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data validation rules

480 papers and 57 presentations; 494 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 Code Hard and Put away Wet: Replacing Hardcoded SAS Software Quality Checks with Data-Driven Design and Defensive Programming Techniques That Validate Code and Control Data Troy Martin Hughes source 8
WUSS 2026 Introducing Source2Zahn: Automating Source-to-Target Mapping for SAS Modernization [presentation] Mike Krizan source 45
PharmaSUG CN 2026 AI-Powered R Shiny Tool for Automated Footnote Comparison Across TLF Packages and Shells Yuan Sun source 11
PharmaSUG 2026 Bridging the Gap: Table-Driven SAS Programming as a Pathway to AI in Clinical Trials Statistical Programming James Sun,
Vijaya Nadella,
Daniel Qi		 source 15
PharmaSUG 2026 Closing the Loop: Validating AI-Generated SDTM Mappings using CDISC CORE and Synthetic Data Pietro Belligoli,
Constantin Weberpals,
Yarhy Flores Lopez		 source 7
PharmaSUG 2026 Code Hard and Put away Wet: Replacing Hardcoded SAS Software Quality Checks with Data-Driven Design and Defensive Programming Techniques That Validate Code and Control Data Troy Martin Hughes source 8
PHUSE US 2026 Accelerating Study Build Using AI Enabled CRF Design Jeremy Zhang,
Aimee Basile		 source
presentation source		 7
PHUSE US 2026 Automated Programming Consistency Checks: Enhancing Clinical Programming Quality, Efficiency and Scalability Narendra Babu Kolisetty source
presentation source		 5
PHUSE US 2026 Automating SDTM Compliance: A Web-Based SDTM Quality Control Tool Enhancing Clinical Trial Data Integrity Indraneel Narisetty,
Gopal Reddy Palvatla		 source
poster source		 11
PHUSE US 2026 Check Yourself: Edit Checks and Queries Made Easy with Shiny Maya Gans source
presentation source		 8
PHUSE US 2026 Creating Synthetic Data that Mimics Real-World Data for Accurate Analysis Programming Development Linshan Yuan,
Weiwei Xu		 source
poster source		 5
PHUSE US 2026 Harnessing AI: Enhancing Test Data Quality and Efficiency in Clinical Trial Set-Up Rita Pecuch,
Varun Jagadeesh		 source
poster source		 8
PHUSE US 2026 Key Guidelines, Tricks and Experiences for the PMDA and a Comparison with FDA and NMPA CDE Submissions Ramesh Potluri source
presentation source		 5
PHUSE US 2026 Leveraging Python for Synthetic External Vendor Data Generation for eCOA and ePRO Hitesh Raval source
presentation source		 9
PHUSE US 2026 Optimising Trial Design Dataset Creation To Minimise P21 Compliance Issues Rama Kudaravalli source
presentation source		 6
PHUSE US 2026 Pre-Conf as a Data Review Layer: An AbbVie Case Study for Optimised Clinical Data Flow Gian Prakash,
Aman Thukral		 source
presentation source		 2
PHUSE US 2026 Problem-First Agentic AI: Transforming Statistical Computing with Purposeful Automation Rajesh Hagalwadi source
presentation source		 8
PHUSE APAC 2026 eDataValidator (eDV): Validating Clinical Data for Confident Submissions Pratika Chatterjee source
poster source		 4
PHUSE EU 2025 ADaM Conformance Rules: Bridging the Gap Between Standards and Practice Rafik Ghazaryan source
presentation source		 6
PHUSE EU 2025 Check Yourself: Edit Checks and Queries Made Easy with Shiny [presentation] Kirsty R. Lauderdale,
Maya Gans		 source 10
PHUSE EU 2025 Efficient Conversion of SDTM/ADaM Specifications from Excel to Define-XML v2.1 Using Pinnacle 21 Community Hiromi Okada,
Seiko Yamazaki		 source
presentation source		 15
PHUSE EU 2025 Enhancing the Validation and Simulation of Real-World Multi-Site Data with R Nikolay Trankov,
Elena Chaparova,
Alexandrina Lambova,
Stavros Oikonomou		 source
presentation source		 11
PHUSE EU 2025 Launching CDISC CORE v1.0: A New Standard for Automated Study Conformance [presentation] Tomás Sabat Stofsel,
Nick De Donder		 source 44
PHUSE EU 2025 Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations Harinarayanan Gopichandran source
presentation source		 8
PHUSE EU 2025 Why Wait for Real Data? The Power of Synthetic Data in Modern Clinical Trials Abhijeet Arora source
presentation source		 6
MWSUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Clinical Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
SESUG 2025 Code Hard and Put away Wet: Replacing Hardcoded SAS Software Quality Checks with Data-Driven Design and Defensive Programming Techniques That Validate Code and Control Data Troy Martin Hughes 8
SESUG 2025 Data Diagnostics with Base SAS Mark L. Jordan 38
SESUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Pharmaceutical and Clinical Trials Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes 9
SESUG 2025 Lookup Tables (LUT) in SAS and Data-Driven Programming Imelda C. Go,
Abbas S. Tavakoli		 17
WUSS 2025 Accredited, Bona fide, Certified, Diploma'ed, and Edumacated: The ABCDEs of Automating the Validation and Monitoring of Professional Requirements for Employees and Job Candidates Through Dynamic, Data-Driven SAS Reporting Troy Martin Hughes source 20
WUSS 2025 Chasing Master Data Interoperability: Facilitating Master Data Management (MDM) Objectives Through CSV Control Tables that Contain Data Rules that Support SAS and Python Data-Driven Software Design Troy Martin Hughes source 5
WUSS 2025 Last Observation Carried Forward (LOCF) in Longitudinal Clinical Studies: Adopting a Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
PharmaSUG 2025 Considerations of R submission in Japan Yuichi Nakajima,
Yasutaka Moriguchi		 source 5
PharmaSUG 2025 Data management and biostatistics synergy: how to achieve and what can be expected Diana Avetisian source 11
PharmaSUG 2025 Key guidelines, Tricks and Experiences for PMDA and comparison with FDA and CDE submission Ramesh Potluri source 6
PharmaSUG 2025 Last Observation Carried Forward (LOCF) in Longitudinal Patient Studies: A Functional Approach to Imputing Missing Values Using PROC FCMP, the SAS Function Compiler Troy Martin Hughes source 9
PharmaSUG 2025 Use Gen AI to program rules in R & Python to generate and validate metadata for data standards and study specifications. Priyanka Sawant,
Kairav Tarmaster		 source 9
PHUSE US 2025 CDISC Open Rules: A Deep Dive into Custom Rule Creation Roman Radelicki source
presentation source		 12
PHUSE US 2025 Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers Julie Ann Hood source
poster source		 4
PHUSE US 2025 Future-Proofing Clinical Data Standards: Preparing for AI and Machine Learning Shivoy Pandita source
presentation source		 8
PHUSE US 2025 Measure Total Steroid Dose Using Real-World Data Yi-Chien Lee source
poster source		 2
PHUSE US 2025 Turbocharge Your Trials: Transform CRF Creation and the CDISC standardization process with Xbiom's Smart Metadata Repository and AI/ML Integrations Harinarayanan Gopichandran source
presentation source		 8
PHUSE US 2025 Using Custom GPT to Write Edit Checks Andrew Burd source
presentation source		 3
MWSUG 2024 Simplify Complex SAS Logic through the Power of Bit Level Data Comparison Kent Phelps,
Ronda Phelps		 source 18
PHUSE EU 2024 FDA Business Rules and CDISC Open Rules: The Road to Adoption Nick De Donder source
presentation source		 4
PHUSE EU 2024 Guidance Beyond the SDTM Implementation Guide Kristin Kelly source
presentation source		 10
PHUSE EU 2024 Harmonising FDA and PMDA Submission Requirements Luca Semeraro source
presentation source		 12
PHUSE EU 2024 Mapping a Veeva SDS Specification to ODM-XML Jørgen Mangor Iversen source
presentation source		 7
SESUG 2024 Data Diagnostics with Base SAS Mark L. Jordan source 37
SESUG 2024 Hands-on Python PDFs: Using the pypdf Library To Programmatically Design, Complete, Read, and Extract Data from PDF Forms Having Digital Signatures Troy Martin Hughes source 22
WUSS 2024 Hands-on Python PDFs: Using the pypdf Library To Programmatically Design, Complete, Read, and Extract Data from PDF Forms Having Digital Signatures Troy Martin Hughes source 22
PharmaSUG CN 2024 An Automatic SDTM Platform: Create Your SDTM Since Case Report Form is Ready! Mingyue Zhu,
Wei Wang,
Mingfeng Zhou		 source 12
PharmaSUG 2024 An approach to make Data Validation and Reporting tool using R Shiny for Clinica Data Validation Madhavi Gundu,
