| 1 |
18 months to make an Analytical CRM dream come true: results obtained by Vodafone Omnitel in B2B Churn Prevention |
Alessandro Bernorio, Paola Bauce |
Presentation |
sample, rate plan, response variable, data mining |
source |
36 |
| 2 |
A data warehouse and data exploitation solution in clinical trials |
F. Patarnello, V. Frizzo |
Presentation |
clinical trial, data warehouse, clinical data, clinical research |
source |
24 |
| 3 |
A G.I.S. tool to support local government in decision-making activities based on an Internet platform |
Chiara Zaina, Raffaele Gareri |
Presentation |
data mart |
source |
16 |
| 4 |
A SAS and Java Application for Reporting Clinical Trial Data |
Kevin Kane |
Presentation |
clinical trial, proc print, clinical data, survival analysis, where statement, output delivery system, proportional hazards assumption |
source |
31 |
| 5 |
A Sense of Perspective: How to use a Star Schema Data Warehouse to see any historical view you want |
Steve Morton |
Presentation |
star schema, surrogate key, proc sql, fact table, dimension table, proc step, create table, premium, data warehouse, natural key |
source |
45 |
| 6 |
A www psychological quest using SAS |
Bernard Pirali, Michel Lehon, Olivier Lebon, Samuel Dupont, Serge Roberfroid, Sylvie Linotte |
Presentation |
output delivery system, clinical trial, data science |
source |
21 |
| 7 |
Adding Value Through Supply Chain Intelligence |
Stephen Toms |
Presentation |
data warehouse, business intelligence, logistic distribution |
source |
16 |
| 8 |
Addressing the New Capital Accord (Basel II) with SAS |
Charles Duclos, Rik van de Weerthof |
Presentation |
sas risk, basel ii, credit risk, capital adequacy, market risk, operational risk, ead |
source |
45 |
| 9 |
Advanced Techniques in CRM |
Donna Byrne |
Presentation |
credit scoring, cross-sell, customer retention, customer satisfaction, machine learning |
source |
19 |
| 10 |
An Introduction to Intelligent Warehousing |
Paul Padley |
Presentation |
business intelligence, data warehouse, link analysis, data mining, regression analysis |
source |
13 |
| 11 |
An Introduction to ODS Markup and Tagsets |
Arthur Witherall |
Presentation |
output delivery system, libname engine, proc template, proc step, dataset, sample |
source |
27 |
| 12 |
An Introduction to SAS IT Management Solutions |
Richard Seery |
Presentation |
model validation, data cleaning, capacity planning, stage 1, stage 2, stage 3 |
source |
20 |
| 13 |
Analysing the competencies required to work in Business Intelligence |
Laurent Boubli |
Presentation |
business intelligence, sas enterprise guide, sas consultant, sas programming |
source |
16 |
| 14 |
AppDev Studio - A Roadmap |
Anton Fuchs |
Presentation |
distributed processing, service provider |
source |
39 |
| 15 |
Applying Business Intelligence to social services and social security |
Cheri Sweigard, Edward Blatt |
Presentation |
data warehouse, business intelligence, correlation |
source |
16 |
| 16 |
As easy as ABC |
Issy Aydiner |
Presentation |
customer profitability, management reporting, product profitability, correlation, excel |
source |
28 |
| 17 |
Balanced Scorecard as the core of a strategy focussed organisation - implentation for a German utility company |
Andreas Renner |
Presentation |
parallel processing |
source |
36 |
| 18 |
Balanced Scorecard at ING Bank |
Jan Lauffer |
Presentation |
dataset, sas base |
source |
27 |
| 19 |
Banking Data Warehouse-Developing Strategy in ICBC |
Chen Daobin |
Presentation |
data mart, mis, tier 1 capital, customer profitability, data governance, management reporting |
source |
19 |
| 20 |
Banking fraud detection and prevention system, based on intelligent data-driven decisions |
George Daminov |
Presentation |
|
source |
15 |
| 21 |
Banking Transactions Analysis using SAS Software |
Lioudmila Dmitrieva, Roman Volynets |
Presentation |
internal audit, interest rate, machine learning, deposit rate, proc report, data merging, where statement |
source |
31 |
| 22 |
Bankruptcy scoring using the SAS Enterprise Miner |
Michael Wetzel |
Presentation |
data mining, neural network, proc hpsplit, discriminant analysis, factor analysis, forecast horizon, credit migration |
source |
18 |
| 23 |
base SAS to SAS/IntrNet Gave Growing Pains to the Data Warehouse - the best story about successful Intranet on mainframe used of more than 15,000 users in the city of Copenhagen |
Erik Madsen, Sven Gaffron |
Presentation |
sas base, data warehouse, sas output |
source |
23 |
| 24 |
Betteremangement.com - Market Leadership Through Thought Leadership |
