS Viya 4 to be used by our planning team for a company-wide demand planning project. | sas viya, anova, data warehouse | source | |
| 27 | Improving Manufacturing Operations: Embedding Computer Vision in an Analytic Pipeline | Sanjeev Heda | Video recording: Manufacturers are constantly looking for new ways to improve their production processes. Using cameras and computer vision is a new way to provide coverage for potential issues that is more cost effective than traditional sensing techniques. But just having a computer vision model is not enough to generate insights that drive action. Organizations need a complete analytic pipeline that has all the necessary components to transform input data sets into actionable insights. This analytic pipeline must have sufficient accuracy to have confidence in predictions, minimal latency to provide these decisions in a timely manner, and have the ability to deploy and scale to multiple cameras and facilities. See how this analytic pipeline for a manufacturing use case can be built and operationalized with SAS Viya using SAS Visual Data Mining and Machine Learning and SAS Event Stream Processing. We will show how the analytic pipeline consumes multiple data sources, contains multiple post-processing analytic techniques to interpret and generate actionable information from the computer vision model outputs, leveraging technology optimized for compute, and the intermixing of both SAS and open source technology in the same analytic pipeline. | machine learning, sas viya, stream processing | source | |
| 28 | Improving Wind Turbine Performance with Principle Components Analysis | Andrew Brody, Tom Anderson |
Video recording: This session will describe how AES uses AI and ML tools to give our wind energy operations teams early indications of an issue on a specific wind asset by leveraging principle components analysis on a sitewide basis. We can predict major component failures early enough to allow the site to make a more informed decision on when to perform the repair to better suit business needs. We can quickly analyze large wind sites of 50-200 wind turbines and give them a list of three to five wind turbines that actually need intervention. We are looking at every turbine sensor across the whole fleet, all in one analysis. | source | ||
| 29 | Increase Supply Forecasting Accuracy by Leveraging Advanced Time-Series Forecasting | Biswajit Das | Video recording: Das | source youtube |
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| 30 | Insurance Risk: Buzzing With Challenges and Innovations | Nektarios Konstantinou | Video recording: Though the insurance industry has a conservative reputation, staying successful requires endurance, agility and innovation. A huge part of the insurance industry is at the last stage of IFRS17 implementations and facing the challenge of steering the business, including operational and strategic planning, based on profitability analysis using completely new metrics. In most geographies, some form of risk-based capital solvency regime has been deployed and practiced for some time. ICS 2.0, a consolidated group-wide capital standard for Internationally Active Insurance Groups (IAIGs) is being introduced. The worldwide validity of ICS might be also a stimulus for non-IAIGs reinsurers to adopt the ICS regime voluntarily and use ICS Coverage Ratio as a standard KPI. To face regulatory requirements, environmental and geopolitical changes, and to stay profitable, reinsurers need to carefully manage the insured portfolio. The efficient pricing process that enables thorough risk analysis, including the use of AI & ML techniques, and reduces the time to market of new models, becomes complicated. To simplify this process, siloed software products for data management, modeling, and reporting need to be replaced by a platform that supports all of those functions. In this session, we will present how SAS supports insurers facing these challenges. | insurance, profitability analysis, data governance | source | |
| 31 | Intelligent Decisioning: Ensuring Fairness in Analytically-Driven Decision Making | Luiz Kauffmann, Diana Maris |
Video recording: Analytics and business rules are delivering powerful capabilities to augment and automate strategic and tactical decisions within customers' lines of business. Analytically-driven decisioning is improving customer interactions in call centers and ensuring the most relevant next-best offers for personalization and customer experience. It is improving credit risk decisions, detecting fraud and reducing losses, automating the underwriting process, streamlining collections processes, and optimizing the supply chain to deliver goods and reduce loss in transit. In many of these use cases, customer data can be used in unfair and biased ways. Companies need to detect possible misuse and identify ways to evolve their decision making to prevent these risks from causing harm to their customers or stakeholders. SAS Intelligent Decisioning, SAS Model Manager and SAS Visual Analytics provide the necessary tools to identify, assess and resolve these risks quickly to ensure decisions and models are fair and unbiased to deliver the best outcome for customers and companies. | sas model manager, credit risk, customer experience | source youtube |
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| 32 | Jakarta Post Covid-19 Economic Resurrection | Muhammed Iqbal | Video recording: Jakarta, the capital of Indonesia, is alsothe most crowded city with more than 16,000 people per square kilometer.Jakarta recorded more than 1.2 million COVID-19 cases by Q2 of 2020, resulting in a 60 percent decrease in GDP growth compared to Q1. To countermeasure the pandemic hit, the central government allocated 123 T Rupiah for micro, small and medium enterprises (MSMEs), which make up 94% of the economy . The government developed Jakpreneur to support MSMEs. The government also built two decision support systems: area prioritization and budget allocation. Within the SAS analytical lifecycle framework, JAKSTAT leveraged data sources, including Jakpreneur, Central Bureau of Statistics and the Ministry of Cooperatives and SMEs in the DataOps stage. In the AI stage, JAKSTAT built segmentations of MSMEs for spatial analysis, produced economic impact modeling, and composed a vulnerability index for financial aid prioritization. The team implemented the model into Jakarta's portal web and mobile app to ensure accessible and timely updates for all stakeholders. The decision support systems are aimed to help the government calculate the simulation of financial aid and allocate it to the right MSMEs. By applying this model to Jakarta first, team JAKSTAT hopes to create a national economic resurrection. | source | ||
| 33 | Learn the Strategy for Migration from SAS9 to SAS Viya | Gary Mehler, Christiana Lycan |
Video recording: Are you still on the fence about making the move to SAS Viya because you don't know where to begin? Getting ready for a migration can sometimes feel overwhelming. During this session, discover best practices for how to take the guesswork out of migration by using data-driven techniques and strategies for the best migration experience. | sas viya | source youtube |
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| 34 | Learn to Play and Play to Learn with SAS Viya | Yi Sun, Roberto Torres, Kate Ulveling |
