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Lyndsay Wise

Hi and welcome to my blog! I look forward to bringing you weekly posts about what is happening in the world of BI, CDI and marketing performance management.

About the author >

Lyndsay is the President and Founder of WiseAnalytics, an independent analyst firm specializing in business intelligence, master data management and unstructured data. For more than seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay conducts regular research studies, consults, writes articles and speaks about improving the value of business intelligence within organizations. She can be reached at lwise@wiseanalytics.com.

Editor's Note: More articles and resources are available in Lyndsay's BeyeNETWORK Expert Channel. Be sure to visit today!

More solution providers are starting to integrate the concept of governed data discovery into their product offerings. After years of trying to adopt data governance initiatives as part of a larger data management framework within organizations, software vendors are integrating similar capabilities into their solutions. The reality, however, isn’t as simple. Organizations need to understand what governance within the framework of data discovery or business intelligence means to make informed decisions in relation to software selection and solution design. Sometimes organizations think that governed data access is a blanketed statement that will apply to all of their analytics use. The reality, however, can be much different.

In most cases, governed data access refers to information accessed within a managed database or set of data sources. This means that governed data access refers to data accessed within specific sources that are part of the solution provider’s offering, but that data accessed externally falls outside the parameters of data governance. Some of the challenges of this for organizations are as follows:

  • providing flexible data access to broader users while controlling data validity
  • ensuring users understand the differences between types of data being accessed
  • limiting access to governed sources
  • developing an iterative framework to manage data quality
  • providing access points and processes surrounding non-governed data sources
  • letting different types of users interact with all the data they require
  • All of these challenges also provide organizations the opportunity to identify the best way to govern their data. Without governed data access points, it becomes hard for users to trust their analytics. Without trust in data it becomes almost impossible to identify whether metrics are accurate. And in many cases, people know that they can’t trust the data they are accessing so don’t want to use their BI tools. This exists whether the tool is Excel or some advanced BI tool, unless data governance exists.

    Because more organizations are starting to quantify the benefits of their data assets, the value proposition of data governance has increased. Therefore, the bundled solutions that include governed data can help organizations achieve quicker implementation times with valid data. The only issue to consider is whether there will be data sources needed for regular analytics that will continue to reside external to the governed sources. Overall, organizations need to understand this to ensure they can evaluate solutions with an understanding of how data will be managed over time.

    This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.


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    Posted October 14, 2014 8:02 PM
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