Vivek Jayesh Mandaliya		 source 10
PharmaSUG 2024 Elevate Your Game: Leveling Up SDTM Validation with the Magic of Data Managers Julie Ann Hood,
Jen Manzi		 source 5
PharmaSUG 2024 Guidance Beyond the SDTM Implementation Guide Kristin Kelly,
Michael Beers		 source 11
PharmaSUG 2024 Optimizing Clinical Data Processes: Harnessing the Power of Metadata Repository (MDR) for Innovative Study Design (ISD) and Integrated Summary of Safety (ISS) / Efficacy (ISE) Lakshmi Mantha,
Purvi Kalra,
Arunateja Gottapu		 source 9
PharmaSUG 2024 Simplifying Edit Check Configuration Vandita Tripathi,
Manas Saha		 source 7
PharmaSUG 2024 Your Guide to Successfully Upversioning CDISC Standards David Neubauer,
Kapila Patel,
Toral Patel,
Soumya Rajesh		 source 19
PHUSE US 2024 Beyond Outliers: Unsupervised Anomaly Detection in Clinical Trial Data Helena Yaben,
Kian Norouzi		 source
presentation source		 9
PHUSE US 2024 Beyond the Hype: A Pragmatic Approach to Leveraging AI/ML for Data Review Robert Musterer source
presentation source		 10
PHUSE US 2024 Demystifying Submissions to NMPA China [presentation] Hiral Raval,
Dyuthi Yellamraju		 source 19
PHUSE US 2024 Future Clinical Data Submission Standards: CDISC, FHIR, OMOP, or Hybrid Model Jeffrey M. Abolafia,
Sarah Ferko,
Ingeborg Holt		 source
presentation source		 10
PHUSE US 2024 Guidance Beyond the SDTM Implementation Guide Michael Beers,
Blue Bell		 source
presentation source		 10
PHUSE US 2024 How to Monitor SDTM Data Health Amanda Cross source
presentation source		 8
PHUSE US 2024 My Data Are Too Good to Be True! Should I Worry About Fraud or Sloppiness? Johann Proeve source
presentation source		 9
PHUSE EU 2023 'Beep Beep': A Metadata Code Writer to Generate SAS Programs Giuseppe Di Monaco source
presentation source		 10
PHUSE EU 2023 A Robust Framework to Provide and Validate Real-Time SDTM Data Bremer Louw source
presentation source		 11
PHUSE EU 2023 Data Managers and R Programming: The Unlikely Pair Anaelle Perretti (Bonetta) source
presentation source		 9
PHUSE EU 2023 Practical Operations of Electronic Study Data Submissions Priyanka Pujari source
presentation source		 9
WUSS 2023 Picking Scabs and Digging Scarabs: Refactoring User-Defined Decision Table Interpretation Using the SAS Hash Object To Maximize Efficiency and Minimize Metaprogramming Troy Martin Hughes,
Louise S. Hadden		 source 15
PharmaSUG 2023 'TUFF' LOVE: SDTM Pain Points Explained! Kristin Kelly,
Michael Beers		 source 12
PharmaSUG 2023 Can We Do It Better? Real-Time Validation Of Sdtm Mapping Is Superior To Double Programming Daniel Rolo,
Bremer Louw		 source 9
PharmaSUG 2023 CDISC Conformance and Compliance: So Many Resources, So Little Time! Jennifer K. Fulton,
Stephen Black		 source 11
PharmaSUG 2023 CDISC SDTM IG v3.4: Subject Visits Ajay Gupta source 7
PharmaSUG 2023 Comparison of My Experience Between an Independent Consultant and an Employee Kriss Harris source 11
PharmaSUG 2023 From FDA to PMDA submission: How to resolve CDISC non-compliance issues Karin Steffensen,
Carina Brixval		 source 16
PharmaSUG 2023 How Can I Put This? - Using a pre-defined spreadsheet to explain your Pinnacle 21 Enterprise Issues Mike Lozano source 12
PharmaSUG 2023 Industry metrics for standards utilization and validation rules Sergiy Sirichenko source 13
PharmaSUG 2023 Picking Scabs and Digging Scarabs: Refactoring User-Defined Decision Table Interpretation Using the SAS Hash Object To Maximize Efficiency and Minimize Metaprogramming Troy Martin Hughes,
Louise S. Hadden		 source 15
PharmaSUG 2023 Study Data Technical Rejection Criteria (TRC) Considerations for Multiple Data Packages in a Single Submission Christine S Teng,
Janet Low,
Si Ru Tang		 source 10
PharmaSUG 2023 Using P21 Checks to Help Your DM Out! Chad Fewell,
Jesse Beck		 source 4
PHUSE US 2023 A Pragmatic Approach to Data Cleaning - Decisions in Selecting When to Apply AI/ML [presentation] Robert Musterer,
Alison Banda		 source 15
PHUSE US 2023 Custom Domains ... the Gaps in Standardized Data Michael Beers source
presentation source		 8
PHUSE US 2023 Decentralized Clinical Data Management (D-CDM): An Innovative 3-Way Approach (Risk-Data-Analytics) to Protect Data Integrity [presentation] Nithiyanandhan Ananthakrishnan,
Mukesh Babu K		 source 13
PHUSE US 2023 Say No to Stale Data!! Implementation of Automated GxP Data Pipelines Using KNIME [presentation] Shiva Katepalli,
Jeffrey Xiong		 source
video		 30
PHUSE US 2023 Technical Rejection Criteria for Study Data (TRC) and Beyond Lina Cong,
Jiang Xu		 source
presentation source		 4
PHUSE EU 2022 Bioresearch Monitoring Data Reviewer's Guide (BDRG) [presentation] Jack Field,
Steve Fitzpatrick		 source
video		 20
PharmaSUG 2022 Begin with the End in Mind: eCOA data from collection to analysis Franklin E. Menius,
Monali Khanna,
Vincent Allibone		 source 7
PharmaSUG 2022 Damn*t, The Define! Julie Ann Hood,
Sarah Angelo		 source 16
PharmaSUG 2022 Lessons Learned from Using P21 to Create ADaM define.xml with Examples Yizhuo Zhong,
Christine S Teng,
Majdoub Haloui		 source 8
PharmaSUG 2022 Redefining Industry Standards: Making CDASH and SDTM Work Together from the Database Level Chad Fewell,
Jesse Beck		 source 5
PharmaSUG 2022 SAS Spontaneous Combustion: Securing Software Portability through Self-Extracting Code Troy Martin Hughes source 15
PHUSE US 2022 An open-source project to map lab terminology and standardize units for analysis Sunil Kumar Pusarla,
Kevin R. Viel,
Dante Di Tommaso		 source
video
presentation source		 7
PHUSE US 2022 FDA Study Data Technical Rejection Criteria (TRC): What You Need to Know! [presentation] Jiang Xu,
Lina Cong		 source
video		 26
PHUSE US 2022 Standards Governance Strengthened by MDR Technology [presentation] Kenneth Stoltzfus,
Maria Sekac		 source 22
PHUSE US 2022 The Bioresearch Monitoring Data Reviewer's Guide (BDRG) [presentation] Julie Maynard,
Sopan Dharma Kaith		 source 25
PHUSE US 2022 Transformation from Prescriptive Clinical Data Analyses to Dynamic Data-driven Analytics through the Adoption of Modularized Cloud Components [presentation] Andy Ratcliffe,
Chris Decker		 source 35
PHUSE EU 2021 Software Demonstration: Aspire "Out of this World" Demo - Sponsored by d-wise [presentation] Andy Ratcliffe source 44
PHUSE EU 2021 The Library Approach Driving EDC Set-up Efficiencies: A Case Study [presentation] Jan De Cleir source
video		 23
PHUSE US 2021 Controlled Terminology Best Practices [presentation] Sarah Angelo source
video		 29
PHUSE US 2021 FDA & PMDA Validator Rules - What, Why and How ... But Should You Care? [presentation] Charanjit Kahlon,
Kishore Pothuri		 source
video		 21
PHUSE US 2021 FDA Conformance Analysis and Upcoming Implementation of Technical Rejection Criteria for Study Data [presentation] Ethan Chen,
Heather Crandall		 source 36
PHUSE US 2021 Leadership Presentations: LE02: How to Build Knowledge Capacity for a High-performance Team [presentation] Xiaohui Wang source 14
PHUSE US 2021 Pinnacle 21: Improving the Data Fitness Score for eSubmission Renu Motwani source
video
presentation source		 9
PharmaSUG 2021 Effective Approach for ADaM Submission to FDA and PMDA Ranvir Singh source 6
PharmaSUG 2021 FDA Study Data Technical Rejection Update [presentation] Ethan Chen source 36
PharmaSUG 2021 SEND for CBER Lisa Lin source 26
PHUSE EU 2020 Data Integrity & Standards in the Clinical Data Pipeline [presentation] Mark Wheeldon,
Raj Indupuri		 source
video		 30
PHUSE EU 2020 Digital Data Flow - A Solution for Study Start-up and Amendments [presentation] Palanipandiyan Chokkalingam,
Srinivasan Mahalingam		 source
video		 22
PHUSE EU 2020 Getting It Right: Refinement of SEND Validation Rules [presentation] Kristin Kelly source
video		 29
PHUSE EU 2020 Novel eCRF Study Template to Support Adaptive Design Studies in Medidata Rave [presentation] Nele Claes,
Ray Lacchman		 source
video		 29
PHUSE EU 2020 Shining Up Our Department: Producing a Biostatistics Metrics Dashboard in Shiny [presentation] Alanah Jonas,
Ann Fitzherbert		 source
video		 17
PHUSE EU 2020 SUPPQUAL Datasets: The Good, the Bad and the Ugly [presentation] Sergiy Sirichenko source