Video recording: Watch how this group of SAS customers transformed their SAS skills to leverage the power of SAS Viya, using Cortex: the online analytics simulation game . This session showcases how customers use this fun and engaging game to apply and advance their machine learning skills using SAS Viya. With no prior experience in SAS Viya, customers were able to hit the ground running in Model Studio and Visual Analytics, jumping to the top of the Cortex leaderboard to compete for those coveted bragging rights and some cool SAS swag! Watch this session to find out who the ultimate winner is, and how easily you can jump into SAS Viya, no matter your skill level. | sas viya, machine learning | source youtube |
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| 35 | Leveraging KT Charts with Streaming Data | Byron Biggs, Sergiy Peredriy |
Video recording: KT chart monitoring enables rapid anomaly detection and process control for high-frequency multivariate data. The method is based on support vector data description (SVDD) applied to a moving window of observations. KT charts are non-parametric sub-group control charts, which can simultaneously monitor central tendency and spread. The method accommodates non-normal data and supports monitoring multimodal processes. Potential industrial IoT applications include predictive maintenance and predictive quality applied to high-value industrial assets and processes. KT chart monitoring consists of two steps: 1. Training - The KTTRAIN procedure in SAS Viya uses the data from normal operations to define the state of statistical control. KT chart training calculates the control limits for permitted deviations in the central tendency and the spread of the process. The KT chart for monitoring the process center is called the A chart, and the KT chart for monitoring the process variation is called the R2 chart. 2. Monitoring - The KTMONITOR procedure in SAS Viya and Streaming KT Chart Monitoring in SAS ESP use the data from the ongoing process to monitor for stability in both the central tendency and the spread by using the control limits that are calculated during the training step. This super demo showcases the capabilities of KT chart monitoring applied to industrial process data. It includes the training process and the detection of anomalies with streaming data. | central tendency, sas viya, outlier | source youtube |
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| 36 | Managing Data Processing for CDC Surveillance Projects Using Metadata | Louise S. Hadden | Video recording: There are many epidemiological and surveillance studies ongoing because of the COVID-19 pandemic, often embodying the definition of "big data" with thousands of participants, variables and lab samples. Researchers use data from many different streams in a given study, including REDCap software, electronic medical records (EMR), chart abstraction, laboratory records and more. Different contractors can be managing different aspects of the same project, the data is changing minute to minute, and the deliveries are required at a fast and furious pace. Wrangling all the different data sources requires robust data management routines, and SAS can help with tools to obtain data via APIs and PROC HTTP, metadata resources and programming techniques. This presentation will use real-world examples to outline best practices for managing multiple aspects of large scale CDC surveillance projects using SAS. |
big data, proc http, sample | source youtube |
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| 37 | Managing SAS Viya 4 at Scale in the Cloud | Jelle Daemen | Video recording: SaasNow has been managing SAS products in a private cloud in a unique monthly, fully self-service cloud model since 2015. Starting with SAS vApp technology, SaasNow was one of the first providers to offer a true cloud experience for SAS Visual Analytics. With the release of SAS Viya in 2016, SaasNow has been able to support many more SAS products, including SAS Visual Data Mining and Machine Learning. Currently, all SAS Viya products and bundles can be automatically deployed on SaasNow within a few hours. Over the years, we have deployed and managed hundreds of environments, ranging from small four core demo environments to multi-server production setups of up to 128 cores with a wide variety of customer-specific customizations and integrations, like customized authentication (Kerberos or SSO integrations) and external data source connections (SQL and Apache Hadoop). We have developed best practices for sizing, deploying, updating, upgrading and monitoring many instances of SAS Viya at the same time. This enables us to make SAS Viya available to our customers and partners within several hours and have new releases available within days after they have been released by SAS. We offer a true cloud experience for SAS Viya. Divided in four activities deployment, monitoring, upgrading and maintenance, we will explain the lessons learned on deploying and managing multiple SAS Viya 4 environments in the cloud. | sas viya, machine learning, proc sql | source | |
| 38 | ML for Inclusive Micro Insurances, Insurance Gaps and Climate Risks | Alexander Buchwald, Lars Krieger |
Video recording: Climate change is impacting everybody, but costs are not shared equally. People with low socioeconomic status in the global south are most vulnerable but are often not aware of and insured against risks like floods and draughts. Micro insurances are an effective measure to help these people by providing low-fee coverage of high-risk events. Gaining strength in numbers, these insurances suffer from high churn rates and seek to maintain customers to provide stable support. The Positive Thinking Company used real-world insurance data to identify factors leading to insurance churn and used them to target people that are at risk to suffer from climate change but are likely to quit. The team used publicly available economic and climate data to add features that allow individuals to determine their personal climate change risks depending on geographic and socioeconomic factors to raise general awareness and insurance benefits. This creates an incentive to use the tool to their benefit, while allowing insurances to target a wider audience, which strengthens overall insurance resilience. This use case shows the power of ML and SAS Viya to create a win-win situation with high impact for people in need. | sas viya | source | |
| 39 | Mobile Network Capacity Planning: Network Areas to Invest In | Hans de Wit, Sten Ruben Strandheim |
Video recording: Telenor Group is a leading telecommunications company across the Nordics and Asia with an award-winning network. In 2020, it was named the fastest network in the world. To maintain a high-quality network, Telenor needs to supply sufficient capacity without going over capacity because it is expensive and uses excess energy. Team 4-kasting created a forecast model system, called hierarchical forecasting, for every Telenor site sector, site and cluster. At SAS Hackathon 2022, the team defined the problem and discussed the data available, from cell to site sector. Team 4-kasting created the model using visual forecasting to supply sufficient capacity without going over capacity. | capacity planning, network capacity | source | |