Steplan |
Presentation |
business intelligence, distribution channel |
source |
52 |
| 25 |
bioWORKS - Easy Calculatio of FDA consistent Bioequivalence |
Justo Lorenzo Bermejo |
Presentation |
business intelligence, data science |
source |
32 |
| 26 |
Budgeting, data analysis and management on the data warehouse of ASL 3 in Turin, Italy |
G. Gallone, V. Liguori |
Presentation |
sas base, regression analysis |
source |
18 |
| 27 |
Buidling Credit Scorecards using SAS Enterprise Miner |
John Lawrence, Martin Crossley |
Presentation |
proc hpsplit, data mining, regression analysis, logistic regression, missing value, neural network, scorecard |
source |
11 |
| 28 |
Building Java based OLAP clients using AppDev Studio |
Anton Fuchs |
Presentation |
|
source |
26 |
| 29 |
Building Strategic Advantage from a Single Customer View in Banking |
Iain Jennings |
Presentation |
proof of concept, retail banking, sas enterprise guide, data mart, data mining, statistical software, customer profitability |
source |
15 |
| 30 |
Calculating the return on investment made in Analytical CRM - does it make business sense? |
AJ Kruger |
Presentation |
interaction effect, neural network, subscriber analytics, network optimization, correlation |
source |
27 |
| 31 |
CIO Intelligence |
Andre Kingham, Richard Seery |
Presentation |
business intelligence, capacity planning |
source |
30 |
| 32 |
Client Report in CIB Bank using SAS Data warehouse |
Kristian Nemeth |
Presentation |
customer profitability, net interest income, current account, interest, product profitability |
source |
21 |
| 33 |
Closing the loop on Fraud |
Anton Hirschowitz |
Presentation |
fraud management, outlier, type i error, card fraud, credit card, sas enterprise guide, data step |
source |
27 |
| 34 |
CMG's approach to application managed services on SAS data warehouses |
Jan Willhem Sijthoff |
Presentation |
business intelligence, data warehouse, sas base |
source |
23 |
| 35 |
Computer management of Human Immunodeficiency Virus Epidemiological Cohorts |
Anne Peroz, Faroudy Boufassa |
Presentation |
clinical trial, missing value, data cleaning, output delivery system, data controls, final analysis, dataset |
source |
39 |
| 36 |
Conclusion to the Academic Initiative Stream |
Lena Ryuji, Nina Hanke |
Presentation |
business intelligence, credit risk, market risk |
source |
10 |
| 37 |
Corporate Financial & Operational Analytical and Reporting System |
Elias Soloviev, Eugene Okhovski |
Presentation |
data mart, output delivery system, analytics platform, calendar year, customer retention, time series analysis |
source |
43 |
| 38 |
Corporate Information Maturity |
Don Hatcher |
Presentation |
|
source |
22 |
| 39 |
Creating a customer event based data warehouse |
David Porter |
Presentation |
flat file, raw data, data warehouse, sas base, fact table, data cleaning, staging area |
source |
35 |
| 40 |
Creating an N-tier distrubuted system - How SAS comes to the rescue |
Gerry P. W. Van Tol |
Presentation |
macro variable, conditional do loop |
source |
13 |
| 41 |
CRM in the credit card area: the impact of business intelligence |
Michael Flaschka |
Presentation |
credit card, variance |
source |
12 |
| 42 |
Custom Bankruptcy Scoring for Account Management |
Edward Penner |
Presentation |
data mining, customer experience, macro put, data cleaning |
source |
10 |
| 43 |
Customer Intelligence: Experiences Using SAS |
Donna Byrne |
Presentation |
customer satisfaction, business intelligence, customer retention, customer lifetime value, credit risk, credit scoring, cross-sell |
source |
31 |
| 44 |
Customer Intelligence:The cornerstone of an Intelligent Strategy |
Shaun Doyle |
Presentation |
cross-sell, key performance indicator, data mart, data mining, customer profitability, profitability analysis |
source |
24 |
| 45 |
Customer management from a data warehouse - A Journey not a Destination |
Tal Shlasky |
Presentation |
data mining, quality of service, data warehouse, credit risk, customer satisfaction, predictor variable, feature selection |
source |
33 |
| 46 |
CWT's Data Warehouse Solution Reduces Travel Expenses |
Thomas Lundberg |
Presentation |
|
source |
13 |
| 47 |
Data Management and Data Analysis Solutions in Manufacturing: 10 Years Experience at Altis Semiconductor |
J. L. Grolier |
Presentation |
data cleaning, data mining, sas base, logistic distribution, sas programming, data visualization, db2 |
source |
36 |
| 48 |
Data Mining experiences in predicting TLC Churn |
Marco Richeldi |
Presentation |
data mining, proc hpsplit |
source |
20 |
| 49 |