video		 40
SGF 2020 How to Master a Risk Data Vault Using SAS Data Integration Studio Linus Hjorth source 11
SGF 2020 Relationship analysis and customer churn forecasting in a financial cooperative institution Carolina Silva,
Brunno Sousa Ramos		 source 7
SGF 2020 Steer Your Hybrid SAS Viya/SAS9 Ship Toward the 'Governed Data' Port Bogdan Teleuca source 15
PharmaSUG 2020 Challenges and solutions for e-data submission to PMDA even after submission to FDA Akari Kamitani,
HyeonJeong An,
Yura Suzuki,
Malla Reddy Boda,
Yoshitake Kitanishi		 source 14
PharmaSUG 2020 Data Review: What's Not Included in Pinnacle 21? Jinit Mistry,
Lyma Faroz,
Hao Meng		 source 7
PharmaSUG 2020 Getting It Right: Refinement of SEND Validation Rules Kristin Kelly source 7
PharmaSUG 2020 Pinnacle 21 Community v3.0 - A Users Perspective Ajay Gupta source 10
PharmaSUG 2020 Project Metrics - a powerful tool that supports workload management and resource planning for Biostats & Programming department. Jian Hua (Daniel) Huang,
Rajan Vohra,
Andy Chopra		 source 11
PHUSE US 2020 Confusing Data Validation Rules Explained, Part 2 Michael Beers,
Blue Bell		 source 6
PHUSE US 2020 Connected Monitoring Mike Henderson source
presentation source		 6
PHUSE US 2020 FDA Study Data Guidance Update Ethan Chen source
presentation source		 6
PHUSE US 2020 FDA View: FDA Study Data Heather Crandall source 6
PHUSE US 2020 Getting It Right: Refinement of SEND Validation Rules Kristin Kelly,
Blue Bell		 source
presentation source		 6
PHUSE US 2020 Handling Duplicate Records in SDTM for Effective Resolution and Explanation in Data Submission Varun Debbeti source
presentation source		 8
PHUSE US 2020 Implementation of Metadata Repository & Protocol Automation at Bayer Pharma Girish Rajeev,
Julius Kusserow		 source
presentation source		 3
PHUSE US 2020 Industry Experiences Submitting Standardized Study Data to Regulatory Authorities Janet Low,
Vincent Guo		 source
presentation source		 12
PHUSE US 2020 Standards Compliance - An Automated Way to Measure the Interoperability of Clinical Studies Rammprasad Ganapathy source
presentation source		 6
PHUSE US 2020 Validation Consistency and Conformance Checking of SEND Datasets Isaac Mativo,
Mohit Matthew		 source
presentation source		 6
PHUSE EU 2019 Data Everywhere: What Does Risk-based Monitoring Mean for Data Management? Swapna Pothula source
presentation source		 5
PHUSE EU 2019 Implementing the CDISC Library API in Software Applications: First Experiences Jozef Aerts source
presentation source		 7
PHUSE EU 2019 TS does not mean T(o) S(uffer) - A hands-on guideline for a better understanding of the TS domain Kristina Zweier source
presentation source		 14
SESUG 2019 Making Life Easier on the SAS End: Best Practices for Collecting Survey Data Collecting Survey source 11
MWSUG 2019 The Doctor Ordered a Prescription ... Not a Description: Driving Dynamic Data Governance Through Prescriptive Data Dictionaries That Automate Quality Control and Exception Reporting Troy Martin Hughes 20
WUSS 2019 A Strategy for Dealing with Pinnacle 21 Errors and Warnings Carey G. Smoak source 2
WUSS 2019 From Readability to Responsible Risk Management: Facilitating the Automatic Identification and Aggregation of Software Technical Debt within an Organization Through Standardized Commenting in SAS Program Files and SAS Enterprise Guide Project Files Troy Martin Hughes source 35
PharmaSUG 2019 A Practical Guide to the Issues Summary in the Data Conformance Summary of Reviewer's Guides Gary E. Moore source 15
PharmaSUG 2019 Automate the Process to Ensure the Compliance with FDA Business Rules in SDTM Programming for FDA Submission Xiangchen (Bob) Cui,
Hao Guan,
Min Chen,
Letan (Cleo) Lin		 source 16
PharmaSUG 2019 CBER Data Standards Update and BioCompute Progress Elaine Thompson source 27
PharmaSUG 2019 Process optimization for efficient and smooth e-data submissions to both FDA and PMDA Eri Sakai,
Malla Reddy Boda,
Akari Kamitani,
Yoshitake Kitanishi		 source 13
PharmaSUG 2019 Strategy to Evaluate the Quality of Clinical Data from CROs Charley Z. Wu source 7
PharmaSUG 2019 Updates on validation of ADaM data Sergiy Sirichenko source 9
PharmaSUG 2019 Ushering SAS Emergency Medicine into the 21st Century: Toward Exception Handling Objectives, Actions, Outcomes, and Comms Troy Martin Hughes source 24
SGF 2019 Creating a Strong Business Case for SAS Event Stream Processing Henrique Consolini Danc source 16
SGF 2019 Data Governance: Harder, Better, Faster, Stronger Vincent Rejany source 18
SGF 2019 Data Modeling for a Better Analytical Environment Linus Hjorth source 12
SGF 2019 Factorization Machines, Visual Analytics, and Personalized Marketing Suneel Grover source 26
SGF 2019 Making Life Easier on the SAS End: Best Practices for Collecting Survey Data Julie Plano,
Keli Sorrentino		 source 11
PHUSE US 2019 A Paradigm Shift to Represent and Manage Clinical Data Standards for Creating Data-driven Specification Veena Nataraj source
presentation source		 9
PHUSE US 2019 CDISC Doesn't Tell You What to Collect But Regulators Do! Diane Wold source
presentation source		 4
PHUSE US 2019 Don't Let Your Data Handle You: A Novel Approach to Clinical Programming Jorine Putter source
presentation source		 10
PHUSE EU 2018 Best Practice for Explaining Validation Results in the Study Data Reviewer's Guide Kristin Kelly,
Michael Beers		 source
presentation source		 8
PHUSE EU 2018 Challenges of Submitting Electronic Study Data to Two Authorities: The PMDA & FDA Torsten Petsching source
presentation source		 6
PHUSE EU 2018 Collaborative Working Groups - Why You Should Take Part! Beate Hientzsch source
presentation source		 5
PHUSE EU 2018 Conformance Rules - How to Follow and Comply When Specified by Multiple Sources? Francis Dsa source
presentation source		 4
PHUSE EU 2018 Diagnostics of technical errors in define.xml file Sergiy Sirichenko,
Max Kanevsky		 source
presentation source		 9
PHUSE EU 2018 Handling CRF Design Changes in a Live Environment Andre Snelting,
Nieke De Ruiter		 source
presentation source		 10
PHUSE EU 2018 Updates on validation of ADaM data Max Kanevsky,
Sergiy Sirichenko		 source
presentation source		 7
SESUG 2018 A Shorter Path to Moving Data Profiles from SAS Data Management Studio to SAS Data Management Server Wayne Hileman source 15
SESUG 2018 Accredited, Bona fide, Certified, Diploma'ed, and Edumacated: The ABCDEs of Automating the Validation and Monitoring of Professional Requirements for Employees and Job Candidates Through Dynamic, Data-Driven SAS Reporting Troy Martin Hughes source 20
SESUG 2018 The Doctor Ordered a Prescription ... Not a Description: Driving Dynamic Data Governance Through Prescriptive Data Dictionaries That Automate Quality Control and Exception Reporting Troy Martin Hughes source 20
SESUG 2018 When Reliable Programs Fail: Designing for Timely, Efficient, Push-Button Recovery Troy Martin Hughes source 14
MWSUG 2018 From Readability to Responsible Risk Management: Facilitating the Automatic Identification and Aggregation of Software Technical Debt within an Organization Through Standardized Commenting in SAS Program Files and SAS Enterprise Guide Project Files Troy Martin Hughes 35
WUSS 2018 How FDA will reject non-CDISC submission Kevin Lee source 6
WUSS 2018 The Doctor Ordered a Prescription ... Not a Description: Driving Dynamic Data Governance Through Prescriptive Data Dictionaries That Automate Quality Control and Exception Reporting Troy Martin Hughes source 20
WUSS 2018 Validating User-Submitted Data Files with Base SAS Michael A. Raithel source 16
PHUSE US 2018 "What's Rules Got to Do with It?" Helena Sviglin source
presentation source		 2
PHUSE US 2018 Best Practices for Explaining Validation Results in the Study Data Reviewer's Guide Kristin Kelly source
presentation source		 6
PHUSE US 2018 Commissioning a MDR System: Next-generation of Standards implementation Abhinav Jain source
presentation source		 6
PHUSE US 2018 Confusing Data Validation Rules Explained Michael Beers source
presentation source		 5
PHUSE US 2018 How to Prepare High Quality Metadata for Submission [presentation] Varun Debbeti source 31