| 40 | Modern Data and Analytics Engineering in Depth | Amy Peters | Video recording: What about all the work needed before you can finally do your analytics and reporting? This session starts from the beginning - data discovery and how you can connect to a wide variety of data sources - to understanding what you are seeing using SAS Information Catalog. Then, find out how to build a flow in SAS Studio to prepare the data using the best techniques available in SAS and Python while tracking work in Git. And finally seeing the results of your labor documented in lineage. Data engineering never looked so good! | sas studio | source youtube |
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| 41 | More Analysis, Less Coding with SAS Viya for Learners | Linda Jordan | Video recording: Machine learning is more than just a buzzword: it is redefining predictive modeling as we know it. In this workshop, you learn how SAS Visual Data Mining and Machine Learning in SAS Viya for Learners makes predictive modeling more accessible to students and professors via two easy-to-use, drag-and-drop interfaces. With the drag-and-drop functionality of SAS Viya, modelers can spend more time analyzing output and selecting their champion predictive model, rather than learning programming syntax. With an increased focus on accessibility, Viya for Learners is a great resource for professors with limited classroom time. | sas viya, machine learning | source youtube |
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| 42 | Optimization of BiciMAD Service Management | María Neira Bustamante | Video recording: Large cities, such as Madrid, have significant problems regarding pollution and urban mobility. Although these cities usually have sustainable transportation alternatives available, some of them have an underperforming service, which discourages people from using them. In Madrid, there is a public transport service known as BiciMad, which provides electric bicycles exclusively. By using both technology and advanced analytics techniques, the BiciMAD service can be optimized to change citizens' urban transportation habits. Our analytical approach has two main phases. First, we created accurate forecasting models to predict the number of bicycles in demand for each day within different time slots. Second, we optimized the process to provide the right number of bicycles to be replaced and removed from each station for every time slot. Let's all do our best to take care of the environment and our society. | source | ||
| 43 | Optimize Every Interaction With SAS Customer Intelligence 360 | Craig Kestecher | Video recording: Customer Intelligence 360 empowers you to reimagine marketing. Drive revenue and improve efficiency with journey activation, customer analysis, a decision engine and more. | source youtube |
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| 44 | Predictive Maintenance for Overhead Utility Infrastructure | Priya Sharma, Craig Foster |
Video recording: SAS Grid Guardian AI is a new solution leveraging partner IoT sensing technology and SAS analytics that enables utilities to significantly improve reliability of electrical distribution networks. In this session, we will first explain the challenge that utilities have with reliability of overhead distribution equipment and how helping them solve these challenges can improve the utility's profitability. We will continue by explaining how our partner, Exacter Inc.'s, sensing technology functions and is deployed on host fleet vehicles in a target geography. Finally, we will demonstrate how SAS software is used for executing analytics to prioritize recommended actions for improving reliability. | predictive maintenance, sas grid | source | |
| 45 | Python Integration in SAS Studio | Alexey Vodilin | Video recording: Data engineering and data scientist teams are multidisciplinary, each with preferred skills and technologies. Some of them use SAS, others may have analytical assets already built in Python. The goal is to enable all types of users to leverage their best skills, ensuring governance and transparent orchestration of assets and enterprise access to data sources. With Python integration in SAS Studio programmers can code, execute and schedule Python scripts within SAS Studio application and add Python artifacts into a SAS Studio Flow. Users can also leverage integration with Git to streamline collaboration. SAS Lineage Viewer allows users to see which tables are used where and when Studio Flow contains Python program steps. | sas studio, python | source youtube |
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| 46 | Quantifying the Risk of Flood and Value at Risk | Mathilda Julin | Video recording: Due to climate change, extreme weather has become more frequent across the world. In the last couple of years, floods have caused major economic and emotional loss in Sweden. By quantifying climate risks, we are able to grasp the extent of possible losses and prepare for extreme scenarios. Using the geographical functions in SAS we can calculate distances on a map between the property's location and the riverbank and the distance of the different levels of flood, gathered from Swedish MSB. Using these distances and the different levels of flood, we can create a cumulative distribution function measuring the risk of flood for any given property. By assigning a loss value following a flood, the aggregated value at risk for an area or a portfolio can be measured. a portfolio can be measured. | variance, cumulative frequency, probability distribution | source | |
| 47 | Real Time Quality Control in Manufacturing Using SAS | Paul Koot | Video recording: Notilyze participated in the 2022 SAS Hackathon, making their debut in the manufacturing category. The team has immersed itself in SAS solutions to gain insights into business processes. They collaborated with HAI to develop hai-app.io. Notilyze aimed to gain insights into managing energy consumption, efficiency and product specifications. The team also wanted to test SAS IoT solutions to deal with real time data. Besides the reduction of greenhouse emissions that is a result of the use of traditional energy sources, the business aim to gain insights into managing energy consumption has only become more relevant since Notilyze's participation in the hackathon. Recent events have shown that energy prices can fluctuate with high volatility due to various circumstances. Optimizing energy usage during manufacturing processes can minimize the exposure of a manufacturer to these fluctuations. Team Notilyze used data from a semi-automated distillation process, which was used to explore business opportunities and gain insights with SAS Event Stream Processing. Team Notilyze used SAS Visual Analytics to discover and visualize insights for the customer. The team developed an add-on for the hai-app using a Kafka queue which facilitated streaming data into SAS using ESP. | quality control, stream processing, real-time processing | source | |
