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
In my recent posts, I've been exploring the issues of integrating data that originates from beyond the organization. But this post looks at a different facet of extra-enterprise data management: data availability. In many organizations, there's a growing trend of making internal analytical data accessible to external consumers. I can
How many times have you gone onto a website, put a few things in a shopping cart, and then exited the Internet? I do it all the time. Sometimes when I log on to that site during my next visit, those same items are still in my cart – ready for purchase. I find
Jeff Stander passes along some of the lessons he's learned about third-party metadata collection.
In two previous posts (Part 1 and Part 2), I explored some of the challenges of managing data beyond enterprise boundaries. These posts focused on issues around managing and governing extra-enterprise data. Let’s focus a bit on one specific challenge now – satisfying the need for business users to rapidly ingest new data sources. Sophisticated business
Most people have logged on to a social media site, maybe to look up an old friend, acquaintance or family member. Some people play games, or post funny pictures or other information they want to share with everyone. Do you ever ask yourself what happens with this information? What if your business wanted to purchase this information and
In 2014, big data was on everyone’s mind. So in 2015, I expected to see data quality initiatives make a major shift toward big data. But I was surprised by a completely new requirement for data quality, which proves that the world is not all about big data – not
Twenty-five years ago (when I was 12 years old), we realized that data, across the corporation, was not integrated. Nor did our data let us predict the future by looking at the past. So we started creating these stores of historical data soon to be called “data warehouse.” Here are
Confusion is one of the big challenges companies experience when defining the data governance function – particularly among the technical community. I recently came across a profile on LinkedIn for a senior data governance practitioner at an insurance firm. His profile typified this challenge. He cited his duties as: Responsible for the collection
In a recent post, we discussed a number of factors that have expanded the reach of organizations' data management functions beyond the traditional scope of an in-house data center. Increased use of external data sources coupled with growing dependence on cloud computing have created an emerging need to exercise some level
