In my previous post, I discussed the characteristics of a strong data strategy, the first of which was that a formal, well-defined strategy exists within your organization. This post discusses how often (and why) your organization’s data strategy needs to be updated. While strategy encompasses and sets the overall direction for
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With data now impacting nearly every business activity, there should no longer be any doubt that data needs to be managed as a strategic corporate asset. This post examines the top five characteristics of a strong data strategy. Existence As I previously blogged, in today’s fast-moving business world now often takes priority
In this two-part series, which posts as the calendar turns to a new year, I revisit the top data management topics of 2015 (Part 1) and then try to predict a few of the data management trends of 2016 (Part 2). Data management in 2016 The Internet of Things (IoT) made significant
In this two-part series, which posts as the calendar prepares to turn 2015 into 2016, I revisit the top data management topics of 2015 (Part 1) and then try to predict a few of the data management trends of 2016 (Part 2). Data management in 2015 Big data continued to make
Time. It flies. It does so whether or not you’re having fun or otherwise putting it to good use. To know where it flies, you’d need to watch. But most of us can’t make the time to watch. How we use time is important since it’s the one resource we
Learn the top 5 reasons for managing data where it lives – whether it's in database or in memory, in the cloud or in-stream.
The Internet of Things (IoT) has become the new It Girl of the IT world. Of course her big brother big data continues to generate big buzz. My sis from another miss Tamara Dull has blogged about the relationship between big data and IoT, positing big data is a subset of IoT on
Jim Harris explains why it's especially important to assess the quality of metadata when it comes to big data.
Jim Harris discusses perspectives on the question of how much quality big data really needs.
Jim Harris addresses some of the most common questions and challenges big data poses for data quality.