We often watch new positions sprout up around emerging technology.  These days, we see new titles such as the chief cloud officer, and other titles that seem just as trendy.  However, the strategic use of data within many enterprises led those in charge to assign data management responsibility to one person; the chief data officer or CDO.

I’m not a big fan of creating positions around trends in technology.  Back in the day, we had the chief object officer, chief PC officer, chief Web officers, you name it.  However, data is not a trend.  It’s systemic to what a business is, and thus the focus on managing it better, and centrally, is a positive step.

Adding a CDO to the ranks of IT makes sense.  The analyst firm, IDC, predicts the global big data technology and services market will reach $23.8 billion by 2016, while the cloud and cloud services market is expected to see $100 billion invested in 2014.  We’ve all seen the explosion of data in enterprises, as the use of big data systems begins to take root, including the ability to finally leverage data for a true strategic business advantage.

The arrival of the CDO has a few advantages for larger enterprises.  Appointing a CDO:

  • Sends a clear message to those in IT that data is strategic to corporate leadership, and that they are investing in the proper management and use of that data.
  • Provides a single entity to govern how data is gathered, secured, managed, and analyzed in a holistic manner.  The enterprise will no longer lock data up in silos, controlled by various departments in the company.
  • Provides a common approach to data integration.  The CDO governs most of the data that needs to be governed, as well as how the data flows from place to place to place.

The role of the CDO will be around the strategic use of business data.  Many enterprises will see this instantiated through projects to put the right technology in place, including emerging big-data systems that manage both structured and unstructured data, key analytics systems, and data integration systems to breakdown enterprise silos.

The use of data analytics is most interesting, considering that data analytics is all about understanding data in the context of other data.  When the first generation of data warehouse systems first hit the streets many years ago, the focus was on taking operational data, placing it in another database model, and then slicing and dicing the data to cull out the required information.

When considering traditional approaches to analytics, the data was typically outdated, months or years old in many cases.  Moreover, the approach was to analyze the data itself.  We could analyze operational trends, such as increasing or decreasing sales, but we would not really understand the reasons for those trends.

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Missing was the ability to manage data in the context of other data.  An example would be the ability to analyze sales trends in the context of key economic indicators, or the ability to understand the collation of production efficiency in the context of the average hourly pay of plant workers.  These are where the true data analytics answers exist.  While they are complex and require true data science to find them, the arrival of the CDO means that the true answers will at least be on the corporate radar.

As these strategic analytics systems rise up within many enterprises, perhaps with the rise of the CDO, so does the focus on data integration.  Data integration, like databases themselves, have been around for years and years.  As we concentrate more on what the data means, in the context of other data, then there is a need to bring that data together.

In the past, data integration was considered more a tactical problem, something that was solved in ad-hoc ways using whatever technology seemed to work at the time.  These days, considering the value of the strategic use of data, data integration has got to be a key best practice and enabling technology that allows the enterprise to effectively leverage the data.

In other words, where once there was much less energy around the use of data integration approaches and technology, these days, data integration is caffeinated.  Perhaps that’s due in part to the arrival of people in the organization with both budget and power, who are now charged with managing the data, such as the CDO.

Of course, reorgs and the creation of new positions don’t solve problems.  They just provide the potential to solve problems.  With the arrival of the CDO comes a new set of priorities around the use of data.  Data integration has got to be at least number 1 or 2 on the priority list.

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