THE ANALYTICS FORUM
Conference Sessions
(NOTE: Some sessions have "Pre-Reading Materials."  Follow the links to check them out!)

Tuesday, November 5, 2002
5:00 pm - 6:00 pm
SIG

The Data Vault: The Next Evolution of Data Modeling

Daniel  Linstedt
Chief Technology Officer
Core Integration Partners

The Data Vault is a patent-pending technique which some industry experts have predicted may start a revolution as the next big thing in data modeling for enterprise warehousing.  This SIG session, led by the creator of the Data Vault, will explain what this new concept is, what its architecture and components are, its applications, and the advantages of the Data Vault over existing techniques.

Pre-Reading Materials

Wednesday, November 6, 2002
10:30 am - 11:30 am
Conference Session 

The Many Become One...Integrating Disparate Data into an Enterprise Data Warehouse

Alan  Chow
SVP, R&D
Teradata, a division of NCR

At its onset, data warehousing promised businesses a better understanding of their customers' businesses as a basis for better decision-making.  Fifteen years later, some organizations have achieved that goal.  They know their customers better, adapt to change faster, and their more accurate predictions pay off in business terms.  However, other organizations have poured money into data warehousing efforts, but haven't realized potential returns.  What's the difference?  All too often analysis is hindered by islands of data scattered across their organization. 

Businesses house data throughout the organization in unconnected and incompatible data marts, creating multiple versions of the truth.  Relatively speaking, data marts appear to be a cheap way, especially to business units, to have control over specific information.  However, current research highlights the disadvantages of those data marts in terms of the cost of ongoing support and maintenance.  

In this presentation, Alan Chow, SVP, R&D, Teradata, a division of NCR, explores how to integrate data from disparate transactional ERP systems into an enterprise active data warehouse - giving users a single view of their business and avoiding the use of costly data marts and ODS.  Alan includes a discussion of consolidation strategies, from higher-level architectures to specific technical solutions, that increase the speed and reduce the cost of data integration between disparate systems. 

Wednesday, November 6, 2002
11:40 am - 12:40 pm
Conference Session 

Analytical Modeling Manifesto

Tom  Haughey
Chief Technology Officer
Pepsi Bottling Group 

This presentation will re-examine the concept of data design for analytical systems such as the data warehouse. It will take a close look at dimensional modeling and define its proper role and context. It will position ER modeling, dimensional modeling (and other forms) into a general framework. Dimensional modeling is usually presented as the end-all and be-all of data warehousing. Is dimensional modeling one of the great con jobs in data management history? In fact, dimensional modeling has strengths and weaknesses. In some ways it has become outmoded. In other ways, it has been around for decades (and will continue to be). There are three ways to improve performance: use better hardware, use better software and optimize the data. The primary justification for dimensional modeling is to improve performance by compromising the data to compensate for the inefficiency of technology. It uses the third method above. A secondary purpose is to provide a consistent base for analysis. Dimensional modeling comes with a price and with restrictions. There are times and places where dimensional modeling is appropriate and will work, and other times and places where it is inappropriate and will actually interfere with the goals of a warehouse.  

To make matters worse, the data warehouse industry suffers from a host of double-entendres that make it difficult to communicate meaningfully. It is not uncommon for two “gurus” to disagree about something without realizing that they are not talking about the same thing. Because of this it is actually necessary to start over and define some terms. This presentation will do just that: it will reexamine these concepts and redefine them; it will establish a framework for integration; and it will address a number of specific analytical modeling issues or situations, such as the following: 

Wednesday, November 6, 2002
1:45 pm - 2:45 pm
Conference Session

 Analytical API Update: XML for Analysis & JOLAP

Seth  Grimes
Principal Consultant
Alta Plana Corporation 

BI vendors led by Microsoft, Hyperion, and SAS Institute last year released version 1.0 of the XML for Analysis (XML/A) specification, "an open-standards-based messaging interface" designed to "promote the standardization of the data access interaction between a client application and business intelligence systems and other applications over the Web and in distributing environments." 