Data Mining In A Zero Latency Enterprise Environment |
Luca Selvatici |
Presentation |
model deployment, phase ii, phase iii, phase iv, data mining, neural network, data validation rules |
source |
24 |
| 50 |
Data Storage Options for SAS Applications: SAS Intelligent Storage |
Bill J. Gibson |
Presentation |
dataset, proc sql, sas base, parallel processing, structured data, data warehouse, audit trail |
source |
47 |
| 51 |
Data Warehousing with SAS |
Wilbram Hazejager |
Presentation |
sas management console, data warehouse, business intelligence, access control, data validation rules, credit risk, data governance |
source |
32 |
| 52 |
Datamining for Lifetime Value |
Nigel Wigram |
Presentation |
data mining, data warehouse |
source |
40 |
| 53 |
Datawarehousing in the Public Sector: Database Integration in the Lombardia Region |
Marco Raffaldi |
Presentation |
|
source |
29 |
| 54 |
Demand Forecasting at Eurostar using Train Classification |
Adeline Laulanie |
Presentation |
agglomerative clustering, hierarchical clustering, macro definition, proc step, proc princomp, proc cluster, proc fastclus |
source |
11 |
| 55 |
Developing an infrastructure for the Efficient Use of SAS at the Federal Statistical Office Germany |
Heinz Stralla |
Presentation |
macro definition, dataset, sas enterprise guide, data science, data governance, time series analysis, data step |
source |
21 |
| 56 |
Do you know, how your customers use your website? You should - we do - Web analysis for Deutsche Telekom's Internet portal based on e-Intelligence, a customized SAS Solution |
Kerstin Kruger, Steffen Scheller |
Presentation |
bar chart, sas base, service provider, bootstrap |
source |
23 |
| 57 |
Drivign forward customer relationship and knowledge |
Bruno Tabourin, Serge Boulet |
Presentation |
customer profitability, profitability analysis, financial services, macro loop, sample |
source |
20 |
| 58 |
E.I.P. - Enterprise Information Portal, a powerful information system belonging to the sales force automation application family |
Alessandro Calderan, Graziano, Riccardo Burtulla, Silvio Rivolta |
Presentation |
customer satisfaction, corporate banking, proc step, credit risk, financial services, market risk, operational risk |
source |
48 |
| 59 |
Enhancing customer profitablity through Marketing Automation - the FNB Experience |
Jithendra Daya |
Presentation |
data mart, customer profitability, data cleaning, campaign response, customer experience, customer satisfaction, retail banking |
source |
25 |
| 60 |
Enterprise Customer Analytics: Dynamically Acting on Real Customer Insight |
Alex Zekulin, Bryan Foss |
Presentation |
kyc, financial services, retail banking |
source |
13 |
| 61 |
Enterprise Guide - A Gateway to SAS |
Amarpal Brar |
Presentation |
sas enterprise guide, time series analysis, proc reg, sas log, libname statement, file statement, correlation |
source |
18 |
| 62 |
European Experiences with the SAS Data Quality Solution |
Rein Mertens |
Presentation |
data cleaning, financial services, service provider, sas enterprise guide, data warehouse, sas base, odbc connection |
source |
26 |
| 63 |
Evaluating SPDS to Improve Performance of a Large Data Warehouse |
Clare Somerville, Colin J. Harris |
The New Zealand Ministry of Social Development data warehouse has been in production for over five years. During that time the number of analysts has increased to one hundred, and more data sources have been introduced. The hardware has been upgraded several times, and we're now running on a large HP UNIX box with 2 TB of disk, 12 GB of memory and 13 TB of online storage. For a number of reasons - most of them related to performance - the Oracle data replicas have been converted to SAS data sets. Though the move from Oracle to SAS greatly improved performance on the warehouse, it raised a number of issues including: how to span data sources across file systems, the use of views for security, and the ability to update and query at the same time. Scalable Performance Data Server (SPDS) was evaluated for use on the warehouse with a view to supplying the answers to these and other questions and issues, including the constant search for better performance |
proc step, dataset, proc sql, proc append, view, proc freq, sql pass-through, work library |
source |
14 |
| 64 |
Exploring Electoral Data with Enterprise Miner Using Self-Organizing Maps and Measures of Spatial Autocorrelation |
Anabela Martins, Fernando Lucas Bacao, Sandra Catarino |
Presentation |
data mining |
source |
12 |
| 65 |
Faster Return on Investment using Solution Blueprints from SAS and Intel |