| 48 | Real-Time Solar Farm Monitoring Leveraging Streaming Analytics Framework | Steven Enck | Video recording: Deploying real-time analytics projects at scale requires a thoughtfully designed process. Fundamentally, that process must address all aspects of the traditional analytics lifecycle but be tailored to run as the data arrives continuously from many devices, sensors, and data sources. This presentation demonstrates a streamlined development and deployment approach that simplifies that process and dramatically improves time-to-value. Data is ingested from real-time sensors across the solar farm as well as from weather API queries in order to monitor key metrics related to power generation, weather conditions, and solar irradiance. These data are used to train and deploy machine learning models that predict energy output related to each string, combiner box, array, and inverter at the solar farm, thereby enabling continuous monitoring of all assets. This presentation will demonstrate the SAS technologies used to deploy the solution, including Event Stream Processing, Model Studio/Manager, and Visual Analytics. In addition, we will discuss how Streaming Analytics Framework integrates these technologies to accelerate delivery. | machine learning, stream processing, real-time processing | source youtube |
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| 49 | Reimagine Marketing With Reality-Tested AI for Moments That Matter | Suneel Grover | Video recording: As brands continue to explore and stress-test mechanisms for deriving actionable insight, AI trust is an emerging trend. The hype of martech innovation continues to soar, and every technology vendor is claiming to bolster the customer experience with ML and AI. At the intersection of data, analytics and marketing, acting on moments of significance between a brand and a customer matter. Is all AI built the same? No. Yet every vendor is pitching it. It isn't enough to capture and store first -, second-, third- and zero-party customer data. Feeding this data into automated or custom models helps serve the marketer's mandate with analytic scores, but still falls short on potential. To gain a competitive advantage, organizations must implement decisioning engines enhanced by model governance, AI bias detection and insights triggered by real-time customer behavior events contextualized by forward-thinking CDP capabilities with a ModelOps mentality. Lean in and look closely, and it becomes obvious that all AI is not built the same. Welcome to the era of next best experiences as brands try new approaches to experiment with personalizing products, offers and actions. In this session, we will highlight how SAS is removing adoption challenges to connect innovation from data science to martech use cases. If trust is critical when using analytics effectively, this is the moment where customer experience projects lift off for success or crash. | customer experience, model governance | source | |
| 50 | Risk Modeling and Decisioning: Analytics for Fun and Profit | Terisa Roberts | Video recording: Risk modeling and decisioning has undergone a steep change in recent years. Firms are navigating new types of risks such as pandemics, geopolitics and climate change by integrating diverse data and powerful analytics in front office systems for real time decisions. In this session, we'll highlight the newer, innovative methods that are driving better, deeper and forward-looking insights. These modern-day risk modeling approaches are not without risks of their own. But with the right controls, they deliver higher value decisions game-changing efficiency gains, significant benefits in new revenue, cost savings and a competitive advantage. | source youtube |
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| 51 | SAS Analytics in Microsoft Azure - AI Has Never Been Easier! | Rich Main | Video recording: SAS Viya is available on Microsoft Azure, and we're better together! Access all the SAS analytics capabilities you know and love, while integrating with Azure services at every level of the analytics stack - from data ingestion and preparation to building and deploying AI pipelines. SAS Viya offers a powerful combination of technologies for extracting insights from data, all protected by built-in security and management from Azure. The result? Anyone can implement AI at scale, anytime. Get ready to see it in action with this demo by Advisory Product Manager Rich Main. In this session, Rich will show you just how simple it is to expedite how you access, explore and prepare data in the cloud. Solve any analytics challenge using a wide range of tools, techniques, and built-in automation. Take advantage of robust integrations with Azure and open source resources. Use streamlined model deployment to get machine learning into production faster. Communicate the results of analytics projects to any audience. With out-of-the-box options for all skillsets, users with diverse roles and preferences can collaborate to build, deploy and manage best-in-class AI models on the SAS Viya platform. Whether you prefer low-code and no-code interfaces, you're a whiz with Jupyter notebooks, or you're a veteran SAS programmer, everything you need is right at your fingertips-you won't want to miss it. | sas viya, data ingestion, model deployment | source youtube |
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| 52 | SAS and Microsoft 365: An Excel-ent Partnership! | Sasha Karpinski, Tim Beese |
Video recording: With more than 1 billion users, Microsoft Office offers some of the most popular productivity tools in the world. Now imagine bringing the power of SAS Viya directly to where these users work every day. SAS for Microsoft 365 provides seamless integration between SAS Viya and Microsoft Office products like EXCEL, Outlook, and PowerPoint, allowing you to access analytical insights powered by SAS without ever leaving your Microsoft applications. You can view and interact with SAS Viya content like SAS Visual Analytics reports and SAS data, insert that content into your Microsoft documents, and refresh that embedded content with the latest information from SAS. Add to your EXCEL worksheets and PowerPoint presentations with embedded SAS content displaying key information with the most up-to-date data. Collaborate by inserting insights from SAS directly into your Outlook communications. You'll leave this session with a better understanding of how you can drive informed decisions by leveraging the power of SAS Viya and the familiarity of Microsoft Office using SAS for Microsoft 365. |
sas viya, excel | source youtube |
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| 53 | SAS Certification Demystified | Matt Scicchitano | Video recording: In this session, you are presented with an overview of the SAS Global Certification Program. We'll help you answer the question "Why get certified?" by demonstrating the value of these credentials in the job market. Here are the topics covered: | source youtube |
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| 54 | SAS Customer Intelligence 360 Recommenders, NLP and Stories About Tigers | Lucas Kelly, Lourdes Siman |