Meanwhile, the nascent JOLAP specification provides a similar API for the J2EE [Java] Web services environment, one that "supports the creation and maintenance of OLAP data and metadata, in a vendor-independent manner."

An overview of the XML/A and JOLAP specifications:

Attendees will learn:

Pre-Reading Materials

Wednesday, November 6, 2002
3:15 pm - 4:15 pm
Conference Session 

Drill-Thru and the Corporate Information Factory

Nicholas  Galemmo
Information Architect
Nestle

  This presentation examines the issues involved in providing drill-through capability from summarized dimensional data marts into a detailed 3NF data warehouse as prescribed in the Corporate Information Factory architecture.

It presents Dr. Kimball's Comforming Dimensions concept and applies it to the CIF.  It looks at issues involved in generating and preserving key values and dealing with structural differences between the 3NF and Dimensional models.  It identifies problem areas and possible solutions.  It investigates the level of functionality a query tool should provide to support cross-model drill through capabilities.

Issues discussed:

Thursday, November 7, 2002
8:30 am - 9:30 am
Conference Session 

New Approaches to Customer Data Integration

A) Reference-Based Customer Data Integration: What it is and Why it’s Better

Chandos  Quill
Vice President, Strategic Marketing
Experian 

Integrating customer data is, by nature, a reference process. Knowing whether data is accurate or not requires a picture of reality to which data cleansers and integrators can compare records. Any other process is a mathematical guessing game that tends to over-or-under merge customer records. If companies aren’t careful, they can accidentally eliminate customer relationships and perpetuate data inaccuracies. 

This presentation details new reference-based data integration methods that achieve dramatically better results. These methods go beyond mere matching formulas to compare customer data to historical customer reference repositories. Case studies will be presented that demonstrate how reference-based matching has helped companies increase the accuracy and number of matching customer records, eliminate ever-matching, reduce processing times and costs, and keep data integrated over time.

Pre-Reading Materials

B) Data Synchronization – A New Approach to Enterprise Customer Data Integration

Jeff  Canter
Vice President of Operations
Innovative Systems, Inc.

Data integration projects are complex and challenging. Customer data integration projects are even more complex and challenging because they usually support multiple business units, each with different requirements for defining "customer."  The departments’ competing definitions and different business objectives often undermine the success of the traditional customer data integration project.

Data Synchronization provides a new approach to customer data integration, an approach that accommodates competing business objectives, and still provides an integrated, enterprise customer view.

This session will present a new vision for enterprise customer data integration, and real-world applications of this valuable approach.  In this session, Jeff Canter will identify and explain the critical success factors for creating a sharable, enterprise customer profile that can easily be segmented into "purpose-driven" views to support the different requirements of departments and applications across the enterprise. 

Thursday, November 5, 2002
9:45 am - 10:45 am 

XML Tools: XQUERY

Denise  Draper
Chief Software Architect
Nimble Technology

Alex Cheng
Director of Engineering
Ipedo

XQuery is the new query language being designed by the W3C to query XML data.  This talk will introduce the main XQuery language features, in particular comparing them to SQL and existing XML access methods such as XPath.  We will demonstrate how XQuery can be used to create a simple web application.  

Pre-Reading Materials

Thursday, November 5, 2002
11:00 am - 12:00 pm 

Real-Time Integration & Analytics

Seth  Grimes
Principal Consultant
Alta Plana Corporation 

John  Ko
Product Marketing Manager
DataMirror  

Ron Agresta
Products Engineer
Dataflux

In this session we look at the inexorable push for instantaneous information.  Whatever your preferred terminology -- “Real-time”, “Zero latency”, “Information on Demand”, “Active Warehousing” – you need to be working towards shorter and shorter timeframes for getting data into and out of analytical systems. 

How is real time integration accomplished in an XML world?  Companies must be able to capture selected events such as purchase orders or invoicing from any application database and send them in industry standard XML formats across the enterprise and beyond. Is the “streaming” of XML documents to application servers, B2B exchanges or other XML-driven applications the answer?

Pre-Reading Materials

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