How do you measure the value of data governance?

Data governance plays an integral role in many enterprise information initiatives, such as data qualitymaster data management and analytics. It requires coordinating a complex combination of factors, including executive sponsorship, funding, decision rights, arbitration of conflicting priorities, policy definition, policy implementation, data stewardship and change management. With so much overhead involved in running a data governance program, it’s essential to be able to measure the value of data governance.

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To stream or not to stream?

man contemplating: to stream or not to streamHadoop may have been the buzzword for the last few years, but streaming seems to be what everyone is talking about these days. Hadoop deals primarily with big data in stationary and batch-based analytics. But modern streaming technologies are aimed at the opposite spectrum, dealing with data in motion and providing analytical insights in flight.

Streaming technologies have been around for a number of years. But recently, the numbers and types of use cases that could take advantage of these technologies has exploded. Today, the question is not really about whether or not to stream. It’s about how to marry new streaming capabilities and approaches with emerging use cases. Read More »

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What's the difference between data governance and data management? (Part 2)

woman looking for a way to define data governanceIn Part 1 of this series, we defined data governance as a framework – something an organization can implement in small pieces. Data management encompasses the disciplines included in the data governance framework. They include the following:

  • Data quality and data profiling.
  • Metadata (business, technical and operational).
  • Data security.
  • Data movement within the enterprise.
  • Data movement/usage outside of the enterprise.
  • Data stewardship or data ownership.
  • Execution of architectures (including data warehousing and big data).
  • Execution of policies and practices set forth in the data governance framework.

I'm sure there are a few more you could add, but this has become quite a large list. Read More »

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What AirBNB teaches us about traditional data governance

With a valuation nearing $30B, AirBNB is a really big deal. The home-sharing service aims to disrupt the traditional hotel industry by letting every Joe and Jane Sixpack turn their homes into de facto temporary lodging.

AirBNB's business model is nothing if not innovative – perhaps too innovative for state and local legislatures. You see, many lodging statutes were conceived decades ago, long before apps and smartphones made anything remotely resembling AirBNB possible. Plenty of established industry types believe that the home-sharing service violates many of these laws. (Faced with significant opposition, AirBNB is upping its lobbying efforts.) Beyond the question of its very legality, the company faces increasing claims that homeowners use the site to discriminate against minority renters. Read More »

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Operational data governance: Who owns data quality problems?

Data integration teams often find themselves in the middle of discussions where the quality of their data outputs are called into question. Without proper governance procedures in place, though, it's hard to address these accusations in a reasonable way. Here's why.

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How I (reluctantly) learned the value of data governance

Data governance must encompass management of the full life cycle of a data policy – its definition, approval, implementation and the means of ensuring its observance

- David Loshin, Data Policies and Data Governance

celebrating the value of data governanceI was checking out my Google stats on Data Quality Pro recently and observed that "How to create a data quality policy" was one of the most popular searches people make. It's easy to understand why.

As you start to mature data quality, you move away from doing isolated cleanups and begin to think about how you can change the wider organisation. Promoting change, even at a departmental level, will require some form of agreed mandate. This need for a template invariably leads to a hunt on the web for how to create a data quality policy.

Policy templates are a useful starting point – but from a data governance perspective, there can be far more value in going down another route.

Let me explain with a true story from my distant past. Read More »

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How do you define data governance?

554391989Data governance has been the topic of many of the recent posts here on the Data Roundtable. And rightfully so, since data governance plays such an integral role in the success of many enterprise information initiatives – such as data qualitymaster data management and analytics.

These posts can help you prepare for discussing data governance at your organization. One of the things I've noticed about a lot of data governance discussions is that they often fail to begin with a good working definition of data governance. A few of my favorites follow.

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What's the difference between data governance and data management? (Part 1)

Lately, the definitions of data governance and data management look very much alike. In this two-part series, we'll define data governance and data management. And we'll see that there's a big difference in the two.

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Should organizations separate analytics governance and data governance?

"Your scientists were so preoccupied with whether or not they could that they didn't stop to think if they should."

—Jeff Goldblum as Dr. Ian Malcolm, Jurassic Park

There's no shortage of content on the web about data governance. A quick Google search of the term reveals more than 450,000 results. On this blog alone you'll find more than 100 posts on this important topic.

But should we think of analytics governance as separate from data governance?

In this post, I'll address this question. Read More »

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Data governance: The perfect marriage of soft and hard skills?

We've witnessed a significant rise in data governance adoption in recent years. Careers, technology, education, frameworks, practitioners – there's growth in all aspects of the discipline.

businessman considering data governance and hard or soft skillsRegulatory compliance across many sectors is a typical driver for data governance. But I also believe one of the main reasons is the realisation by data leaders that they need a broader, over-arching governance framework if they are to deliver on their vision for a mature information strategy.

Of course, delivering these frameworks and change structures is no easy task. In particular, it requires you to first get in touch with the "softer" side of consulting skills.

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