MIT Information Quality Symposium Day 2

With Day 2 of the MIT IQIS complete, I thought it would be good to write up another summary. I was very impressed with the quality of speakers and their dedication to the field of Information Quality. The work shows a lot of innovative thinking and pride. (I’ll add in links and update later today)

Robert Grossman – Information Quality in the Cloud

Bob is part of the Open Cloud Consortium and passionate about the topic. He presented everything you need to know to understand where Cloud Computing is today, where it’s going next (based on open debate among dueling standards boards), and how it affects Information Quality discussions. He has a unique ability to take very complex topics and break them down into simple conversations.

The most interesting part for me was defining Public, Community and Private Clouds, which I couldn’t have described before this talk. I also appreciated his comment that Cloud is the only way to analyze 100TB of data, and that the alternative is to merely entomb it.

Delphine Clement - Cost of Non Quality Data

Delphine is from HP in France and discussed how they have approached their KQI – Key Quality Indicators. I like that KQIs mirror KPIs but that Information Quality is metadata reporting rather than business metrics so it’s separate. Delphine also presented a methodology for measuring direct vs. indirect cost savings from Data Quality initiatives. She has clearly spent a lot of time working on this approach and is doing a great job. I really enjoyed this presentation.

Lyn Robison - Diagnosing IT’s Impact on the Business

Lyn, from The Burton Group has a theory on how to measure data quality from an IT perspective, but I thought it was very pie in the sky. There were lots of questions about the politics of such an effort, and I don’t think the approach was practical. For instance, if your measured data quality metrics turn up as poor, the IT organization will blame the business. There’s no way this could work politically.

I liked that Lyn tried to compare the business people’s perception of Data Maturity vs. the IT perception, but how do you align IT perception and Business perception? Someone also asked, should IT be measured on poor data quality? The answer: Not if the Business owns the data.

Steve Sarsfield - Using Data Quality Scores to Sell IQ Value

Steve echoed others who encouraged Information Quality progress by “Leveraging a Crisis” to build momentum. He also asked us to present the “Do Nothing” approach, i.e. present to our management what would happen if they ignored the problem. Steve’s scoring method was based on the Trillium TS Insight product, but appeared to be a practical way to measure Data Quality. I think some of this can be done easily with or without Trillium, but I appreciated how the tool can manage the measurements over time.

Marillo Boccia – Data Quality in the Media Industry

Marillo is the Director of Database Marketing at Grupo Abril, the largest publisher in the Southern Hemisphere. He presented a project (done with the help of service provider Assesso) where his team personalized magazine ads for Banc Itau to 1.2 Million subscribers. Cool stuff. They merged their subscriber database with the bank’s and did a massive customer data cleanup to ensure very high data quality. They amazed their customers in the process.

Dan Defend and Aparna Vani - Data Quality Challenges for Yahoo’s Massive Data Environment

Dan and Aparna presented the Data Quality and Analytics sides respectively. They monitor website interaction and uncover trending and outage information by analyzing a constant flow of clickstream data. Their group deals iwth duplication challenges, security issues, and the need to report outage alerts instantly. Their work was also driven by past MIT IQIS conferences, and they presented their practical approach to establishing a central data quality process and framework.