To a great extent, the data manipulation layer of our multi-tiered master data services mimics the capabilities of the application services discussed in the previous posting. However, the value of segregating the actual data manipulation from the application-facing API is that the latter can be developed within the consuming application’s
Data profiling is a core technique of data quality management and often the starting point for so many projects these days. Because it’s such a relatively simple technique to apply, it’s easy to overlook some of the more advanced techniques that can take your data profiling to the next level.
With respect to data, there seem to be a few types of companies: Those that do fairly little with the value of their data. I've consulted for quite a few. Those that maximize the value of their data, often controversially. Facebook and Google are squarely in this group. Those that maximize the
In his book Where Good Ideas Come From: The Natural History of Innovation, Steven Johnson explained that “error is not simply a phase you have to suffer through on the way to genius. Error often creates a path that leads you out of your comfortable assumptions. Being right keeps you in
Last time we started to discuss the strategy for applications to transition to using master data services. At the top of our master data services stack, we have the external- or application-facing capabilities. But first, let’s review the lifecycle of data about entities, namely: creating a new entity record, reading
These days there is endless talk about data: how to use it, how to value it, where to get it, how to secure it and when to measure it. Data is pervasive, and it is beginning to influence our society with increasing impact and accelerating velocity. Let’s examine the effect on the
One of the growing trends I’m witnessing when talking to Data Quality Pro’s guest interviewees is the use of federated data quality tactics. The idea is a simple but compelling one. Rather than having a large team that manages data quality across the organisation, you create satellite teams that adopt
While we live in an era of big data, it's folly to claim that all data is accurate. Just because you read something on the internet doesn't make it true. In this post, I'll look at two organizations that are working to increase data accuracy and transparency. I'll spare you
We sometimes describe the potential of big data analytics as letting the data tell its story, casting the data scientist as storyteller. While the journalist has long been a newscaster, in recent years the term data-driven journalism has been adopted to describe the process of using big data analytics to
In the last two series of posts we have been discussing the challenges of application integration with a maturing master data management (MDM) repository and index, and an approach that attempts to easily enable existing applications to incrementally adopt the use of MDM. This approach involves developing a tiered architecture