PHUSE US 2018 The Changing Landscape of Data Quality at CDER: an Overview of the Core DataFitness Assessment Crystal Allard,
Michelle Dieter,
Lilliam Rosario		 source
presentation source		 8
PHUSE US 2018 Want Submission-Ready Datasets Package from the Get-Go? Kishore Pothuri,
Bhavin Busa		 source 7
PharmaSUG 2018 A time saving approach to track data issues Aishhwaryapriya Elamathivadivambigai source 8
PharmaSUG 2018 Accredited, Bona fide, Certified, Diploma'ed, and Edumacated: The ABCDEs of Automating the Validation and Monitoring of Professional Requirements for Employees and Job Candidates Through Dynamic, Data-Driven SAS Reporting Troy Martin Hughes source 20
PharmaSUG 2018 An Efficient Tool for Clinical Data Check Chao Su source 8
PharmaSUG 2018 Best Practice for Explaining Validation Results in the Study Data Reviewer's Guide Kristin Kelly source 6
PharmaSUG 2018 Confusing Data Validation Rules Explained Michael Beers source 6
PharmaSUG 2018 Diagnostics of technical errors in define.xml file Sergiy Sirichenko,
Max Kanevsky		 source 9
PharmaSUG 2018 Electronic Data Submission and Utilization in Japan Yuki Ando source 25
PharmaSUG 2018 Introducing Dynamic Data Quality Control Methods: Abstracting Data Validation through External Data Troy Martin Hughes source 20
PharmaSUG 2018 Stay ahead of the game: Know the SDTM compliance check reject messages before creating your SDTM datasets Lixiang Larry Liu,
Yuqin Li		 source 6
PharmaSUG 2018 Want Submission-Ready Datasets Package from the Get-Go? Kishore Pothuri,
Bhavin Busa		 source 8
PharmaSUG 2018 Why organizations need MDR systems to manage metadata? Abhinav Jain source 7
SGF 2018 Accelerate your End-to-End Enterprise Decisions with SAS Viya David R. Duling,
Steve Sparano		 source 12
SGF 2018 Identifying Behaviors and Irregularities in Public Procurement in the Brazilian Federal Government Andre Castro source 15
SGF 2018 Improved Campaigning at Africa's Largest Pay TV Service Provider with SAS Marketing Optimization Jean De Villiers source 16
SGF 2018 Introducing SAS Decision Manager 5.1 with Business Rules for SAS Viya Chris Upton source 10
SGF 2018 Using SAS Visual Analytics to Solve Problems with Reporting Based in Microsoft Excel Amanda Pasch source 7
SGF 2018 Validating User-Submitted Data Files with Base SAS Michael A. Raithel source 16
SESUG 2017 Statistician's secret weapon: 20 ways of detecting raw data issues Lixiang Larry Liu source 8
SCSUG 2017 Use Machine Learning to Discover Your Rules David R. Duling source 10
PHUSE EU 2017 Constrain your Terminology - Use Integrity Constraints to Validate your Data Sven Greiner source
presentation source		 9
PHUSE EU 2017 Formedix On: A Powerful Platform to Accelerate Clinical Trials Kevin Burges source
presentation source		 2
PHUSE EU 2017 How a Metadata Repository can Facilitate Automated Data Collection Processes Judith Goud source
presentation source		 8
WUSS 2017 Data Exploration for Sweet Spots by Using Heat Maps in SAS Alec Zhixiao Lin source 7
WUSS 2017 Next Best Offer Analytics using SAS Robin E. Way,
William Eisenhauer		 source 12
PharmaSUG 2017 ADaM Compliance - Validating your Specifications Trevor Mankus,
Kent Letourneau		 source 9
PharmaSUG 2017 Common Programming Errors in CDISC data Sergiy Sirichenko source 9
PharmaSUG 2017 Data Integrity: One step before SDTM Pavan Kathula,
Sonal Torawane		 source 9
PharmaSUG 2017 Good Data Validation Practice Sergiy Sirichenko,
Max Kanevsky		 source 10
PharmaSUG 2017 How will FDA Reject non-CDISC submission? Kevin Lee source 6
PharmaSUG 2017 Real Time Clinical Trial Oversight with SAS Ashok Gunuganti source 7
PharmaSUG 2017 Sponsor Oversight of CROs Data Management and Biostatistical Abilities Lois Lynn source 7
PharmaSUG 2017 Statistician's secret weapon: 20 ways of detecting raw data issues Lixiang Larry Liu source 8
PharmaSUG 2017 The Do-s/Don-ts, An SDTM Validation Perspective. The should/shouldn-t when explaining issues in the Study Data Reviewers Guide Thomas Guinter source 8
PharmaSUG 2017 Usage of Pinnacle 21 Community Toolset 2.x.x for Clinical Programmers Sergiy Sirichenko,
Michael DiGiantomasso		 source 23
SGF 2017 A Hadoop Journey along the SAS Road Sumit Sukhwani,
Krutharth Peravalli,
Amit Gautam		 source 8
SGF 2017 Power to the People! Web Service Scoring for the Masses Prasenjit Sen,
Chris Upton		 source 13
SGF 2017 Use Machine Learning to Discover Your Rules David R. Duling source 10
SGF 2017 Using Analytics to Prevent Fraud Gives HDI Fast and Real-Time Approval for Claims Rayani Melega source 9
SGF 2017 Using Segmentation to Build More Powerful Models with SAS Visual Analytics Darius S. Baer,
Sam Edgemon		 source 18
SESUG 2016 Fuzzy Matching: Where Is It Appropriate and How Is It Done? SAS Can Help. Stephen B. Sloan,
Dan Hoicowitz		 source 10
PHUSE EU 2016 Efficiency and Delivery Driven by Metadata [presentation] Magnus Mengelbier source 15
PHUSE EU 2016 Japanese Electronic Submission in CDISC Formats Takashi Kitahara source
presentation source		 8
PHUSE EU 2016 What is high quality study metadata? Sergiy Sirichenko,
Max Kanevsky		 source
presentation source		 9
WUSS 2016 Are you ready for Dec 17th, 2016 - CDISC compliant data submission? Kevin Lee source 6
WUSS 2016 Ushering SAS Emergency Medicine into the 21st Century: Toward Exception Handling Objectives, Actions, Outcomes, and Comms Troy Martin Hughes source 23
PharmaSUG 2016 Building Efficiency and Quality in SDTM Development Cycle Kishore Pothuri,
Bhavin Busa		 source 6
PharmaSUG 2016 Usage of Pinnacle 21 Community Toolset 2.1.1 for Clinical Programmers Sergiy Sirichenko,
Michael DiGiantomasso,
Travis Collopy		 source 19
SGF 2016 Architecting Data Management: Seven Principles Using SAS, DataFlux, and SQL Bob Janka source 20
SGF 2016 Enhanced Segmentation Using SAS Visual Analytics and SAS Visual Statistics Darius S. Baer,
Suneel Grover		 source 19
SGF 2016 Enterprise Data Governance across SAS and Beyond Jeff Stander source 20
SGF 2016 Fuzzy Matching: Where Is It Appropriate and How Is It Done? SAS Can Help. Stephen B. Sloan,
Daniel Hoicowitz		 source 10
SGF 2016 Mass-Scale, Automated Machine Learning and Model Deployment Using SAS Factory Miner and SAS Decision Manager Jonathan Wexler,
Steve Sparano		 source 19
SGF 2016 Prescriptive Analytics - Providing the Instruction to Do What's Right Tho H. Nguyen,
Fiona McNeill		 source
presentation		 11
SGF 2016 SAS Spontaneous Combustion: Securing Software Portability through Self-Extracting Code Troy Martin Hughes source 11
SGF 2016 Streaming Decisions: How SAS Puts Streaming Data to Work Fiona McNeill,
David R. Duling,
Steve Sparano		 source
zip		 15
SGF 2016 Taming the Rule Charlotte Crain,
Chris Upton		 source 13
SGF 2016 The Journey Towards an Omnichannel Reality Jørn Tronstad source 10
SGF 2016 The Optimization of the Optimal Customer Pamela Dixon source 9
SGF 2016 When Reliable Programs Fail: Designing for Timely, Efficient, Push-Button Recovery Troy Martin Hughes source 14
MWSUG 2015 SAS Spontaneous Combustion: Securing Software Portability through Self-Extracting Code Troy Martin Hughes 9
MWSUG 2015 Ushering SAS Emergency Medicine into the 21st Century: Toward Exception Handling Objectives, Actions, Outcomes, and Comms Troy Martin Hughes 23
MWSUG 2015 When Reliable Programs Fail: Designing for Timely, Efficient, Push-Button Recovery Troy Martin Hughes 12
PHUSE EU 2015 Analysing the Role of a Lead Programmer Ester Schoeman source
presentation source		 9
PHUSE EU 2015 CONNECT and CREATE - Connect Standards and Enable Protocol Authoring Abi Velurethu,
Susanne Pangritz		 source
presentation source		 16
PHUSE EU 2015 Data-centric System Development Life Cycle for Automated Clinical Data Development Systems Kevin Lee source
presentation source		 5
PHUSE EU 2015 Managing Data Standards Libraries Compliance (to CDISC) Deborah Paletta source
presentation source		 7
SESUG 2015 How to Build Study Quality Surveillance for a Clinical Study? Angela Teng source 3
WUSS 2015 Architecting Data Management: 7 Principles using SAS, DataFlux and SQL Bob Janka source 17
