Wednesday, August 21: TDWI Data Modeling: Data Warehousing ...

August 2002
Dear Attendee, Thank you for joining us last week in Las Vegas for our TDWI World
Conference- Summer 2002 and for filling out our conference evaluation. Even
with the plethora of activities available in Vegas, classes were filled all
week long as everyone made the most of the wide range of full- and half-day
courses, Guru Sessions, Peer Networking, and Night School.
We hope you had a productive and enjoyable week in Las Vegas. This trip
report is written by TDWI's Research Department, and is divided into nine
sections. We hope it will provide a valuable way to summarize the week to
your boss! Table of Contents
I. Conference Overview
II. Technology Survey
III. Keynotes
IV. Course Summaries
V. Peer Networking Sessions
VI. Vendor Exhibit Hall
VII. Hospitality Suites and Labs
VIII. Upcoming Events, TDWI Online, and Publications
IX. Best Practices and Leadership in Data Warehousing Awards I. Conference Overview By Meighan Berberich, TDWI Marketing Manager; Margaret Ikeda, TDWI
Membership Coordinator; and Yvonne Rosales, TDWI Registration Coordinator We had a terrific turnout for our Summer 2002 Conference. More than 630
data warehousing and business intelligence professionals attended from all
over the world. Our largest contingency was from the U.S., but data
warehousing professionals came from Canada, Europe, Asia, New Zealand,
Saudi Arabia, and South America. This was truly a worldwide data
warehousing event! Our most popular courses of the week were "TDWI
Fundamentals of Data Warehousing," "TDWI Data Modeling," "Business
Intelligence for the Enterprise," "Dimensional Modeling, Beyond the
Basics," and "Designing a High Performance Data Warehouse."
Data warehousing professionals devoured books for sale at our membership
desk. The most popular titles were: 1. The Data Warehouse Lifecycle Toolkit, R. Kimball, L. Reeves, M. Ross,
& W. Thornthwaite
2. The Data Warehouse Toolkit, 2nd Edition, R. Kimball & M. Ross
3. Improving Data Warehouse and Business Information, L. English
4. Data Model Resource Handbook, Vol. 1, L. Silverston
5. Building and Managing the Meta Data Repository, D. Marco II. Technology Survey-Data Modeling, ETL, and Meta Data
By Julia F. Butcher, Partner, Panacea Group, and Consultant with CONNECT:
The Knowledge Network During the TDWI World Conference-Summer in Las Vegas, we surveyed
colleagues on a number of topics relating to the implementation and ongoing
support of their data warehouses. The survey provides insight into some of
the most effective ways to manage and organize resources. This summary
reflects the views of a representative sample of the survey respondents.
[1] The majority of colleagues completing the survey were corporate IT
professionals. Forty-nine percent of respondents were providing information
on data warehouses that have been in production for one to five years. The
remaining respondents were working on data warehouses that were either not
yet in production or had been in production for less than a year. Fifty-five percent of the respondents were working with data warehouses
that they classified as departmental data stores, while the remaining 45
percent were working with enterprise solutions. Of those warehouses in
production for less than one year, the vast majority were reported to be
departmental solutions. Of warehouses in production for one to five years,
80 percent were reported to be enterprise solutions, as were 85% of
production warehouses with more than five years in service. When asked if the demand for information in the data warehouse had changed
in the past year, 96 percent reported that demand had increased, and 4
percent reported that demand had remained the same as last year. Notably,
none of the respondents reported a decrease in demand for data warehouse
information. Of executive sponsor support, 56 percent reported an increase
and 7 percent reported a decrease in executive support, with the remainder
(37 percent) reporting no change in executive support.
[pic]
Diagram 1 Respondents were asked four questions based on diagram 1.[2] When asked
which stage of maturity best described their data warehouses, 37 percent
responded that initiation best described their current situation, 33
percent reported being in the growth stage and 30 percent in the maturity
stage. When dividing the total budget allocated for the data warehouse,
respondents in the maturity stage indicated that an average of 58 percent
of the total budget was spent during initiation, 25 percent during growth,
and 17 percent in maturity. The information technology and business organizations building and using
data warehouses included a wide array of tasks and responsibilities.