Jim Watts, Mark Pallone |
Presentation |
|
source |
23 |
| 66 |
Financial Risk Management within the Generali Group: a structured approach |
Paolo Pirona |
Presentation |
reference data, sas risk, interest rate, property and casualty, credit risk, insurer, life insurance |
source |
28 |
| 67 |
Forewarned is Forearmed: previenting defections of our best customers |
Filippo Avigo, Salvina Piccarreta |
Presentation |
data mining, data mart |
source |
27 |
| 68 |
GAMBRO - A Leading Global Medical Technology and Healthcare Company |
Catherine Collier |
Presentation |
clinical trial, audit trail, data governance, data cleaning |
source |
10 |
| 69 |
Genomic Analysis Solutions from SAS |
Gerhard Held, Russell D. Wolfinger |
Presentation |
|
source |
25 |
| 70 |
Getting Fast Retun on Intelligence from your ERP Data |
Bernd Kosnar |
Presentation |
|
source |
26 |
| 71 |
How to benefit from SAS investments over time |
Nicholas Bull |
Presentation |
proc report, data cleaning, proc step, customer satisfaction, db2 access, ods excel, phase ii |
source |
26 |
| 72 |
How to maximize the effectiveness of 2000 salesmen |
Antonello Mana, Elena Delapiano, Giorgio Rivero |
Presentation |
likelihood function, data mining, sample |
source |
24 |
| 73 |
How to move from OPINIONS to FACTS |
G. Ricci, G. Zanini, M. Rinchi |
Presentation |
sas risk engine, trend analysis, data mining, business intelligence, distribution channel, proc freq |
source |
25 |
| 74 |
Identifying fugitives with data mining |
Bulcsu Fajszi, Gergo Galfi, Zoltan Benedek |
Presentation |
normalization |
source |
24 |
| 75 |
Implementing a new Capacity Planning Process |
Ian Hindshaw |
Presentation |
capacity planning |
source |
29 |
| 76 |
Implementing BASEL II |
Morgens Kristensen |
Presentation |
stress testing, cluster analysis, missing value, data cleaning, bufsize, credit portfolio, economic capital |
source |
25 |
| 77 |
Implementing BASEL II - What to consider |
Morgens Kristensen |
Presentation |
stress testing, cluster analysis, missing value, data cleaning, basel ii, bufsize, credit portfolio |
source |
26 |
| 78 |
Implementing Strategic Performance Management (SPM) - Will it give you the Power to Know? |
Ingrid Sternhoff, Pål Navestad |
Presentation |
|
source |
23 |
| 79 |
Improving Bank Profits with Next-Generation Data Mining Techniques |
Rafael Alverez Cuesta |
Presentation |
logistic regression, proc hpsplit, logistic distribution, regression analysis, missing value, population |
source |
17 |
| 80 |
Increasing Retail Banking Profitability through CRM: the UniCredito Italiano Case History |
Giorgio Redenmagni |
Presentation |
data mining, customer lifetime value, market basket analysis, business intelligence, corporate banking, customer profitability, customer retention |
source |
34 |
| 81 |
Information at your fingertips - Knowledge based marketing and sales at Peugeot Germany |
Josef Gerber, Thomas Marx |
Presentation |
access control |
source |
20 |
| 82 |
Information infrastructure for society: A proactive strategy |
Lars Thygesen |
Presentation |
|
source |
31 |
| 83 |
Innovations in Cash Logistics: CoBaCash - An intranet based system for optimizing cash supply for branches and ATMs |
A. Ruban, L. Nottekämper |
Presentation |
data wrangling, sorted data, raw data, logistic distribution |
source |
25 |
| 84 |
Integrating With .NET - Patterns for Leveraging SAS in Microsoft's Strategic Architecture |
Daniel Jahn |
Presentation |
in=, sql server, web service, proc corr, dataset, proc sql, libname engine |
source |
29 |
| 85 |
Introduction to Customer Intelligence |
Alan Gormley |
Presentation |
banking, credit scoring, outlier, capacity planning, data validation rules, campaign response, credit risk |
source |
26 |
| 86 |
Introduction to SAS Risk Management |
Mika Hakuni |
Presentation |
variance, proc princomp, data mining, credit risk, market risk, monte carlo, operational risk |
source |
24 |
| 87 |
IT as a Driving Force for Business Innovation in Slovak Insurance |
Oto Maly |
Presentation |
outlier, data mart, life insurance, cluster analysis, link analysis, output delivery system |
source |
49 |
| 88 |
IT Service Quality Excellence |
Donatella Gandino |
Presentation |
fault management, service provider |
source |
26 |
| 89 |
Japanese Corporate Bankruptcy Prediction Model |
Iwabuchi |
Presentation |
data cleaning, data mining, dataset, logistic regression, credit risk, logistic distribution, regression analysis |
source |
22 |
| 90 |
Know whom your cusomers listen to - Scoring for marketing channels reception propensity |