WUSS 2015 Building and Customizing a CDISC Compliance and Data Quality Application Wayne (Weizhen) Zhong,
Accretion Softworks		 source 5
WUSS 2015 SAS Spontaneous Combustion: Securing Software Portability through Self-Extracting Code Troy Martin Hughes source 9
WUSS 2015 Why Aren't Exception Handling Routines Routine? Toward Reliably Robust Code through Increased Quality Standards in Base SAS Troy Martin Hughes source 15
PharmaSUG CN 2015 SDTM Electronic Submissions to FDA: Guidelines and Best Practices Christina Chang,
Kyle Chang		 6
PharmaSUG 2015 A Web-Based Approach to Fighting Analysis Chaos Gordon Fancher,
Rajeev Karanam,
Shawn Hopkins		 source 7
PharmaSUG 2015 Begin with the End in Mind - Using FDA Guidance Documents as Guideposts when Planning, Delivering and Archiving Clinical Trials David C. Izard source 12
PharmaSUG 2015 Getting Rid of Bloated Data in FDA Submissions Ben E. Bocchicchio,
Frank L. Roediger		 source 8
PharmaSUG 2015 Japanese submission/approval processes from programming perspective Ryan Hara source 7
PharmaSUG 2015 Let SAS "Modify" Your Excel File Nelson Lee source 5
PharmaSUG 2015 The Best Practices of CDISC ADaM Validation Checks: Past, Present, and Future Shelley Dunn,
Ed Lombardi		 source 9
PharmaSUG 2015 The Most Common Issues in Submission Data Sergiy Sirichenko,
Max Kanevsky		 source 9
PharmaSUG 2015 Usage of OpenCDISC Community Toolset 2.0 for Clinical Programmers Sergiy Sirichenko,
Michael DiGiantomasso,
Travis Collopy		 source 19
PharmaSUG 2015 When Reliable Programs Fail: Designing for Timely, Efficient, Push-Button Recovery Troy Martin Hughes source 12
SGF 2015 Benefits from the Conversion of Medicaid Encounter Data Reporting System to SAS Enterprise Guide [presentation] Eric Sather source 4
SGF 2015 Dynamic Decision-Making Web Services Using SAS Stored Processes and SAS Business Rules Manager Lori Small,
Chris Upton		 source 16
SGF 2015 Integrating Data and Business Rules with a Control Data Set in SAS Edmond Cheng source 11
SGF 2015 Make Better Decisions with Optimization David R. Duling source
zip		 10
SGF 2015 Master Data and Command Results: Combine Master Data Management with SAS Analytics for Improved Insights Ron Agresta source 6
SGF 2015 Next Generation: Using SAS Decision Manager to Modernize and Improve Your Operational Decisions Steve Sparano source 20
SGF 2015 The Business of Campaign Response Tracking Pamela Dixon source 8
SGF 2015 Using SAS to Deliver Web Content Personalization Using Cloud-Based Clickstream Data and On-premises Customer Data Mahesh Subramanian,
Suneel Grover		 source 24
SGF 2015 Why Aren't Exception Handling Routines Routine? Toward Reliably Robust Code through Increased Quality Standards in Base SAS Troy Martin Hughes source 17
SGF 2015 Will You Smell Smoke When Your Data Is on Fire? The SAS Smoke Detector: A Scalable Quality Control Dashboard for Transactional and Persistent Data Troy Martin Hughes source 25
PHUSE EU 2014 Monitoring Clinical Trials with a SAS Risk-Based Approach Laurie Rose source
presentation source		 9
PHUSE EU 2014 Standards Driven Innovation [presentation] Frederik Malfait source 36
MWSUG 2014 Secret Sauce for Reporting Health Care Data Using SAS and SQL Server Business Intelligence Bradley Blackmore,
Gowri Madhavan		 13
MWSUG 2014 Why Aren't Exception Handling Routines Routine? Toward Reliably Robust Code through Increased Quality Standards in Base SAS Troy Martin Hughes 14
MWSUG 2014 Will You Smell Smoke When Your Data Are on Fire? The SAS Smoke Detector: Installing a Scalable Quality Control Dashboard for Transactional and Persistent Data Troy Martin Hughes 25
PharmaSUG 2014 SDTM, ADaM and define.xml with OpenCDISC Angela S. Ringelberg,
Tracy Sherman		 source 21
PharmaSUG 2014 Self-fulfilling Macros Generating Macro Calls and Enabling Automation from a Specification Y. Christina Song source 6
SGF 2014 Big Digital Data, Analytic Visualization, and the Opportunity of Digital Intelligence Suneel Grover source 17
SGF 2014 Data Visualization within Management at Euramax Peter Wijers source 6
SGF 2014 Introduction to SAS Decision Management Steve Sparano,
Charlotte Crain,
David R. Duling		 source 18
SGF 2014 Using SAS MDM deployment in Brazil Ielton de Melo Gonçalves source 5
SESUG 2013 Data Entry in SAS Strategy Management A New, Better User (and Manager) Experience David Shubert source 20
MWSUG 2013 Applying Customer Analytics to Customer Decisions Wanda Shive 5
PharmaSUG 2013 DataSetBuilder - An Application for Creating Edit Check Test Cases within SAS Data Sets by Non-Programmers Richard Addy source 9
PharmaSUG 2013 OpenCDISC: Beyond Point and Click Frank C. DiIorio source 12
PharmaSUG 2013 SDTM, ADaM and define.xml with OpenCDISC Angela S. Ringelberg,
Tracy Sherman		 source 16
SGF 2013 A Metadata-Driven Programming Technique Using SAS Xiyun Wang source 14
SGF 2013 Data Entry in SAS Strategy Management A New, Better User (and Manager) Experience David Shubert source 20
SGF 2013 Extraction, Transformation, and Loading (ETL) for Outcome Measures of Workers? Compensation Benefits Mike Maier source 10
SGF 2013 How to Do a Successful MDM Project in SAP Using SAS MDM Advanced Casper Pedersen source 6
SGF 2013 Next-Generation Detection Engine for Fraud and Compliance Ryan Schmiedl source 6
SGF 2013 SAS Enterprise Business Intelligence Deployment Projects in the Federal Sector: Best Practices Jennifer Parks source 13
SGF 2013 Sobeys and SAS - How Do You Talk to Your Customer? Ashok Setty,
Wanda Shive		 source 5
SGF 2013 Time Is Precious, So Are Your Models: SAS Provides Solutions to Streamline Deployment Jonathan Wexler,
Wayne Thompson		 source 17
SGF 2013 What's New in SAS Data Management Malcolm Alexander,
Nancy A. Rausch		 source 17
NESUG 2012 Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros Airaha Chelvakkanthan Manickam 13
NESUG 2012 Loading Metadata to the IRS Compliance Data Warehouse (CDW) Website: From Spreadsheet to Database Using SAS Macros and PROC SQL Robin Rappaport,
Jeffrey S. Butler		 7
NESUG 2012 Practical Application of SAS Capabilities for Pharma Goaling and Performance Review Ramya Purushothaman 15
PHUSE EU 2012 CDISC Advisory Board Validation Project - Best Practices for CDISC Validation Rules Lauren L. Shinaberry source
presentation source		 4
PHUSE EU 2012 One Approach to a Metadata and Data Standards Repository Bill J. Gibson source
poster source		 4
PHUSE EU 2012 Optimizing Data Validation Andrew Newbigging source
presentation source		 10
SESUG 2012 SAS Enterprise Business Intelligence (EBI) Deployment Projects in the Federal Sector: Best Practices Jennifer Parks,
Falls Church		 source 12
PharmaSUG CN 2012 Rising to Excellence - How a China CRO Achieves International Standards [presentation] Helen Yin,
Minzhi Liu		 27
PharmaSUG 2012 Interesting Technical Mini-Bytes of Base SAS - From DATA Step to Macros Airaha Chelvakkanthan Manickam source 13
SGF 2012 CSI: Customer Segmentation Intelligence for Increasing Profits Darius S. Baer source 13
SGF 2012 Custom Rollup: When the Cubes Default Behavior Doesnt Do the Right Job! Paresh M. Patel source 11
SGF 2012 Easily Add Significance Testing to your Market Basket Analysis in SAS Enterprise Miner Michael Faron,
Goutam Chakraborty		 source 6
SGF 2012 Improving Retail Decisions with Customer Analytics: Leveraging Actionable Customer Insights to Build Sales and Profits Wanda Shive,
Dwight J. Mouton		 source 7
SGF 2012 Interesting Technical Mini-Bytes of Base SASFrom DATA Steps to Macros Airaha Chelvakkanthan Manickam source 13
SGF 2012 Practical Application of SAS Capabilities for Pharma Goaling and Performance Review Ramya Purushothaman source 16
SGF 2012 Revenue Assurance: Using SAS to Identify Revenue Leakages Ahmed Darwish,
Sunil Goklani		 source 9
SGF 2012 Simple Version Control of SAS Programs and SAS Data Sets Magnus Mengelbier source 11
SGF 2012 The Systems Development Life Cycle (SDLC) as a Standard: Beyond the Documentation Dianne Louise Rhodes source 5
SGF 2012 What's New in SAS Data Management Nancy A. Rausch,
Michael Ames,
Wilbram Hazejager		 source 13
SESUG 2011 Creating Stored Processes with Dynamic, Cascading Prompts Harry Droogendyk source 16