Respondents indicated that teams are most effective when the business
organization is responsible for: data warehouse executive sponsorship,
assistance in obtaining the necessary budget, providing detailed
requirements of data and reporting needs, assisting with data validation
and testing, training other business users in the use of the information,
and creating reports with business intelligence tools. The most effective
information technology teams are responsible for the technical
implementation of hardware and software, operations required for loading
data warehouses from source data, and management of the implementation
projects, often in partnership with key business users. The majority of respondents with warehouses in the growth and maturity
stages indicated that the most effective organizational model for them
included a separate, dedicated, ongoing support team that manages the day
to day loading and troubleshooting of the production warehouse while the
development team is responsible for the implementation of new subject
areas. Additional responsibilities were addressed in the following table: |Task |IT |Business |Outside |Shared by |Not |
| |owned |owned |organizati|IT and |done |
| | | |on |business | |
|Data training |34% |31% |3% |24% |8% |
|Warehouse reporting and |52% |35% |4% |9% |0% |
|data manipulation tools | | | | | |
|training | | | | | |
|Meta data management and |58% |13% |0% |17% |12% |
|maintenance | | | | | |
|New subject rollout |35% |17% |0% |48% |0% |
|planning and management | | | | | |
|New subject rollout |45% |0% |9% |36% |10% |
|execution | | | | | |
Of the organizations that responded to the survey, 47 percent reported that
outside consulting services were used in the development and/or support of
their data warehouses. Of those, 93 percent used consultants in the
initiation stage, 57 percent in the growth stage, and 29 percent used
consultants in the maturity stage. Of those organizations utilizing
consulting resources, the following table reflects the roles played by
consultant resources:
|Role |Utilization |
| |%[3] |
|Project Management |15% |
|Technical |48% |
|Architecture | |
|Data Modeling |33% |
|Database |30% |
|Administration | |
|Business Analysis |19% |
|Design |56% |
|Construction |63% |
|Testing |41% |
|Training |15% |
|Deployment |30% |
|Production Support |33% |
III. Keynotes Monday, August 19, 2002: Business Intelligence 2002: Trends, Teams, and
Taboos By Wayne W. Eckerson, TDWI Director of Education and Research Wayne Eckerson kicked off the week by asking the question many TDWI members
are pondering: "What's next?" Eckerson stated that many data warehousing
teams have spent the past couple of years head down building their first
several iterations of the data warehousing environment. Now they want to
build on initial successes (or recover from unfortunate failures) and make
the data warehouse more strategic to the organization. Eckerson presented data that suggests that slightly more than one third (35
percent) of organizations believe their data warehouses are strategic to
their companies. Eckerson said strategic data warehouses are "mission
critical systems that drive the business on a day to day basis." He
referenced Best Buy's Web-based scorecards for analyzing product
assortments, inventory, sales, and supplier performance as an example of a
strategic data warehouse that delivers huge benefits. To create a strategic data warehouse, Eckerson said companies need to
adhere to the four "A's": Alignment, Architecture, Analytics, and
Applications. Under Architecture, Eckerson drew a sizable response from the
audience when he introduced a KPI for data warehouses: "The health of your
data warehouse is inversely proportional to the number of spreadsheets
being used as surrogate data marts." Eckerson calls these surrogate data
marts "spreadmarts" and offered several strategies for weaning users off
renegade spreadsheets onto a more architected data environment. Thursday, August 22, 2002: The Future of BI: Where Do We Go from Here? Keynote Panel: Herb Edelstein, Doug Hackney, Claudia Imhoff, Laura Reeves,
and Bill Schmarzo; moderated by Wayne Eckerson The Thursday keynote panel consisted of luminaries Herb Edelstein, Doug
Hackney, Claudia Imhoff, Laura Reeves, and Bill Schma