Video recording: Stories connect a person to a world that seems far away; a world filled with tigers, pandas and great blue whales. It is this connection between people and the natural world that drives so much of what we do at the World Wildlife Fund. The question is, how do we make the right connections with the right people? How do we personalize the web visitor's experience so that this connection has the greatest impact? In this presentation, WWF data scientists will detail how our partnership with SAS has allowed us to recommend specific stories to segments of our web visitor population. Using recommendation engines served through CI360 applications, we can present ocean lovers with ocean stories, forest dwellers with topics about the trees, and wildlife protectors with facts about tigers. We will explain how we advanced from out-of-the-box recommenders to innovative customized recommendation systems (Factorization Machines and Bayesian Personalized Ranking) using SAS Viya. Finally, we will detail how natural language processing of SAS 360 Discover data allowed us to cater these recommendation engines to specific segments, keeping our visitors on our website for longer periods of time and increasing the probability of meeting organizational goals. Join us as we show you how a story of a tiger in India can function as an entry point into a world of conservation. | recommendation engine, sas viya | source | |
| 55 | SAS Intelligent Monitoring: Anomaly Detection App in the Azure Marketplace | Saurabh Mishra | Video recording: Are you looking to easily deploy smart asset monitoring with zero code? Come learn about SAS Intelligent Monitoring! This exciting new offering on the Azure Marketplace helps your domain experts quickly add monitoring, rules and alerts to your in-service assets without data science or coding experience. The best part is you can get started in hours or days and avoid the traditional cycle of a months-long transformation project. Our solution makes it easy to add new and existing assets into the application, acquire IoT data using standard Azure services, gain rapid insights with intelligent data profiling, and streamline anomaly detection model definition and deployment across your operations. In this session, we will walk you through an introduction of the application, the process for provisioning on the Azure Marketplace and a hands-on demonstration of its capabilities. If you're ready to accelerate your digital transformation and time to value with IoT, don't miss this session! | outlier, data profiling | source | |
| 56 | SAS Model Studio: Building ML, Text Analytics and Forecasting Pipelines | Wendy Czika | Video recording: Building models is a critical phase of the analytics life cycle for machine learning, text analytics and forecasting. SAS Model Studio is a web-based application in SAS Viya with all the tools you need for this phase. In this environment, you can create pipelines representing the sequential tasks involved with building your model, including feature engineering, dimension reduction, model training and tuning, and model assessment and comparison, with insights for your project summarized for you. You can seamlessly transition to and from phases, including data preparation, wrangling on the front end and deploying your models on the back end. We'll give a demonstration of Model Studio with a focus on SAS Visual Machine Learning that includes some of our latest capabilities around AutoML, responsible AI and enhancements for model autotuning. We will also showcase features in Model Studio for SAS Visual Text Analytics and SAS Visual Forecasting. | machine learning, data wrangling, feature engineering | source youtube |
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| 57 | SAS Visual Investigator: Your Window Into SAS | Seb Charrot, Susan Trueman |
Video recording: How do I search my data? How do I action this decision? How do I investigate this further? How do I explore hidden relationships in my data? How do I bring a human into the loop? These are just some of the questions SAS Visual Investigator answers by offering an action and investigation tool that provides a window into the SAS ecosystem for the operational user. This super demo will illustrate the capabilities of SAS Visual Investigator and its touchpoints across SAS. | source youtube |
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| 58 | SAS Visual Text Analytics: Exploring Literature for Drug Safety Signals | Ari Zitin | Video recording: Explore the capabilities of SAS Visual Text Analytics by searching abstracts from biomedical and life sciences research literature for adverse event signals. In this workshop you will build a text analytics pipeline to extract key pieces of information from the literature that identify a safety risk in some previously marketed drugs. We use literature abstracts extracted from the National Library of Medicine's PubMed database to explore adverse event signals around cancer and cancer causing chemicals in the generic drug Ranitidine. We create custom concept rules in SAS Visual Text Analytics to highlight some of these safety signals, and we also see how to visualize these results in SAS Visual Analytics. This workshop is designed to be accessible to SAS users with no background in pharmacovigilance, the topic area was chosen to illustrate the use of text analytics on real-world data in the context of a real historical safety issue. | adverse events, life sciences | source youtube |
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| 59 | SAS Viya with SingleStore: Maximize the Value of Your Data | Bill Danker, Jason Secosky |
Video recording: Business leaders need to deliver next-generation analytics capabilities for faster decision insights, while also reducing costs, improving scalability and simplifying data access for data scientists across their organization. See how you can build an integrated transactional and analytical platform that supports query, reporting and AI model-building capabilities. You'll learn how to work directly with SingleStore DBMS tables in SAS Visual Analytics and how you can combine multiple data stores into an all-in-one database for analytics and AI workloads with built-in encryption, simplified data storage with compression and reduced data duplication. See also the Super Demo: SAS Viya With SingleStore: Maximize the Value of Your Data [DEMO] | sas viya, data science | source youtube |
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| 60 | SAS Viya With SingleStore: Maximize the Value of Your Data [DEMO] | Bill Danker | Video recording: Business leaders need to deliver next-generation analytics capabilities for faster decision insights, while also reducing costs, improving scalability and simplifying data access for data scientists across their organization. See how you can build an integrated transactional and analytical platform that supports query, reporting and AI model-building capabilities. You'll learn how to work directly with SingleStore DBMS tables in Visual Analytics andhow you can combine multiple data stores into an all-in-one database for analytics and AI workloads with built-in encryption, simplified data storage with compression and reduced data duplication. | sas viya, data science | source | |
| 61 | Sizing your SAS Viya 4 Environment | Tom Dogger | Video recording: At SaasNow, we have deployed dozens of SAS Viya 4 environments since the initial release at the end of 2020. While the underlying technology of SAS Viya 4 has radically changed from a microservices approach to a cloud-native Kubernetes deployment model, these changes are mostly invisible to end-users of the platform compared to SAS Viya 3. The new deployment model, however, impacts how to size and scale your environment. Many of our customers and partners have questions about sizing their SAS Viya 4 environment. In this presentation we will share our approach to sizing your SAS Viya environment. | sas viya | source | |