Pawel Gasiorowski, Wojciech Latusek |
Presentation |
logistic regression, neural network, sample, data mining, logistic distribution, regression analysis, probability distribution |
source |
20 |
| 91 |
Leverage your Microsoft strategy by integrating SAS business intelligence solutions with v8e Integration Technologies |
Ilse Eelen, Patrick Bourgi |
Presentation |
business intelligence, analytics platform |
source |
35 |
| 92 |
Leveraging SAP BW with SAS for creating business value at Electrabel |
Patrick Xhonneux, Paul Bruynseels |
Presentation |
snowflake schema, proof of concept, data mining, dimension table, bank transaction, sas risk engine, sas consultant |
source |
22 |
| 93 |
Linking Financial Measures to Your Company's Strategy |
David C. Schwerbrock |
Presentation |
|
source |
28 |
| 94 |
Making Your Data a Strategic Asset |
Tony Fisher |
Presentation |
business intelligence, data profiling, frequency analysis, data cleaning, data warehouse, outlier, proc freq |
source |
29 |
| 95 |
Managing Risk of a Power Generation Portfolio |
Coyle |
Presentation |
sas risk, credit risk |
source |
17 |
| 96 |
Market risk estimation through modeling and visualizations in the SAS System |
Jerzy Krawczuk |
Presentation |
variance, market risk, interest rate, confidence level, time series analysis, probability distribution, operational risk |
source |
9 |
| 97 |
Mazimizing Campaign Return through Marketing Intelligence |
Markus Matzak |
Presentation |
sample, customer experience, data mining, cross-sell |
source |
16 |
| 98 |
Medicaid Data Warehouse |
Anthony Simmons |
Presentation |
sql server, proc sql, data warehouse, insurance claims, sas enterprise guide, data mining, financial reporting |
source |
12 |
| 99 |
Modern Management in the Public Sector using SAS Strategic Performance Management |
Debora De Haes |
Presentation |
management reporting |
source |
22 |
| 100 |
Monitoring internal behavior of external IT services using ITSV |
Peter Oudshoorn |
Presentation |
data warehouse, structured data, quality of service, capacity planning, correlation |
source |
29 |
| 101 |
Moving from PC SAS 6.12 to SAS 8.2 on a Terminal Server |
Monika Kawohl |
Presentation |
data cleaning, clinical trial, sample |
source |
22 |
| 102 |
MPG - SAS |
Arnaud Parent, Isabelle Le Roy |
Presentation |
excel, seasonality |
source |
30 |
| 103 |
Netarget - intelligence creation as core business process |
Christophe Cousin |
Presentation |
data science, normalization, sample |
source |
20 |
| 104 |
New tools for a new context: Enterprise Miner in the French gas industry |
Herve Augendre |
Presentation |
logistic regression, data mining, logistic distribution, regression analysis |
source |
17 |
| 105 |
OLAP Business Metrics Library - Tailored Analyses for Retailers' Mass Data and complex Business Figures |
Sven Viergutz |
Presentation |
data mart, customer profitability, data wrangling, group by, data science, proc sql |
source |
23 |
| 106 |
Opening the door to your information |
Stephan Haux |
Presentation |
financial reporting |
source |
22 |
| 107 |
Optimising Supplier Spend - the new financial management task |
Brigitte Ley |
Presentation |
business intelligence |
source |
38 |
| 108 |
Outcome on a bank sales campaign based on scoring list |
Gianluca Bo |
Presentation |
insurer, data mining, life insurance, current account, logistic regression, response variable, sample |
source |
20 |
| 109 |
Payment Behavior Analysis and Prediction Project at a Telco Company |
Osge Neslihan Cayci |
Presentation |
data mining, churn prediction, feature selection, cross-sell, fraud management, regression analysis |
source |
21 |
| 110 |
Personalization through Web Mining - New Approaches for One-to-One Marketing |
Stefan Weingaertner |
Presentation |
business intelligence, customer retention |
source |
19 |
| 111 |
Predictin Customer Default Times using Survival Analysis Methods in SAS |
Bart Baesens |
Presentation |
survival analysis, neural network, credit scoring, data mining, proc phreg, regression analysis, proc step |
source |
16 |
| 112 |
Proactive Information Delivery via Publish and Subscribe |
Ingrid Hertel |
Presentation |
|
source |
40 |
| 113 |
Proper Architecture Considerations For Data Warehouse Implementation |
Mark Nilan |
Presentation |
metadata management, sas base, sas enterprise guide, business intelligence, data mart, data warehouse, data validation rules |
source |
29 |
| 114 |
Proving the value of IT on the bottom line |
Arne Lofgren |
Presentation |
data validation rules, capacity planning, customer satisfaction, sas risk engine, service provider, stage 1, stage 2 |