SESUG 2011 Loading Metadata to the IRS Research Compliance Data Warehouse (CDW) Website: From Excel Spreadsheet to SQL Server Relational Database Using SAS Macro and PROC SQL Robin Rappaport,
Jeffrey S. Butler		 source 7
PHUSE EU 2011 A simple interface for defining, programming and managing SAS edit checks Virginie Freytag,
Michel Toussaint		 source
poster source		 7
PHUSE EU 2011 An Animated Guide: A program to read information in SAS headers and produce reports for programming Russell M. Lavery source
poster source		 19
PHUSE EU 2011 Queries management: Interfacing SAS with in-house EDC application Virginie Freytag,
Michel Toussaint		 source
poster source		 5
PHUSE EU 2011 Study Composer: a CRF design tool enabling the re-use of CDISC define.xml metadata Philippe Verplancke source
presentation source		 5
PharmaSUG 2011 Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains Janet E. Stuelpner,
Jack Shostak		 source 12
PharmaSUG 2011 Data Edit-checks Integration using ODS Tagset Niraj J. Pandya,
Vinodh Paida		 source 6
SGF 2011 A SAS Macro to Validate Business Rule for Phasing Derivation in a Clinical Data Repository Ellen Xiao source 6
SGF 2011 Confessions of a Clinical Programmer: Dragging and Dropping Means Never Having to Say You're Sorry When Creating SDTM Domains Janet E. Stuelpner,
Jack Shostak		 source 12
SGF 2011 How TV 2 Improves Data Quality and Facilitates a Unified Customer View for Optimizing the Customer Experience Svein O. Gundhus,
Terje Vatle		 source 12
SGF 2011 Increasing Efficiency in Optimization Robbie Reynolds,
Angela Williams		 source 5
SGF 2011 Innovations in Data Management - Introduction to Data Management Platform Wilbram Hazejager,
Pat M. Herbert		 source 8
SGF 2011 Master Data Management, the Third Leg of the Data Management Stool: a.k.a. the DataFlux qMDM Solution Pat M. Herbert,
Wilbram Hazejager		 source 9
SGF 2011 Stacking the Deck: Dynamically Filtering Prompt Values for Stored Processes Susan Trelstad,
Kyle Koenig,
Alesia Pehl		 source 9
NESUG 2010 An Animated guide: Suggestions for coding standards Russell M. Lavery 24
WUSS 2010 Creating a Patient Profile using CDISC SDTM Marc Desgrousilliers source 5
WUSS 2010 Normalized Editchecks Automated Tracking (N.E.A.T.) Frank Fan source 11
PHUSE EU 2010 An Animated Guide: Coding Standards for SAS Production Programs Russell M. Lavery source 24
PHUSE EU 2010 CDISC integration in a clinical data management system Peter Van Reusel source
presentation source		 13
PHUSE EU 2010 Defining "Compliance" for Analysis Data Chris Decker,
Randall Austin		 source
presentation source		 7
PHUSE EU 2010 Study conduct in a global integrated SAS environment Martin Probach source
presentation source		 3
PharmaSUG 2010 Online Query Management System: An Innovative SAS/IntrNet Solution for Clinical Data Management Romain Miralles 12
PharmaSUG 2010 Quality in a World of "Standards" with Differences! Sandra VanPelt Nguyen 9
SGF 2010 dATa qWaliti 4 Analytics David Barkaway,
Gerhard Svolba		 source 12
SGF 2010 Dealing with Lab Data: Stacking the Deck in Your Favor Jennifer K. Fulton source 9
SGF 2010 Detecting Claim Fraud and Improving Product Quality: Case Studies in Reducing Warranty Costs David Froning source 8
SGF 2010 Tabular Reporting Data Standard Frederick A. Cieri source 9
SGF 2010 The Power of User-Defined SAS Code in SAS Data Integration Studio Anders Holte source 12
SGF 2010 Utilizing SAS Marketing Optimization as a Forecasting Tool Dwight J. Mouton,
Robbie Reynolds,
Angela Williams		 source 8
PHUSE EU 2009 Accelerate Clinical Development through Management of Data Quality [presentation] David Smith source 30
PHUSE EU 2009 Crossing the Chasm: Simplifying Data Management with Perl and Metadata Stephen Baker source
presentation source		 9
PHUSE EU 2009 Database/Biostatistics Audits - from the Auditor's Perspective Barry Ryan source
presentation source		 7
PHUSE EU 2009 Implementation of CDISC Standards at Nycomed [presentation] Berthold Traub source 31
PHUSE EU 2009 Metadata and Standard Programs Marianne Carames,
Martin Lindhard		 source
presentation source		 10
PHUSE EU 2009 This study is essentially just like that other one Louise Mazzeo source 5
PNWSUG 2009 Parameter-Driven Data Validation and Transformation Or The Marriage of Microsoft Excel and SAS Macro Variables to Solve ETL Problems Hugh Shinn,
Wanda Hopkins		 17
NESUG 2009 Using HASH to find a sum over a transactional path Richard A. DeVenezia 5
SGF 2009 Backpacking Your Way through CDISC: A Budget-Minded Guide to Basic Concepts and Implementation Rachel Brown,
Jennifer K. Fulton		 source 7
SGF 2009 Distribution Interruption Performance Reporting: A Complete Solution Chris van der Westhuizen source 10
SGF 2009 The Interactive Data Warehouse: Introducing Transactional Data Marts and "Smart Applications" to Interact with Data Warehouse Data Stein Arve Finnestad,
Gisle Karlsen,
Rune Lekve,
Pål Navestad,
Terje Stromstad,
Odd Jarle Tednes		 source 8
SGF 2009 Using SAS to Build the Managed Care Data Warehouse at Community Care Behavioral Health Organization Mary Doyle,
Qingfeng Liang,
Gretchen Ciocco,
Michele Mesiano,
Shouqiang Wang		 source 8
SCSUG 2008 Optimizing Marketing Campaign ROI through Process Automation Tariq S. Jaffery,
Shirley Liu,
Rick Vela		 5
SESUG 2008 Parameter-Driven Data Validation and Transformation Or The Marriage of Microsoft Excel and SAS Macro Variables to Solve ETL Problems Hugh Shinn,
Wanda Hopkins		 source 17
PHUSE EU 2008 Data Standardisation, Clinical Data Warehouse and SAS Standard Programs Jean-Marc Ferran,
Mikkel Traun		 source 8
PHUSE EU 2008 Improving the Quality of Data Ester Schoeman source 7
NESUG 2008 An Approach to CDISC SDTM Implementation for Clinical Trials Data William Chen,
Margaret M. Coughlin		 5
NESUG 2008 Clinical-Data Acceptance Testing Procedure Sunil Kumar Gupta 15
NESUG 2008 Extending the Power of SAS with Java Joseph Belice,
Kevin C. Harper,
Steven Schwartz		 20
PharmaSUG 2008 Clinical-Data Acceptance Testing Procedure Sunil Kumar Gupta 15
PharmaSUG 2008 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 14
SGF 2008 Clinical-Data Acceptance Testing Procedure Sunil Kumar Gupta source 15
SGF 2008 Implementing a Customer Retention, Cross-Sell, Up-Sell, and Payment Risk Solution Using SAS Telecommunications Intelligence Solutions for Orange Dominicana Carmelina Collado,
Daniel Demonchy,
Marcos Arancibia,
Al Cordoba		 source 9
SGF 2008 SAS for Real-Time Applications Paul Kent,
Bryan Wolfe,
Daniel Jahn,
James Carroll,
Dan Dotson		 source 17
SGF 2008 SAS Scripting of a Production Database into an Open Test Environment Sigurd W. Hermansen,
Himanshi Singh,
Laura Hrycyk		 source 5
SGF 2008 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 source 14
SESUG 2007 Data Quality Management, Data Cleansing, and Discrepancy Reporting Jenine Milum source 9
PHUSE EU 2007 DQC checker Ryan Finch source 7
PHUSE EU 2007 WEB-TRIAGE: Application for patient registration in ph I studies Angelo Tinazzi,
Lucio Ferraresi		 source 10
PharmaSUG 2007 Leveraging Base SAS for Constructing a Low-Cost, Data Clarification Request Generation and Tracking System Independent of a Clinical Data Management System David M. Escobar,
Barbara Mathewson,
George Strang		 7
PharmaSUG 2007 Programming Tips and Examples for Your Toolkit, III John Morrill 12
PharmaSUG 2007 Statistical Outputs as Groups of Related Data: Overcoming Some Common Pagination Challenges Alexandr Alexin 6
SGF 2007 Integration of webAF and Table-Driven Methodology Shelly Yiu-Morrison source 11
SGF 2007 SAS Information Map Studio and SAS Web Report Studio-A Tutorial Angela M. Miles,
Brian O. Hall		 source 21
SGF 2007 Speed It Up - Active Warehousing with SAS Data Integration: From Batch to Real-Time Eric Hunley,
Gary Mehler,
Nancy A. Rausch		 source 16
PHUSE EU 2006 Real Time: what is it and what are we doing about it? Richard H. Phillips,
Gregory S. Barnes Nelson		 source 14
PHUSE EU 2006 Standardization in Clinical Development Marianne Carames source 7
SESUG 2006 Master Data Management: What It Is and Why You Should Care John E. Bentley source 5