| 62 | Software Workshop: Advanced Tips and Tricks for Model Studio | Jeff Thompson | Video recording: In this presentation, we'll cover some advanced tips and tricks that model studio users may find helpful. Have you generated new inputs that are not interpretable and then tried to use the model interpretability features to gain insight? The model interpretability features use the uninterpretable inputs! We'll show a trick that forces the model interpretability features to use the original inputs. Do you have open source code or legacy SAS 9 code you'd like to run in a pipeline? We'll show how code which is external to SAS Viya can be run in a model studio pipeline. Have you ever tried to create custom plots in a pipeline? We'll use some custom SAS code along with the SAS code node to create plots not readily available from model studio nodes. | sas 9, sas viya | source youtube |
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| 63 | Software Workshop: Automated Large-Scale Forecasting | Chip Wells | Video recording: Explore SAS Visual Forecasting tools in the context of developing and maintaining a large-scale forecasting project. In this workshop, you will build and then refine a large-scale forecasting system. The focus is on selecting appropriate methods for data creation and variable transformations, model generation, and model selection. Methods for improving overall baseline forecasting performance are also implemented. | feature selection, data transformation | source youtube |
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| 64 | Software Workshop: End-to-End Machine Learning in Model Studio | Andy Ravenna | Video recording: Effective predictive modeling projects follow the SAS analytics life cycle, from data to discovery and then deployment. SAS Viya provides the capability to perform all these steps from one graphical user interface, making the transition between stages of the analytics life cycle seamless. In this workshop, you load data into memory, prepare input variables for modeling, and build complex analytics pipelines to demonstrate powerful machine learning models. Need to better understand your model? No problem. We'll show you how to produce model interpretability plots. Need to integrate open-source models? No problem. We'll show you how to do that and deploy any model with one click. Then the best-performing model is saved and packaged for deployment, and you still have the ability to retrain this model on new data -- all from the same shared interface. | machine learning, sas viya | source youtube |
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| 65 | Speaking to Microsoft Excel with PROC SQL in SAS Viya | Charu Shankar | Video recording: Microsoft EXCEL, SQL and SAS are all equally loved for their unique strengths. EXCEL has been a go-to for a long time. Database workers live in SQL. SAS Viya is a cloud-enabled, in-memory analytics engine that provides quick, accurate, and reliable analytical insights. What would it be like to stay in the comfort of SAS while beckoning EXCEL in to join data using PROC SQL. If you have wondered how this is possible, then come to this session. Watch this incredible trio in action. You will learn to bring in data from EXCEL to SAS Viya using SAS engines, join multiple EXCEL spreadsheets, summarize data within SAS Viya using PROC SQL, and send the results to EXCEL. And you do all these things within SAS. Charu will show you a great way to build a bridge between SAS coders and colleagues who never code. All levels welcome! |
excel, sas viya, proc sql | source youtube |
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| 66 | Struggling with Syntax? SAS Studio to the Rescue! | Jacqueline Johnson | Video recording: One of the more frustrating elements of learning to code in SAS is mastering the syntax. In this hands-on workshop, we will use SAS Studio tasks in SAS OnDemand for Academics to automatically generate code for a range of statistical analyses such as t-tests, analysis of variance, linear regression, and logistic regression. For even more flexibility in our modeling, we will also cover the autocomplete and dynamic syntax tooltips in the programming editor of SAS Studio - which aids in the construction of more dynamic statistical models. Both sets of SAS Studio tools will help you obtain results from statistical analyses faster - so that you can focus more on the results… rather than the syntax errors. For our academic partners, this means more time covering course content - which makes you, and your students, more productive. | sas studio, data science, anova | source youtube |
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| 67 | Teaching the Computer to See for Those Who Cannot | Jonathan Moreno Narvaez | Video recording: Forms are the main method of interacting with the digital world. We use forms to get everything done, big or small, many times, every single day. Yet most forms are impossible to work with, especially for people with disabilities. Team Funka created a test software, with the power of machine learning and computer vision to identify forms that are unusable by people who use assistive technologies. | machine learning | source | |
| 68 | The Batting Lab: Driving Home the Power of Data | Gunce Walton | Video recording: Designed to combine their favorite team sport with our vast data analysis experience, the Batting Lab was created for children to improve their batting performance while also gaining an understanding of the importance of data. SAS worked with the North Carolina State University's softball and baseball teams to collect data on the key moments of an elite player's swing. We then used those data points and employed our cutting-edge analytics to analyze, model and understand the dynamics of an optimal swing. Once the optimal phases of a swing were identified, the model was used to score the batting skills of aspiring players in real time. The Batting Lab helps children gain the confidence they need to succeed with a triple play of batting, analytics and data literacy. We invite you to come explore the power of the SAS Batting Lab. | data science, edge computing | source | |
| 69 | The Chart Chasers! Finding Lost Revenue for Healthcare Providers | Shane Hanley | Video recording: Value-Based Care (VBC) is a health care delivery model under which providers (hospitals, labs, doctors, nurses and others) are paid based on the health outcomes of their patients and the quality of services rendered. In this model, physicians can lose visibility into how the billing codes impact their payments. In addition to errors in incorrect coding, there are often multiple correct diagnose codes available for any given patient. These typically vary based on specificity, severity or combinations of conditions. Without visibility into payment impact, doctors often select the first available code and hope that they get paid. The Chart Chasers! won three category awards at the 2022 SAS Hackathon competition: Health and Life Sciences, Natural Language Processing, and the Americas region. The team used SAS Data Science and Decisioning to build a solution for creating automatically suggested billing re-codes for medical reviewers. They implemented text analytics, business rules, workflow features, code flagging and initial start/stop/synonym lists to develop initial analytic models. The team developed a custom interface for medical coding reviewers and subject matter experts to review suggestions and provide feedback for continuous model improvement. They also used the Medicare & Medicaid Services database to calculate the Medicare Risk Adjustments. This helps hospitals and revenue cycle management organizations recover lost money due to errors and optimal alternative coding. | quality of service, data science, risk adjustment | source | |