source |
24 |
| 115 |
Putting Customer Data to Work |
Jackie Ronson, Maggie Scott |
Presentation |
proc freq, financial services |
source |
19 |
| 116 |
Putting Customer Data to Work |
Jackie Ronson, Maggie Scott |
Presentation |
proc freq, financial services |
source |
19 |
| 117 |
Re-Inventing the Company: How to Manage Change |
Luc Mertens |
Presentation |
|
source |
27 |
| 118 |
Realisation of the SAS France Balanced Scorecard |
Alexandre Ghilardi |
Presentation |
key performance indicator, data cleaning |
source |
15 |
| 119 |
Rising to the challenge - 7 rules to realising your strategy |
Stefan Gossler |
Presentation |
|
source |
20 |
| 120 |
Risk Management for Utilities companies |
M. Palomo |
Presentation |
market risk, sas risk engine, variance, data governance, interest rate, management reporting, operational risk |
source |
22 |
| 121 |
ROI for forecasting cellular sales crystal bal |
Adrian Mattioli, Margie van Straten, Mike Montgomery |
Presentation |
excel, sas enterprise guide |
source |
15 |
| 122 |
ROI for forecasting cellular sales crystal bal |
Adrian Mattioli, Margie van Straten |
Presentation |
excel, sas enterprise guide |
source |
15 |
| 123 |
Runinng IT as a Business - Managing the Value of IT |
Han T. M. van der Zee, Mark Griep |
Presentation |
group by, sample |
source |
21 |
| 124 |
Running IT as a Business - How to managing your Sercie Provision - Intoduction of Improved Service Level Control & ICT Management Control |
Mark Griep |
Presentation |
business intelligence, extract |
source |
15 |
| 125 |
SAS and the CRO |
Peter Stagg |
Presentation |
21 cfr part 11, audit trail, data standard, validation documentation, clinical research, sas enterprise guide, data science |
source |
14 |
| 126 |
SAS application: PEST 4 for sequential clinical trials |
Tatsuru Matsushita |
Presentation |
standard deviation, sample size, confidence interval, confidence level, clinical trial, sample, proc calis |
source |
19 |
| 127 |
SAS Drug Development: Intelligent Research Management |
Andrew T. Fagan |
Presentation |
clinical research, 21 cfr part 11, clinical trial, audit trail, clinical data, pharmaceutical industry, data science |
source |
18 |
| 128 |
SAS Enterpise Miner: What does the future hold? |
David R. Duling, Sascha Schubert |
Presentation |
proc step, batch processing, data mining, model training, training set, dataset, proc hpsplit |
source |
45 |
| 129 |
SAS Environment-Based Data Analysis |
Marin |
Presentation |
data mining, life insurance, sas base, output delivery system, proc genmod, regression analysis |
source |
27 |
| 130 |
SAS Human Capital Management @ ING Netherlands |
H. Tijssen |
Presentation |
management reporting, phase i, phase ii |
source |
28 |
| 131 |
SAS integration Technologies - A Roadmap |
Mark Toor |
Presentation |
conditional do loop, dataset, sas base, connection string, macro loop, sas enterprise guide, proc sql |
source |
62 |
| 132 |
SAS Meets Big Iron: High Performance Computing in SAS Analytic Procedures |
Robert A. Cohen |
Presentation |
proc step, proc genmod, proc loess, proc reg, confidence interval, proc glm, logistic distribution |
source |
61 |
| 133 |
SAS OLAP Services - Driving Business Intelligence |
Ingo Brenckmann |
Presentation |
business intelligence, access control |
source |
25 |
| 134 |
SAS Process Intelligence for Manufacturing |
Gerhard Held, Ian D. Cox |
Presentation |
|
source |
41 |
| 135 |
SAS SPD Server, applying intelligence to data storage |
Jochen Kirsten |
Presentation |
access control, where statement, sas management console, by group processing, data merging, sas base, proc step |
source |
26 |
| 136 |
SAS Strategic Performance Management |
Goessler |
Presentation |
|
source |
9 |
| 137 |
SAS web technologies enable the developers to meet flexibility the client requirements |
Gvoskov |
Presentation |
output delivery system, analytics platform, excel |
source |
57 |
| 138 |
SAS/IntrNet - Information Delivery via the Web |
Ingrid Hertel |
Presentation |
|
source |
33 |
| 139 |
Scaling Up and Out: The Value Propostion of the SAS Scalable Architecture |
Cheryl Doninger |
Presentation |
|
source |
59 |
| 140 |
Segmentation and Cross-Selling Project |
Kirca |
Presentation |
credit card, retail banking |
source |
34 |
| 141 |
Solving the complex problem of Energy Trading Risk Management |
Allan Watson |
Presentation |
sas risk, business intelligence, market risk, enterprise risk, data mining, ledger, resource allocation |
source |
35 |
| 142 |
Specialized Masters in Business Intelligence |