WUSS 2006 An Approach Finding the Right Tolerance Level for Clinical Data Acceptance Karen Walker source 5
WUSS 2006 PROC SQL: A Powerful Tool to Improve Your Data Quality Keh-Dong Shiang source 10
WUSS 2006 What's New in Data Quality? Pat M. Herbert source 6
NESUG 2006 Performance Boosters: Streamlining Report Production from Days to Hours Jim Fang,
Patrick Dunleavy,
Vinod Narayanan,
Anuj Sharma		 9
NESUG 2006 SAS Macros and the Power of Design Dalia C. Kahane 12
PharmaSUG 2006 Real Time: what is it and what are we doing about it? Richard H. Phillips,
Gregory S. Barnes Nelson		 14
PharmaSUG 2006 Transforming Business Requirements into System Solutions Yongcun Zhang 10
SUGI 2006 Modular Programming using SAS/AF and SAS SCL Kevin Graham source 8
SUGI 2006 PROC SQL: A Powerful Tool to Improve Your Data Quality Keh-Dong Shiang source 10
SUGI 2006 Real Time: What Is It? What Are We Doing about It? Richard H. Phillips,
Gregory S. Barnes Nelson		 source 14
SUGI 2006 Using External Data Dictionary Files When Building SQL Queries in Base SAS Mike D. Tangedal source 10
SUGI 2006 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 source 13
SCSUG 2005 Maintaining Inherited SAS Code Clarence W. Jackson 9
PHUSE EU 2005 Consistent Variables + Consistent Checks = Cleaner Data Greg Silva source 5
PHUSE EU 2005 Integrating SAS With Open Software in a Validated Drug Safety Environment Jeremy Fletcher source 48
PHUSE EU 2005 The European System for Monitoring Drug Safety, EudraVigilance Hans-Georg Wagner,
Olivier Simoen		 source 13
WUSS 2005 Understand, Document, and Automate Your Programs and Data Tables Anthony M. Dymond source 12
PharmaSUG 2005 An Approach Finding the Right Tolerance Level for Clinical Data Acceptance Karen Walker 6
PharmaSUG 2005 Consistent Variables + Consistent Checks = Cleaner Data Greg Silva 5
SUGI 2005 Data Profiling: Designing the Blueprint for Improved Data Quality Brett Dorr,
Pat M. Herbert		 source 10
SUGI 2005 Implementing Data Warehousing and Business Intelligence at McMaster University Using the SAS Intelligence Value Chain Debbie Weisensee,
Eric Matthews,
Anne McInnis		 source 10
SUGI 2005 Taming Transformation: A Strategy for Metadata within the Warehouse Katherine Prairie source 9
NESUG 2004 Clinical Trial Data Validation: Using PROC SQL Effectively Balakrishna Dandamudi 20
SCSUG 2004 Data Quality and Base SAS Clarence W. Jackson 6
SCSUG 2004 SAS Optimization: What's New and What's Next Edward P. Hughes 25
SESUG 2004 "Methods for Minimizing Errors in Address Data" Milorad Stojanovic source 6
SESUG 2004 A Hiker's Guide to Web Development Steve James source 10
SESUG 2004 Building Efficient State Transition Diagrams from Charges, Collection and Call Detail Transactional Feeds Brett C. Peppe source 19
SESUG 2004 Exceptional Exception Reports Gary M. McQuown source 10
WUSS 2004 SAS Data Quality - A Technology Overview Eric Hunley source 13
MWSUG 2004 Exceptional Exception Reports Gary M. McQuown 10
PharmaSUG 2004 SASUnit: Automated Testing for SAS Gregory S. Barnes Nelson 15
PharmaSUG 2004 The Implementation of Automatic Obvious Data Modifications (ODMs) on Late Phase Trials Using SAS PROC SQL Kathleen Kushner,
Philip Pellicone		 6
SUGI 2004 A Hiker's Guide to Web Development Steve James source 13
SUGI 2004 Architectural Views on Building an Actuarial System with SAS/Warehouse Administrator Dominic Roy,
Alain Baillargeon		 source 10
SUGI 2004 Automated Testing and Real-time Event Management: An Enterprise Notification System Gregory S. Barnes Nelson,
Danny Grasse,
Jeff Wright		 source 13
SUGI 2004 Data Quality Management: The Most Critical Initiative You Can Implement Jonathan G. Geiger source 15
SUGI 2004 Data Quality Solution - A Technical Overview Eric Hunley source 14
SUGI 2004 Designing Information Maps for Ad Hoc Reporting Diane Hatcher source 11
SUGI 2004 Developing Data Marts and Web-Enabled OLAP for Actuarial and Underwriting Analysis Michael Krumenaker,
George Bukhbinder		 source 8
SUGI 2004 From Buzzwords to Business Value Liz Roche source 19
SUGI 2004 Unusual Uses of SAS Steven J. First source 8
SCSUG 2003 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 7
SCSUG 2003 Writing Your SAS Program Right Clarence W. Jackson 11
SESUG 2003 A Hiker's Guide to Web Development Steve James source 12
SESUG 2003 Automated Testing and Real-time Event Management: An Enterprise Notification System Gregory S. Barnes Nelson,
Danny Grasse,
Deborah Pine		 source 6
SESUG 2003 Data-driven Validation Rules: Custom Data Validation Without Custom Programming Don Hopkins source 8
NESUG 2003 A Hiker's Guide to Web Development Steve James 12
NESUG 2003 Building an Actuarial System with SAS/Warehouse Administrator Dominic Roy 5
NESUG 2003 How to Add a Format Viewer to the SAS Explorer Randy D. Herbison 10
NESUG 2003 User Implementation and Revision of Business Rules Without Hard Coding: Macro-Generated SAS Code Michael Krumenaker,
Jit Bhattacharya		 11
NESUG 2003 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 7
SEUGI 2003 Analytical CRM at Swisscom Fixnet - The data warehouse concept, mode development with Enterprise Miner and implementation [presentation] Miltiadis Sarakinos source 22
SEUGI 2003 Making the most of Business Intelligence with SAS Data Quality [presentation] Paul Padley source 37
SEUGI 2003 Metadata Strategies: your guide through the data jungle [presentation] Achim Granzen source 35
SEUGI 2003 Next Generation reporting with SAS 9.1: Reporting for the masses [presentation] Ingrid Hertel source 24
SEUGI 2003 SAS Demand Intelligence [presentation] Udo Sglavo source 27
SEUGI 2003 SAS Interaction Management [presentation] Jens Echtermeyer source 22
SEUGI 2003 Welcome to "Adminstration and Metadata" stream [presentation] Achim Granzen source 36
VIEWS 2003 Design Considerations when Developing Applications using SAS Vijay Rajandram presentation 4
SUGI 2003 Better Decisions Through Better Data Tony Fisher,
George Marinos		 source 6
SUGI 2003 Flip the Bow Tie: Pushing Business Intelligence to Operational Applications Larry D. Bramblett source 6
SUGI 2003 The Horror of Bad Data Quality Henri Theuwissen,
Nancy Croonen		 source 7
SUGI 2003 Web-Enable Your SAS Applications Teresia L. Arthur,
Mary Jafri		 source
MWSUG 2002 Data Quality - The Fuel that Drives the Business Engine Tony Fisher 5
NESUG 2002 Get With the Validation Program - Successful Steps to Edit Check Failures Michael Rea 2
NESUG 2002 Improving Upon Success: An Integrated Healthcare Business Solution Craig Dickstein,
Christopher Yindra,
Alan Dickson		 10
SESUG 2002 Data Quality - The Fuel that Drives the Business Engine Tony Fisher source 5
WUSS 2002 XML: What is it, and Why Should SAS Users Care? Miriam Cisternas,
Ricardo A. Cisternas		 source 7
SEUGI 2002 Data Mining In A Zero Latency Enterprise Environment [presentation] Luca Selvatici source 24
SEUGI 2002 Data Warehousing with SAS [presentation] Wilbram Hazejager source 32
SEUGI 2002 Introduction to Customer Intelligence [presentation] Alan Gormley source 26
SEUGI 2002 Proper Architecture Considerations For Data Warehouse Implementation [presentation] Mark Nilan source 29
SEUGI 2002 Proving the value of IT on the bottom line [presentation] Arne Lofgren source 24
PharmaSUG 2002 (Web) Software Development: Best Practices for Developing Enterprise Applications Gregory S. Barnes Nelson 8
PharmaSUG 2002 Using SAS to get more out of Oracle Clinical Jim Johnson 10
SUGI 2002 (Web) Software Development: Best Practices for Developing Enterprise Applications Gregory S. Barnes Nelson,
Danny Grasse		 source 8
SUGI 2002 A Scorecard Approach to Improving Data Quality Phil Nousak,
Robert W. Phelps		 source 9
SUGI 2002 Data Quality - The Fuel that Drives the Business Engine Tony Fisher source 5
SUGI 2002 Data Warehousing - What's It All About? Learning to Walk in Seven League Boots Steve Morton source 7
SUGI 2002 Data Warehousing in the Modern World: A Case Study Revisited Mary K. Tucker source 8
SUGI 2002 IDW - The Next Generation Data Warehouse Larry D. Bramblett source 5
SUGI 2002 Offer Optimization - Optimizing Cross-sell and Up-sell Opportunities in Banking Andrew G. Storey,
Marc-David Cohen		 source 7
