Does it upset you when you log onto your healthcare insurance portal and find that they spelled your name wrong, have your dependents listed incorrectly or your address is not correct? Well, it's definitely not a warm fuzzy feeling for me! After working for many years in the healthcare, pharmaceutical and
I'm frequently asked: "What causes poor data quality?" There are, of course, many culprits: Lack of a data culture. Poor management attitude. Insufficient training. Incorrect reward structure. But there is one reason that is common to all organizations – poor data architecture.
Many data quality issues are a result of the distance separating data from the real-world object or entity it attempts to describe. This is the case with master data, which describes parties, products, locations and assets. Customer (one of the roles within party) master data quality issues are rife with examples, especially
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
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
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
I am currently cycling through a schema-on-read data modeling process on a specific task for one of my clients. I have been presented with a data set and have been asked to consider how that data can be best analyzed using a graph-based data management system. My process is to
Yes. But since this post needs to be more than a one-word answer to its title, allow me to elaborate. Data governance (DG) enters into the discussion of all enterprise information initiatives. Whether or not DG should be the opening salvo of these discussions is akin to asking whether the
I've been in many bands over the years- from rock to jazz to orchestra - and each brings with it a different maturity, skill level, attitude, and challenge. Rock is arguably the easiest (and the most fun!) to play, as it involves the least members, lowest skill level, a goodly amount of drama, and the