Jean-Francois Fiorina |
According to an IDC France study the French market for the business intelligence companies grew by 33% in 2000 and represented 2.7 MdF(billion French francs). 4 big companies (Business Objects, Cognos, SAS and Hypérion) each share this market. The European market according to Dataminor, will represent 5.8Md$(billion US dollars) in 2005. The company estimates that this market will see a growth of 37% in 2001 and an average annual growth of 35% over the next 5 years. The training expenditure in this area should go up by 33 % in Europe from now to 2004. This market is fully expanding and requires specialists in sales, consulting, project management or management of these solutions of business intelligence as well as for software companies, consulting agencies, or businesses who use (or who will use) these systems. |
business intelligence, logistic distribution |
source |
5 |
| 143 |
State of the Art Management Information System in Internet Banking at Credit Suisse Financial Services |
Martin Prestera |
Presentation |
mis, management reporting, sas enterprise guide, data wrangling, insurer, excel |
source |
20 |
| 144 |
Strategic Measurement and Reporting in City Governance |
David Walker |
Presentation |
correlation, proc freq |
source |
24 |
| 145 |
Strategic Procurement in the Public Sector implementing SAS SRM at UWV |
Evert van Os, Grieko Enter |
Presentation |
claims fraud, quality assurance |
source |
19 |
| 146 |
Swin into data to best support top management decision in a dynamic and competitive market |
Cristiano Portas |
Presentation |
business intelligence, output delivery system, elapsed time, order by, phase i, phase iv, excel |
source |
40 |
| 147 |
System for calculation of flights' profitability |
Ikanowicz |
Presentation |
management reporting |
source |
27 |
| 148 |
Terabyte-class data analysis for CRM in service provider |
Ryo Mukae |
Presentation |
business intelligence, data mining, data science, sas enterprise guide, link analysis, excel, service provider |
source |
18 |
| 149 |
The Balanced Scorecard and Decision Support System - Case Study |
Elsa Farto |
Presentation |
proof of concept |
source |
41 |
| 150 |
The corporate strategy and the CRM |
Jose Luis Mena Cea |
Presentation |
data mining |
source |
12 |
| 151 |
The Integration of SAS-Datawarehousing in the business process |
Hans Koppelaar |
Presentation |
business intelligence, data mart, sas base |
source |
17 |
| 152 |
the need for e in Justice statistics |
Anne-Marie De Meyer, Martine Beullens |
Presentation |
proc tabulate, proc step, macro variable, data mart, case management, class variable, data step |
source |
42 |
| 153 |
The Norwich Union CRM Evolution |
Nunney |
This Paper will address how at Norwich Union we have taken a cautious step wise approach to building our CRM infrastructure, and how we are developing our initial direct marketing system to be the backbone of our CRM strategy. Becoming Customer Focused The need for a customer marketing database evolved from the Norwich Union direct business back in 1998. The direct business provides direct channels such as mail, telemarketing and Internet for Norwich Union and is split into a different number of product groups that deal with the company's wide range of life assurance, pensions, insurance and other offerings. Separate business units like Norwich Union Direct (Primarily Home and Motor insurance), Life and Pensions and Healthcare have physically different locations and hold their data in disparate product referenced databases. A single customer view was needed and so the MIDAS (Marketing Information Direct Access Service) project was born. The project has three aims: 1 |
proof of concept, data mining |
source |
2 |
| 154 |
The Power of Enterprise Intelligence |
Chris M. Pieper |
Presentation |
customer profitability, stage 2 |
source |
32 |
| 155 |
The problem of treasurey portfolio optimisation |
Alexey Kulemin, Vasily Konuzin, Vasily Sorokoumov, Victor Kulyshev |
Presentation |
monte carlo, interest rate, time series analysis, portfolio risk, covariance, sensitivity analysis, standard deviation, sample |
source |
52 |
| 156 |
The SAS Enterprise Architecture - Achieving Enterprise Integration |
Paul Padley |
Presentation |
change data capture, data standard, link analysis, dataset, proc sql, business intelligence, data warehouse |
source |
48 |
| 157 |
The STAR System, a Data Warehouse for Statutory Financial Reporting |
Dagmar Brautigam, Minna Oksanen |
Presentation |
audit trail, financial reporting, excel |
source |
20 |
| 158 |