| 70 | The Science Behind the Batting Lab | Gunce Walton | Video recording: Designed to combine their favorite team sport with our vast data analysis experience, the Batting Lab was created for children to improve their batting performance while gaining an understanding of the importance of data. SAS worked with North Carolina State University's softball and baseball teams to collect data on the key moments of an elite player's swing. We then used those data points and employed our cutting-edge analytics to analyze, model and understand the dynamics of an optimal swing. Once the optimal phases of a swing were identified, the model was used to score the batting skills of aspiring players in real time. The Batting Lab helps children gain the confidence they need to succeed with a triple play of batting, analytics and data literacy. We invite you to come explore the power of the SAS Batting Lab. | data science, edge computing | source youtube |
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| 71 | These are a Few of Our Favorite SAS Functions | Richann J. Watson, Louise S. Hadden |
Video recording: SAS functions act as subroutines, combining arguments, operations and optional parameters, and they return a value as a result. These values can be either numeric or characters and can be used to create variables in expressions, via the DATA STEP, WHERE statements, the SAS macro language, within PROC REPORT and in PROC SQL. CALL routines are very similar to SAS functions, sometimes sharing the same name and providing the same or similar functionality. CALL routines, as the name implies, begin with CALL statements, with the routine name appearing after "CALL", followed by parenthetical arguments. As with SAS functions, the number of required and optional arguments vary. Functions and CALL routines fall into specific categories, including character and string-matching functions and CALL routines and mathematical functions. Our favorite functions, PRXMATCH and PRXCHANGE, CATT and CATX and mathematical functions, fall into these two broad categories. We will provide descriptions of our favorite functions, guidance on how to use these functions and individual business use examples. |
sas function, macro facility, proc report | source youtube |
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| 72 | Time to REST: An Overview of SAS API Use Cases on GitHub | Joe Furbee | Video recording: Fill the void, bridge the gap, elephant in the room, give 'em what they want. OK, I'll stop. These phrases came to mind and represented what we wanted to address with our SAS API use case project. The work is in progress - but we have good, tangible results to share. This session introduces developers to the SAS REST API end-to-end use cases repository on sassoftware GitHub. Learn how to navigate it, how to use it and how to contribute to it. As SAS increases its focus on APIs and open-source integration, there's a need to identify common use cases for APIs and provide concrete examples. The project focuses on enriching and simplifying SAS API documentation and provides end-to-end use cases. to the goal is to cultivate the developer experience which will ultimately increase adoption of SAS APIs. The repository compiles multiple use cases which are available in various coding languages. During the session, you'll see the repository and be guided through a use case, from authentication to processing the results. SAS encourages and facilitates user contributions to the GitHub repository. In addition, find out how users can create and share their own use cases. | rest api | source youtube |
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| 73 | Unified ModelOps and Containerized Deployment for All Models | Glenn Clingroth, Sophia Rowland |
Video recording: SAS Model Manager acts as a unified model repository for SAS and open source models, where models can be registered, managed, monitored and deployed from one central location. Using SAS Model Manager, organizations can establish repeatable and standardized ModelOps processes to traverse the last mile of analytics and get the most value from their analytical investments. Now organizations can move a model from analytical development environments and workbenches through validation to production in a governed and managed manner. Using SAS Container Runtime, models can be deployed into lightweight, portable and standardized containers with no recoding required. SAS Model Manager has complete, out-of-the-box functionality to make it accessible to frontline workers, risk teams, data scientists, IT, ModelOps engineers, managers and executives. All users can understand and provide input into the ModelOps process, balanced with the ability to extend our tool and build custom solutions programmatically. By creating a solution where multiple parts of the organization can collaborate on the ModelOps process, we help reduce silos and improve business outcomes through efficient use of models for better decision making. | sas model manager, data science, data cleaning | source | |
| 74 | Using Machine Learning to Enhance Short-Term Demand Sensing | Charlie Chase | Video recording: Consumer packaged goods (CPG) companies account for some of the biggest industries in the world and provide items that are used regularly by consumers including food, beverages and other household products. Since many products provided by CPG companies have short shelf lives and are intended to be used quickly, companies need to routinely replenish products on store shelves to meet consumer needs. Effective supply chain management is critical to ensure the timely replenishment of products by properly managing the movement and storage of raw materials and finished goods from the point of origin to the point of consumption. A key component of supply chain management for retailers and CPG companies is forecasting short-term consumer demand accurately to ensure their products are available to consumers when they need them. Implementing a short-term forecast (one-to-eight-week) is critical to understanding and predicting changing consumer demand associated with sales promotions, events, weather conditions, natural disasters and other unexpected shifts in consumer demand patterns. Short-term demand sensing allows retailers and CPG companies to predict and adapt to those changing consumer demand patterns. | machine learning | source | |
