Enterprise Data World 2009

Formerly known as the DAMA International Symposium and Wilshire MetaData Conference, Enterprise Data World 2009 was held April 5-9 in Tampa, Florida at the Tampa Convention Center.

Enterprise Data World is the business world’s most comprehensive vendor-neutral educational event about data and information management. This year’s program was bigger than ever before, with more sessions, more case studies, and more can’t-miss content. With 200 hours of in-depth tutorials, hands-on workshops, practical sessions and insightful keynotes, the conference was a tremendous success. Congratulations and thanks to Tony Shaw, Maya Stosskopf and the entire Wilshire staff.

I attended Enterprise Data World 2009 as a member of the Iowa Chapter of DAMA and as a Data Quality Journalist for the International Association for Information and Data Quality (IAIDQ).

I used Twitter to provide live reporting from the sessions that I was attending (Click here to view all of my #edw09 tweets).

I wish that I could have attended every session, but here are some highlights from ten of my favorites:

8 Ways Data is Changing Everything

Keynote by Stephen…

Formerly known as the DAMA International Symposium and Wilshire MetaData Conference, Enterprise Data World 2009 was held April 5-9 in Tampa, Florida at the Tampa Convention Center.

I attended Enterprise Data World 2009 as a member of the Iowa Chapter of DAMA and as a Data Quality Journalist for the International Association for Information and Data Quality (IAIDQ).

I used Twitter to provide live reporting from the sessions that I was attending.

I wish that I could have attended every session, but here are some highlights from ten of my favorites:

8 Ways Data is Changing Everything

Keynote by Stephen Baker from BusinessWeek.

His article Math Will Rock Your World inspired his excellent book The Numerati. Additionally, check out his blog: Blogspotting.

Quotes from the keynote:

“Data is changing how we understand ourselves and how we understand our world”
“Predictive data mining is about the mathematical modeling of humanity”
“Anthropologists are looking at social networking (e.g. Twitter, Facebook) to understand the science of friendship”

Master Data Management: Proven Architectures, Products and Best Practices

Tutorial by David Loshin from Knowledge Integrity.

Included material from this excellent book Master Data Management. Additionally, check out his blog: David Loshin.

Quotes from the tutorial:

“Master Data are the core business objects used in the different applications across the organization, along with their associated metadata, attributes, definitions, roles, connections and taxonomies”
“Master Data Management (MDM) provides a unified view of core data subject areas (e.g. Customers, Products)”
“With MDM, it is important not to over-invest and under-implement – invest in and implement only what you need”

Master Data Management: Ignore the Hype and Keep the Focus on Data

Case Study by Tony Fisher from DataFlux and Jeff Grayson from Equinox Fitness.

Quotes from the case study:

“The most important thing about Master Data Management (MDM) is improving business processes”
“80% of any enterprise implementation should be the testing phase”
“MDM Data Quality (DQ) Challenge: Any % wrong means you’re 100% certain you’re not always right”
“MDM DQ Solution: Re-design applications to ensure the ‘front-door’ protects data quality”
“Technology is critical, however thinking through the operational processes is more important”

A Case of Usage: Working with Use Cases on Data-Centric Projects

Case Study by Susan Burk from IBM.

Quotes from the case study:

“Use Case is a sequence of actions performed to yield a result of observable business value”
“The primary focus of data-centric projects is data structure, data delivery and data quality”
“Don’t like use cases? – ok, call them business acceptance criteria – because that’s what a use case is”

Crowdsourcing: People are Smart, When Computers are Not

Session by Sharon Chiarella from Amazon Web Services.

Quotes from the session:

“Crowdsourcing is outsourcing a task typically performed by employees to a general community of people”
“Crowdsourcing eliminates over-staffing, lowers costs and reduces work turnaround time”
“An excellent example of crowdsourcing is open source software development (e.g. Linux)”

Improving Information Quality using Lean Six Sigma Methodology

Session by Atul Borkar and Guillermo Rueda from Intel.

Quotes from the session:

“Information Quality requires a structured methodology in order to be successful”
Lean Six Sigma Framework: DMAIC – Define, Measure, Analyze, Improve, Control:
- Define = Describe the challenge, goal, process and customer requirements
- Measure = Gather data about the challenge and the process
- Analyze = Use hypothesis and data to find root causes
- Improve = Develop, implement and refine solutions
- Control = Plan for stability and measurement

Universal Data Quality: The Key to Deriving Business Value from Corporate Data

Session by Stefanos Damianakis from Netrics.

Quotes from the session:

“The information stored in databases is NEVER perfect, consistent and complete – and it never can be!”
“Gartner reports that 25% of critical data within large businesses is somehow inaccurate or incomplete”
“Gartner reports that 50% of implementations fail due to lack of attention to data quality issues”
“A powerful approach to data matching is the mathematical modeling of human decision making”
“The greatest advantage of mathematical modeling is that there are no data matching rules to build and maintain”

Defining a Balanced Scorecard for Data Management

Seminar by C. Lwanga Yonke, a founding member of the International Association for Information and Data Quality (IAIDQ).

Quotes from the seminar:

“Entering the same data multiple times is like paying the same invoice multiple times”
“Good metrics help start conversations and turn strategy into action”
Good metrics have the following characteristics:
- Business Relevance
- Clarity of Definition
- Trending Capability (i.e. metric can be tracked over time)
- Easy to aggregate and roll-up to a summary
- Easy to drill-down to the details that comprised the measurement

Closing Panel: Data Management’s Next Big Thing!

Quotes from Panelist Peter Aiken from Data Blueprint:

Capability Maturity Levels:
- Initial
- Repeatable
- Defined
- Managed
- Optimized
“Most companies are at a capability maturity level of Initial or Repeatable”
“Data should be treated as a durable asset”

Quotes from Panelist Noreen Kendle from Burton Group:

“A new age for data and data management is on horizon – a perfect storm is coming”
“The perfect storm is being caused by massive data growth and software as a service (i.e. cloud computing)”
“Always remember that you can make lemonade from lemons – the bad in life can be turned into something good”

Quotes from Panelist Karen Lopez from InfoAdvisors:

“If you keep using the same recipe, then you keep getting the same results”
“Our biggest problem is not technical in nature – we simply need to share our knowledge”
“Don’t be a dinosaur! Adopt a ‘go with what is’ philosophy and embrace the future!”

Quotes from Panelist Eric Miller from Zepheira:

“Applications should not be ON The Web, but OF The Web”
“New Acronym: LED – Linked Enterprise Data”
“Semantic Web is the HTML of DATA”

Quotes from Panelist Daniel Moody from University of Twente:

“Unified Modeling Language (UML) was the last big thing in software engineering”
“The next big thing will be ArchiMate, which is a unified language for enterprise architecture modeling”