The use of SAS in Volkswagen Financial Services |
Jan Suniar |
Presentation |
customer segmentation, data wrangling, excel |
source |
20 |
| 159 |
The Vuliindlela Project: Satisfying National and International Reporting Requirements |
Ismail Mamoojee |
Presentation |
mis, available balance, management reporting |
source |
34 |
| 160 |
Tracking Error |
Francoise Grandjean, Gregory Magro |
Presentation |
standard deviation, excel, extract, interest rate, management reporting, lookup, sas risk engine |
source |
21 |
| 161 |
Tracking your data warehouse using SAS |
Hiadong Tang (Don), Xiao Ji |
Presentation |
data warehouse, sas log, error message, sas batch, macro variable, business intelligence, data mart |
source |
55 |
| 162 |
Transparent strategies with financial intelligence |
Krista Saukkonen |
Presentation |
quality of service, ledger, profitability analysis |
source |
25 |
| 163 |
Tuning WebHound 4.0 and SAS 8.2 for Enterprise Windows Systems |
Martin Powdrill |
Presentation |
cpu time, mp connect, parallel processing |
source |
26 |
| 164 |
Turin Olympic Winter Games 2006: a marketing survey of local government initiatives, conducted with SAS tools |
Veronica Baldisserri, Flavio Bonifacio |
Presentation |
factor analysis, regression analysis, response variable, output delivery system, proc reg, logistic regression, proc step |
source |
44 |
| 165 |
Using activity based costing to enhance shareholder value - the tool to take shareholder value to the shop floor where it counts |
Otto Paul Brand |
Presentation |
|
source |
21 |
| 166 |
Using Metadata to drive better business decisions |
Michele Ryals |
Presentation |
sas management console |
source |
39 |
| 167 |
Using SAS to determin file and space usage in UNIX |
Mike Montgomery |
The paper will show tools developed to manage a proliferation of SAS files and directories in a UNIX environment. The tools were used to determine how and by whom approximately 2 terabytes of disk space was being used, how the usage was likely to grow, and how much of the space was been occupied without being used. Benefits derived from the tool included: an objective basis for a possible internal charge-back policy for the use of disk space, a basis for an archiving policy, essential information for an overdue V6-V8 conversion plan, essential information for a data warehousing project. The paper will also show techniques that extended the ODS HTML output beyond what is possible through its standard usage |
output delivery system, proc step, ods html |
source |
9 |
| 168 |
Valuing People as Assets - Monitoring, Measuring & Managing |
Betty Silver, Randy Guard |
Presentation |
customer satisfaction |
source |
20 |
| 169 |
Version 9 - What's New |
Paul Kent |
Presentation |
where statement, sas base, elapsed time, mp connect |
source |
24 |
| 170 |
Web & Data Warehouse to evaluate and control activities of Regione Piemonte Cancer Screening Programs |
Corrado Marozzo, Patrick Jegou |
Presentation |
output delivery system, elapsed time, format statement, data science, population, excel, proc step |
source |
44 |
| 171 |
Web Portal for Controller Information |
Louis Broekhuijsen-Blöys |
Presentation |
business intelligence, excel |
source |
24 |
| 172 |
What's New in ODS for V9.0 |
Paul Kent |
Presentation |
ods html, numeric variable, proc print, proc step, sas base, ods csv, ods pdf |
source |
40 |
| 173 |
What's New in the Output Delivery System, Version 9.0 |
Sandy McNeill |
Along with every new version of SAS, the ODS developers work hard to bring you new features. So what's new with Version 9? A new destination called MARKUP along with something called markup definitions (aka TAGSETS) will become production. This new destination allows configurability of your markup output. Another new destination (also available as a PROC) that will be production for Version 9 is the DOCUMENT. If you've ever wanted to the ability to run your procedures once and then go back and pick and choose which pieces you want or how you would like them rendered, then this is for you. In addition to these new destinations, RTF has some new features and functionality -- options for Page X of Y, decimal alignment, and cell indention are a few of the highlighted features |
proc step, output delivery system, ods rtf, proc template, proc print, footnote statement, proc report, excel |
source |
10 |
| 174 |
When Worlds Collide - ETL and EAI Combine to enhance and Intelligence Architecture |
David Annis, Mark Nilan |
Presentation |
customer experience, change data capture, transaction monitoring, proc sql |
source |
24 |