In his pithy style, Seth Godin’s recent blog post Analytics without action said more in 32 words than most posts say in 320 words or most white papers say in 3200 words. (For those counting along, my opening sentence alone used 32 words). Godin’s blog post, in its entirety, stated: “Don’t measure
A lot of data quality projects kick off in the quest for root-cause discovery. Sometimes they’ll get lucky and find a coding error or some data entry ‘finger flubs’ that are the culprit. Of course, data quality tools can help a great deal in speeding up this process by automating
My previous post explained how confirmation bias can prevent you from behaving like the natural data scientist you like to imagine you are by driving your decision making toward data that confirms your existing beliefs. This post tells the story of another cognitive bias that works against data science. Consider the following scenario: Company-wide
What kind of security do we need for this conversion? In fact, where are the security people? Including security personnel upfront in any conversion project can sure save some time and heartache later. It is important to include security for the following: Source system access – You must be able
Data profiling is essential. So why do so many data quality teams fail to get the most out of this crucial technique? In my short video, you’ll discover the answers to unlocking the full potential of your data profiling efforts. By broadening and deepening your knowledge of data profiling with
Nowadays we hear a lot about how important it is that we are data-driven in our decision-making. We also hear a lot of criticism aimed at those that are driven more by intuition than data. Like most things in life, however, there’s a big difference between theory and practice. It’s
Working from home confers significant benefits. Two of my favorites are a two-second commute and the ability to take afternoon naps without offending judgmental coworkers. Among the drawbacks, though: I'm not going to randomly meet someone at the office. Like many single professionals, I have dabbled in the world of
Many people, myself included, occasionally complain about how noisy big data has made our world. While it is true that big data does broadcast more signal, not just more noise, we are not always able to tell the difference. Sometimes what sounds like meaningless background static is actually a big insight. Other times
Why do so many data migration projects fall off the rails? I’ve been asked this question a lot and whilst there are lots of reasons, perhaps the most common is a bias towards finding the wrong kind of data quality gaps. Projects often tear off at breakneck speed, validating and cleansing
Over the course of the last eight years, I've interviewed countless data quality leaders and learned so much about the common mistakes and failures they've witnessed in past projects. In this post I wanted to highlight five of the common issues and give some practical ideas for resolving them: #1: Not connecting
