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.

MIT Information Quality Industry Symposium Day 1

I’m just settling in for Day 2 of the MIT IQIS 2009 and thought I’d throw out some thoughts for a couple of future posts I’m drafting. Here are the quick recaps from yesterday. 

Danette McGilvray - Ten Steps to Data and Trusted Information

A great primer on how to manage any Data  Quality project. Her 10 steps made a lot of sense. Not all of the methodology would be used for any given project, but still it worked for me. I also won her book, “Executing Data Quality Projects” in the drawing at the end of the class.

Bill Inmon - DW2.0 and Unstructured Data

After 10+ years in Data Warehousing I finally got to see Bill Inmon speak. Bill is the rockstar of the DW world. He’s regarded as the Father of Data Warehousing and treated as royalty at a conference like this. His new stuff was all about contextual ETL. Sounded interesting, but I believe there are others working on the same thing.

Keynote: Ronald Bechtold - Transforming the Army with High

Ronald is the Chief Data Officer at the Army. Cool title. Not what you’re picturing. He is a passionate CIO type who has a huge challenge. Definitely some words of wisdom in there. “Focus on solving problems,” rather than tools, technology or data. Good stuff!

Joe Bugajski - MDM Improves Information Quality to Deliver Value

Joe had some great examples where Data Quality actually led to increased revenue. Imagine that! Value from Data work. I think that’s what we’re all striving for. Joe is a big personality who speaks well, so this one was entertaining.

Mark Goloboy (that’s right, me) - CRM Data Quality for Sales and Marketing

After a bit of nerves, I found my groove and thought the presentation went really well. Some good questions about where my company started with Data Governance - it’s a very new ffocus or us. I also got to push back on some industry experts when asked why we weren’t focusing on MDM to start. Plus, Bill Inmon attended.

Martin Boyd - Product Data Quality Product from Silver Creek

More contextual analysis. Seemed to be done in a very smart way. The software was functional at big clients, and they had figured out how to solve some complex issues around improving poor product data. If they had the same thing for Customers, it would be a more interesting product. More development or a merger are needed here.

Letting B2B Data Die or: How I Learned to Stop Worrying and Ignore the Problem

I had a conversation with a colleague from another company recently. They mentioned a data quality project to clean up old B2B CRM Data.  I had to stop and ask, “Why?” This wasn’t just old data, but really old pre-acquisition data from another source system.

We discussed further and I found that the data in question was sales data from 2006. When it was migrated the database keys were butchered, and many of the relationships were lost. It was going to take  four FTE resources over 6 months to fix the problem. In a bad economy, I just couldn’t justify why any company would spend that effort. My suggestion… Dump the data from the reporting tables. That’s right. Delete it. Archive it for audit purposes, but get it out of the way and focus on today’s problems.

My colleague was shocked. Here I am, a Data Governance expert and Data Quality evangelist telling them to ignore the problem. My reasoning? You need to constantly prioritize your projects. If something is more valuable in terms of revenue, or presents a greater risk, or is a bigger pain to more people, fix that first! Don’t dwell on perfection. You’ll never get there. Just try to make the most improvements you can, as quickly as you can. Grab the low hanging fruit rather than re-planting the tree.

If this offends your data quality sensibilities, please comment. I’m curious to know whether my opinion resonates.

Meet the Data, Technology and Analytics Blog

This is the first in a series of blog posts discussing important trends in Data Governance, Marketing Analytics, Sales and Marketing Technology, and Social Media. I’ve decided that in order to learn from the constant flood of information on podcasts, blogs, books, and internet articles, I need to embrace the technologies and put my opinion of them out there for others to review.

I have included links to more information about me, and will integrate personal and professional information into the site in the future. For now, check me out on LinkedIn for professional interests, and Facebook for personal interests.

Please visit the site to see future posts, and leave your feedback.

Mark