Category: IT
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Leader’s Data Manifesto at #EDW19: Building a Foundation for Data Science
It’s been a truism that data is a resource, but to prove it you just have to follow the money. As the illustration shows, the vast majority of corporate market value draws from intangible assets. Just as money is an abstraction that represents wealth, data is an abstraction that represents these intangible assets. It’s year…
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Enterprise Data Prep for Analytics: Two Principles
Data scientists spend most of their time doing data integration rather than gathering insights. In my interview with data scientist Yan Li, she said that data collection and prep takes at least 70% of her time. Obviously, there’s a lot of integration work to do on data that’s new to analytics efforts, but not every…
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Anonymize Data for Better Executive Analytics
Reading articles about data anonymization makes it clear that it is not an entirely effective security measure (here and here), but still part of a robust security capability, and required if your organization is affected by GDPR. (I use “anonymization” as a general term encompassing techniques that de-identify personal data within a given data set.) But there’s a positive…
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Toward an Analytics Code of Ethics
In data management and analytics, we often focus on correcting apparent inability and unwillingness on the part of business leaders to effectively gather and capitalize on data resources. With that perspective, we often see ethics as a side issue difficult to prioritize given the scale and persistence of our other challenges. At least that was…
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Data Integration Benefits? They’re Obvious.
“At least 84 percent of consumers across all industries say their experiences using digital tools and services fall short of expectations.”* That quote headed a recent article by David Roe on the role of data integration in digital workplace apps. However, the opening quote reflects the pervasive dearth of integrated data among the companies most of…
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Meaningful Requirements Start Successful Data Projects
To me, development projects fail or succeed in the first few weeks. Once a project starts off in the wrong direction, momentum and expectations tend to prevent a return to the proper path. With today’s wealth of database options each addressing exciting new possibilities, the right choice for the application’s data foundation plays a large…
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Start Data Quality Improvements with a New Definition
What is Data Quality anyway? If you are a data professional, I’m sure someone from outside our field has asked you that question, and if you’re like me you’ve fallen into the trap of answering in data-speak. To my listener, I’d guess that the experience was similar to having a customer service rep who has just…
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Sound Data Culture Enables Modern Data Architectures
Modern data architectures, by enabling data analytics insights, promise to drive order of magnitude value gains across many business sectors (here, here, and here). Not so long ago, big data presented a daunting challenge. Although tools were plentiful, we struggled to conceptualize the architecture and organization within which to capitalize on those tools. Now solid…
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Fixing Tableau Desktop Blue Screen or Unresponsive
Tableau desktop (10.2.2 on Windows 7 at work) was consistently locking up my computer or causing a BSOD when I tried to start it. After struggling for a while trying to solve the problem, I found out it was because it used all resources when opening the log file, which had over time grown to…
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The PDDQ Framework: Lean Data Quality for Patient Records
For most of us it may have slipped under the radar, but in December a groundbreaking Patient Demographic Data Quality framework was jointly released by a US government agency and the CMMI Institute. In response to findings that many “safety-related events were caused by or related to incorrect patient identification”, the Office of the National Coordinator…