| 75 | Using National Crime Data to Improve Law Enforcement | Brian Acken | Video recording: Most police agencies across the globe regularly submit their data to national systems to track crime statistics. SAS has been researching how this data can be used to gain greater insight into local agency trends and areas of interest. In this breakout session, see SAS' current developments for ingesting crime data using SAS technologies and how they provide an elevated awareness to the story within the data. Discover the steps SAS is taking to make loading data faster, the tools that can be used to understand and visualize data and how agencies across the globe will benefit. | source youtube |
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| 76 | Using Python for Data Analytics in SAS Viya | Peter Styliadis | Video recording: Unite the Python language with the analytic power of SAS. In this presentation, you learn how to use the SWAT (SAS wrapper for analytics transfer) package to take advantage of the SAS cloud analytic services (CAS) engine in SAS Viya for massively parallel processing (MPP). We begin with a quick overview of SAS Viya and the CAS engine and then discuss how to leverage the strengths of the CAS engine and your local Python client, how to connect Python to CAS, and how to access and load data into CAS's MPP environment. Then we dive into exploring, preparing, and analyzing data using the CAS server, taking advantage of the CAS server's distributed processing power using familiar Pandas API and CAS actions from the SWAT package. Lastly, we learn how to unite traditional Python packages such as Pandas and matplotlib with the summarized results from the CAS server for additional processing and visualization. | sas viya, cas, cas action | source zip youtube |
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| 77 | Using SAS to Download Files From Amazon Web Services S3 | Michael A. Raithel | Video recording: The popularity of cloud computing is resulting in more organizations storing data in clouds and processing it off premises. It's a matter of time before many SAS programmers will be tasked with accessing client data stored in cloud structures. A Westat project was tasked with downloading objects stored in Amazon Web Services (AWS) Simple Storage Services (S3) buckets. The assignment was for a list of objects to be downloaded from an S3 bucket every week. This presentation will start with an overview of cloud computing services and the top cloud providers. Next, we will discuss AWS S3 and how SAS PROC S3 can be used to process objects in S3. You will learn about a SAS macro program that was written to access a given S3 bucket and download a set of objects whose names were specified in a flat file. The macro program is general enough that it can be used as-is to download files. The program can also be used as a jumping-off point for writing programs that perform other functions on objects stored in S3 buckets. |
flat file, sas programmer, macro definition | source youtube |
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| 78 | Using Simulation to Plan and Rescue Clinical Trial Enrollment | Jim Box | Video recording: The key factor to successfully completing a clinical trial and achieving the required timeline is to have a solid plan that forecasts how patients will be enrolled into the trial. These forecasts are typically built from assumptions about the number of countries and investigator sites to use, how long it will take them to get operational, and what patient enrollment rates they can achieve. Unfortunately, traditional enrollment predictions using these factors are usually accomplished by applying point estimates and educated guesses that do not take variability into account. This leads to inaccurate projections that are usually not met during the trial operation. In comparison to this traditional approach, the SAS Clinical Enrollment Simulation Cloud allows the study planner to build in variability to the estimates which will show a more accurate picture of how enrollment is likely to progress and the probability of hitting key milestones. User can also modify input values to create "what if" scenarios which can identify a best path forward and be used to inform the strategic decisions when enrollment falls short of targets. | clinical trial | source | |
| 79 | Visual Studio Code SAS Programming Extension: Meeting You Where You Work | Casey Smith | Video recording: Visual Studio Code (VS Code) is a popular development environment for programmers. It is free, built on open source and runs everywhere. In addition to robust out-of-the-box software development features, its rich extensibility model makes VS Code powerful. Extension authors have contributed many VS Code extensions, which improve VS Code functionality. SAS recently contributed its own official SAS Extension for Visual Studio Code to the VS Code Marketplace, which makes it more convenient to use VS Code for programming in the SAS language. The SAS Extension for Visual Studio Code provides SAS language features, including SAS syntax highlighting, color themes, code completion, pop-up syntax help, snippets and the ability to run your SAS code and view results directly from VS Code. Come see how you can more efficiently develop SAS programs in VS Code using the SAS Extension for Visual Studio Code! | sas syntax, sas programming | source youtube |
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| 80 | What to Know About SAS and Microsoft 365 Integration | Tim Beese | Video recording: With more than 1 billion users, Microsoft Office offers some of the most popular productivity tools in the world. Now imagine bringing the power of SAS Viya directly to where these users work every day? SAS for Microsoft 365 provides seamless integration between SAS Viya and Microsoft Office products like EXCEL, Outlook and PowerPoint - giving you to access analytical insights powered by SAS without ever leaving your Microsoft applications. You can view and interact with SAS Viya content like SAS Visual Analytics reports and SAS data, insert that content into your Microsoft documents, and refresh that embedded content with the latest information from SAS. Augment your EXCEL worksheets and PowerPoint presentations with embedded SAS content displaying key information with the most up-to-date data. Collaborate more effectively by inserting meaningful insights from SAS directly into your Outlook communications, then sharing those insights with your colleagues. In this session, you'll gain a better understanding of how you can drive better-informed decisions by leveraging the power of SAS Viya and the familiarity of Microsoft Office using SAS for Microsoft 365. |
sas viya, excel | source youtube |
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| 81 | Workload Management on SAS Viya:Orchestrate Your Viya Processing | Wes Gelpi, Alex Daehnrich |
Video recording: As organizations create analytic and data management workloads inSAS Viya, they are faced with challenges in balancing cost and agility. The SAS solution to balance good Viya performance with reasonable infrastructure costs is the SAS Workload Management add-on to Viya. SAS Workload Management extends the capabilities of Kubernetes by adding priority-based queues, providing the ability to control where and when jobs are processed based on prioritization and resource allocation. In this session, the value and features of SAS Workload Management will be discussed and demonstrated. | resource allocation, sas viya, data governance | source |
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