SUGI 2002 The Knowledge Warehouse: The Next Step Beyond the Data Warehouse Anthony M. Dymond source 8
NESUG 2001 Community Right-to-Know: Using the Web to Publish Toxic Chemical Release Information at the U.S. EPA Myles E. Powers 2
VIEWS 2001 Managing Supplier Relationships In The E-World: The Need For Information [presentation] Jennifer Major,
Trevor Payne		 59
SESUG 2001 A Scorecard Approach to Improving Data Quality Robert W. Phelps,
Phil Nousak		 source 9
SESUG 2001 Knowledge Management Using an Expert System Written in SAS Anthony M. Dymond source 7
SESUG 2001 Supplier Management with SAS Supply Chain Solutions Edward P. Hughes source 4
SESUG 2001 Web-Intelligence: A Primer Donald J. Henderson,
Ralph Mittl		 source 10
SCSUG 2001 A Scorecard Approach to Improving Data Quality Robert W. Phelps,
Phil Nousak		 9
SCSUG 2001 Knowledge Management Using an Exper System Written in SAS Anthony M. Dymond 7
SCSUG 2001 Supplier Management with SAS Supply Chain Solutions Edward P. Hughes 4
SCSUG 2001 Web-Intelligence: A Primer Donald J. Henderson,
Ralph Mittl		 10
SEUGI 2001 Data Mining In a Zero Latency Enterprise [presentation] Philip Bosinoff source 36
SEUGI 2001 e-Intelligence and e-CRM in a competitive new economy [presentation] Dorte Ransby source 27
SEUGI 2001 Integrated Customer Call Information [presentation] John Nysse source 45
SEUGI 2001 SAS Information Delivery Portal - Delivering Information to the Masses! [presentation] Don Hatcher source 36
PharmaSUG 2001 Saving Trees: Managing the Edit Check Process Electronically Timothy D. Kelly 4
SUGI 2001 A Case Study in Data Warehousing and Data Mining Using the SAS System Mary K. Tucker source 3
SUGI 2001 Versioning an Existing Data Warehouse K. Mistry,
John Finianos		 source 4
NESUG 2000 Saving Time with Variable Labels Brian Conley 2
NESUG 2000 Saving Trees: Managing the Edit Check Process Electronically Timothy D. Kelly 3
NESUG 2000 Unlock MDDB File Using MDDB_M Class Hsiwei Yu,
Rashmi Lal		 5
SEUGI 2000 A reporting system on the WEB [presentation] Pål Navestad source 16
SEUGI 2000 An online Business Monitoring System - Actual online information on highly automated Business Processes in a large scale SAP Environment - Case Study and Outlook [presentation] Elmar Husmann source 20
SEUGI 2000 Benefits From Merging Datawarehouses [presentation] Jurgen Wielandts,
Sophie Ceyssens		 source 18
SEUGI 2000 From Doctor Shopping to Data Warehouseing to Improve Health Outcomes [presentation] John Trabinger source 47
SEUGI 2000 SAS/IntrNet - Tips and Techniques [presentation] Matthias Boge source 52
SUGI 2000 From the Analysts to the Executive - Business Visualization and Enterprise Reporting with the SAS System Joe Costanzo,
Ben Zenick		 source 5
SUGI 2000 SAS Common Metadata and Current Industry Metadata Trends Vernee Stevens source 4
SUGI 2000 SAS' Best Kept Secret: Macro Windows for Applications Development Kay L. Alden source 4
SESUG 1999 Effective strategies for managing SAS applications development Christopher A. Roper source 7
SESUG 1999 Householding and Its Relationship to Customer-to-Customer Marketing and Data Mining Jacob Sacolick source 8
WUSS 1999 Mergers & Acquistions in a Data Warehousing Environment Demetris Papaiacovou source 3
NESUG 1999 Are We Done Yet? Tracking Your Data Management Process with SAS Software Daphne E. Ewing,
Barbara McLaughlin		 4
MWSUG 1999 Warehouse to Web Using a Powerful SAS Solution Inez Williams,
Carol Martin		 5
SEUGI 1999 Police Data Warehouse in Finland [presentation] Ari-Pekka Neuvonen source 25
SEUGI 1999 Using the Web to view your data warehouse [presentation] Frank Nauta source 29
SEUGI 1999 What's New in SAS/Warehouse Administrator Software [presentation] Scott Anderson source 37
SUGI 1999 Extending the Life of Your SAS/AF Application: Exploiting the Model-Viewer Paradigm Gregory S. Barnes Nelson source 10
SUGI 1999 HR Vision Software - A Decision Support System for Human Resource Professionals Beverly Dudley source 2
SUGI 1999 SAS RDBMS!A GUI Approach to Data Entry Using SAS/AF Software Enforced with Relational Model Integrity Constraints from ORACLE Annie S. Guo source 6
SUGI 1999 The Quality Data Warehouse - Solving Problems for the Enterprise Brad Klenz,
Donna O. Fulenwider		 source 8
WUSS 1998 National Comprehensive Cancer Network (NCCN): Integrating SAS Edit Checks into a Web-Based On-Line Data Entry System Deborah A. Testa,
Rebecca Ottesen,
Wendy Paul,
James Chen,
Eva Lepisto,
Joyce C. Niland		 source 2
PharmaSUG 1998 Designing Edit Check Subsystem in SAS/IntrNet James Sun,
Monmouth Junction		 5
SUGI 1998 Data Warehousing and the Web Jim Davis source 4
SUGI 1998 Does a Data Warehouse Deliver the Goods? Glen Payne source 3
SUGI 1998 The SAS System Powers Web Measurement Solution at US West Robert M. Romero,
Dale Hamilton		 source 5
SESUG 1997 Beyond Field Validation: Incorporating the Batch Edit Into the Total Data System John A. Quarantillo 3
SEUGI 1997 A data management system for use in the pharmaceutical and biotechnology Industries Ellen Krantz source 12
PharmaSUG 1997 Benefits of using a SAS based Electronic Data Collection Application Tracy Millander,
Ronald Fitzmartin		 2
SUGI 1997 SAS Code Generator Based on Table-Driven Methodology in a Batch Environment Arthur K. Yao source 6
SUGI 1997 Structuring Your Data Warehousing Project: Moving from the Concept to the Reality Peter R. Welbrock source 8
SUGI 1997 Successful Business Intelligence Systems: Improving Information Quality with the SAS System W. Droogendyk,
L. M. Harschnitz		 source 6
SESUG 1996 Creating and Linking Customized SCL Objects Andrew A. Norton 7
NESUG 1996 Creating and Linking Customized SCL Objects Andrew A. Norton 7
SEUGI 1996 Data Warehousing Sean Kelly source 31
SEUGI 1996 The growing need for distributed data warehouse systems due to globalisation of business Ger Scherpens,
Sander Piet		 source 12
SEUGI 1995 Applications Development Environment (ADE) Keith Collins source 13
SUGI 1995 ClinAccess: A Client/Server Approach to Clinical Trials Data Management and Regulatory Approval Martin J. Rosenberg source 7
SUGI 1994 A SAS/AF System for Entry, Validation, Analysis, and Reporting of Diverse Survey Data from Multiple Sites William A. Harris,
Charles W. Warren		 source 6
SUGI 1994 Developing Integrated Clinical Trials Systems: The ClinAccess Experience Martin J. Rosenberg source 7
WUSS 1993 An Integrated Clinical Trials System Utilizing Client Server and Graphical User Interface Technology Martin J. Rosenberg source 7
SEUGI 1993 Client/Server Architectures Tony Percy source 24
NESUG 1992 Use of a Centralized Data Dictionary in Designing an Occupational Health Information System Anne Stocum 6
NESUG 1992 Use of Code Generation in a Standard Edit Check Facility Robert Musterer 4
SUGI 1992 An Integrated Clinical Information System for Pharmaceutical Research Martin J. Rosenberg source 7
NESUG 1990 Edit-checking: A SAS Based System for Logically Editing Patient Data Records Maria K. Wills 6
SUGI 1989 ADVANCS: An Automated Data Validation and Correction System Jessica Bondy,
Dennis C. Lezotte,
Julie A. Marshall		 source 5
SUGI 1989 SIR on SSHENET: Developing a Common Student Information Database for 14 Universities and.Sharing It under CMS Robert A. Lahr source 5
SUGI 1988 Using the SAS System to Meet Business Processing Needs in a Mainframe Environment Lynn M. Huckert,
Mary G. Pulling,
George P. Riner		 source 6
SUGI 1987 An End-User System for Reporting using SAS/AF Software and SAS/FSP Software as Code Generators Nora Lynne Yamasaki source 3
SUGI 1987 Data Entry Backup System: An Application of PROC FSEDIT in SAS/FSP Software Hugh G. McCabe source 7
SUGI 1986 Computerized Clinical Data Bank Networks Bruce Guthrie,
Christine L. Wolf		 source 5
SUGI 1986 The Use of the SAS Macro Facility in the Development of a Clinical Information System Thomas R. Hoffman source 8
SUGI 1985 ACDAS - An Automated Clinical Data Analysis System Lynn T. Julian,
Donald D.M. Tong		 source 6
SUGI 1984 THECIS-The Clinical Information System Judith A. Burns,
Leon T. Hairie,
Thomas R. Hoffman		 source 6

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