Data Governance is an important discipline to institutionalize in organizations that create and leverage data…which happens to be just about any organization with processes.  And that is the key: data governance is really not about data at all.  It is about creating more efficient, equitable and compliant processes.  The data just happens to be the easiest way to get there.  The basic cycle is processes create data, and by finding data issues, you can (more times than not) find an offending process issue.  Simple enough.

However you will be hard-pressed to find a robust data governance program at most organizations because most organizations go about it the wrong way. Many start with a big-bang approach which can be summarized as coercing a dozen key stakeholders to take half a day a month to talk about standards, road maps and maturity models.  It also doesn’t help that business leaders often struggle with quantifying the value of “data management” or “data quality”.

Build your data governance program one issue at a time.  Find a data problem, find the associated process issue, measure the breadth of the issue, work with the stakeholders to get it fixed, measure the results.  Rinse and repeat.  As you work through each issue, start presenting the results cumulatively.  Try to focus on low hanging fruit initially (few stakeholders, easy fixes) and as you build measurable results, expand to include larger issues with more stakeholders that require broader decisions.  Keep up the regularity of the issues you find, create a tracking list or queue, and start having regular meetings with the stakeholders including IT.  All of a sudden, you have yourself an actionable group of stakeholders making data governance decisions. They see the value, they understand the importance, and you have shown quantifiable value early and often.

CentricInfo, I’m proud to say, was acquired by the Enterprise Strategy Group (ESG) as of December 1st, 2010 (stay tuned for the press release).  ESG is a full service, integrated 360 degree analyst firm that serves technology professionals with market research, hands-on lab testing and strategic consulting.  What they lacked – until now – is coverage and service offerings in the data management market.  CentricInfo brings to ESG a talented group of technologists and business analysts with data management skills with an end-user perspective. Because we have predominantly been working with end users solving business-IT challenges, we enjoy a fresh view of technology and how it is being realistically deployed in the field.   CentricInfo extends ESG’s current consulting practice with experience and best practices in deploying, managing, and maintaining database applications, whether they are used for online transaction or decision support processes.  The CentricInfo team takes an information-centric approach – looking from the data up to the application and business process that supports users, as well as looking down the technology stack to make sure that technology is aligned cost effectively. Now, as part of ESG,we will continue to offer our comprehensive suite of services – but now have the added benefit of research and analysis, peer review and score-carding capabilities that ESG provides.  We are all excited about this new opportunity and look forward to an exciting 2011.

Happy New Year!

Julie Lockner

2010 - Then Founder & President, CentricInfo

2011 – Now Sr Analyst & VP, Data Management, ESG

A successful Information Lifecycle Management (ILM) program not only targets the implementation of a balanced storage strategy but it also addresses the effective and efficient use of data. In fact, you will be hard-pressed to fully implement a balanced architecture for your organization without addressing the data first. Who is using the data? What is it being used for and where does it live? How is it being used? What business processes create, edit, modify, measure and leverage this data? Clearly answering question such as these can unearth a multitude of potential actions around creating better efficiency in data creation, usage, replication/duplication, and retention.

An oversimplified example might be: database A has a table with a million rows containing five years of data. After a thorough analysis, it is revealed that only three months of data are really used and the rest can be removed, effectively cutting the table down to 50k rows. Now, when implementing a tiered storage strategy, we only need to store 50k rows (perhaps on a higher tier based on its usage) as opposed to splitting hot and cold data and overstoring unneeded information. We’ve effectively reduced the hardware, facilities and support cost by not storing the other 950k rows of data and at the same time aligned the business process (data usage) with the correct storage tier. Expect to release somewhere between 50-75%* of the now unused storage back to the procurement pool to be repurposed.

With a full-cycle ILM implementation, we can show not only that the right storage mix for our business (business performance) has been delivered, but that we have reduced the overall usage (therefore cost) of our IT assets (business efficiency). In other words, true organizational value will stem from ROA: the more effective and efficient use of assets. To deliver ROA with ILM, intiatives must address everything from the business process to the disk.

*Estimated range. 95% of the written data was removed, however, you need to account for database overhead (reorganization, partitioning, etc) and storage overhead (LUN sizes, virtualization, etc).

One of the key goals of the capacity planning discipline is to achieve a balance in infrastructure assets. Essentially, this involves balancing CPU – your raw horsepower – with I/O delivery or throughput. An example of an unbalanced architecture would be where you have lots of CPU to crank through data, but your throughput is too constrictive to allow full use of your CPU. 

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CentricInfo is a data management consulting services company focused on aligning IT assets with business requirements with the goal of reducing cost and improving efficiencies. The major obstacle in accomplishing these goals is all of us – people. We get in the way of ourselves, our egos, our pride and our habits. We come up with great ideas, start a company, and then become successful beyond our capabilities. We try to stay nimble, react to the market/environment, try implement processes so we can scale and grow, and painfully experience our failures. The old ways don’t work with the new business volumes, we can’t see beyond our nose and then – it happens. IT hits the fan.
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