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Avalon Consulting 2016 Prediction: Data Governance in the World of Cloud and Big Data

Virtualization and Cloud executives share their predictions for 2016.  Read them in this VMblog.com series exclusive.

Contributed by Wayne Applebaum, Vice President of Analytics; Applied Innovation at Avalon Consulting, LLC

Data Governance in the World of Cloud and Big Data

The Gartner Group published a study last year that stated:

"... by 2017,  33 percent of Fortune 100 organizations will experience an information crisis, due to their inability to effectively value, govern and trust their enterprise information."

Gartner cites the cause of this crisis as the ever-increasing amount of data that is being collected, stored and analyzed.

People want their information sources to resemble a utility; turn the tap and the water flows. No need to worry about which source the water came from, the pipes that carried it to you or the treatment plant it went through. The water provided is reliably assumed to be from a trusted source. But in terms of information utility, we are not quite there yet when it comes to reliably assuming it comes from a trusted source.

Gartner is correctly describing a situation that has been brewing for the past 15-20 years-a situation that is now accelerating because of Big Data and the Cloud technologies.  In the case of Big Data, we are storing and sourcing a wider variety of information. It is also information that may have go through a number of transformations. Think about what we have to do to score tweets for customer sentiment analysis. The scoring rules we create to accomplish this determine the results we will get.  If two groups create different scoring rules for the same phenomenon, then their results will not be comparable. If there is a desire to compare results across products or time periods, then consistency is a necessary component.

Data Governance needs to play a role in providing this consistency and helping us achieve that "utility" state.  Maintaining consistency of definition and metadata becomes more difficult when users are integrating this information with other data sources.

While the cloud adds to accessibility, it also creates a more difficult data governance situation. Logically, no matter how seamless it may appear to the user, the more sources, locations and access, the more difficult it is to control.

A key issue is you have to control security, access, metadata and life cycle across multiple systems. Information needs to be compatible across systems. As analytics need continue to grow, so will the need to integrate data across systems to get the business insight we are seeking.

While some of these issues can be solved by technology, many are highly "people dependent." For example, while technology can be used to enforce practices, standards and definitions, we still need people to agree on consistent definitions, transformations and calculations that form the basis for any effective data governance efforts.

Even without big data and cloud technologies, it is not unusual to find organizations with multiple data sources that may contain different definitions of basic things like revenue, customer, sales and fulfillment rate. Plus companies routinely extract information from enterprise data sources and manipulate them in Excel spreadsheets. At this stage data governance goes out the window.

When we add to that Big Data and Cloud to the mix, we are taxing our traditional governance constructs. One of the primary reasons is that data governance has evolved in a world that focused on two types of data: Transactional and Master. Implementers of ERP systems focus of these two types of data almost exclusively.

The game changes when instead of just wanting to process transactions (such as orders, payments, payroll) we want to consolidate and analyze transactional information to make better business decisions.

Business Decision data results from the combination of transactional and master-data and outside data to answer business questions like "what is a products contribution margin (which may have to access current commodity prices)?"

Business Decision data could also be the customer sentiment about a given product created from consolidating tweets.  In short, any time we combine data to create new information we are creating Business Decision Data.

The calculations and algorithms that are employed to create this type of data often go undocumented. As the number of big data and analytics projects increases, so does the amount of business decision data, accelerating the problem.

With the Cloud and Big Data, we need to consider data governance in terms of some new conditions that have resulted from the Big Data movement:

  • Data now comes in a wider variety of different forms and sources
  • It may be stored in various locations, some outside the firewall or control of the organization using it.
  • Business Decision Data, and Big Data Transformations create new Data Governance Challenges.

While there are some groups like the Cloud Security Alliance that are in the process of establishing standards for Data Governance in a Cloud Environment,  this remains a relatively new area that is being tackled in the standards arena.   Developing ways of leveraging repeatable methods to implement data governance in the world of the cloud and Big Data will be a key for the competitiveness of your enterprise in the future.  This is a critical topic I work with on a daily basis with my clients, and I'm encouraged by the attention it is receiving. There is much work to be done still, but the future is bright for those who truly embrace Data Governance in this context.

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About the Author

Wayne Applebaum, Vice President of Analytics & Applied Innovation at Avalon Consulting, LLC

Wayne Applebaum is Avalon Consulting, LLCs Vice President of Analytics and Applied Innovation. He is responsible for delivery of Avalon's Analytics Services as well as its Big Data, Search and Semantics practices. He has more than thirty years of experience in data analytics and enterprise consulting. Prior to joining Avalon, Dr. Applebaum was a Principal Business Architect at SAP, responsible for designing and leading the implementation of analytic solutions. Dr. Applebaum holds an MA and Ph.D. in Statistics from the University of Pittsburgh; he earned a Bachelor of Science in Psychology from The City College of New York.

About Avalon Consulting, LLC

Avalon Consulting, LLC transforms data investments into actionable business results through the visioning and implementation of Big Data, Web Presence, Content Publishing, and Enterprise Search solutions. We are the trusted partner to over one hundred clients, primarily Global 2000 companies, public agencies, and institutions of higher learning. Avalon is known for providing clients a superior engagement experience through a combination of business acumen, intellectual curiosity, collaborative work style, and strong partnerships with award-winning vendors. Avalon's deep technical expertise mitigates project risk and reduces total cost of ownership for our clients. Headquartered in Plano, Texas, Avalon also maintains offices in Austin, Texas; Boulder, Colorado; Chicago, Illinois; Minneapolis, Minnesota; St. Louis, Missouri and Washington, D.C. For more information, please visit www.avalonconsult.com.

Published Thursday, October 22, 2015 8:01 AM by David Marshall
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