The Data Roundtable
A community of data management expertsDon't be shy! Interviewing people BEFORE or AFTER a facilitated session just takes a bit of confidence, and good preparation. Building your confidence gets easier and easier the more you participate in interviews. The objective is to prepare and not waste anyone’s valuable time. I like to prepare notes based on
Many managers still perceive data quality projects to be a technical endeavour. Data being the domain of IT and therefore an initiative that can be mapped out on a traditional project plan with well-defined exit criteria and a clear statement of requirements. I used to believe this myth too. Coming
![Non-geeks want to know: will Hadoop mess up my data warehouse ecosystem?](https://blogs.sas.com/content/datamanagement/files/2014/11/Technology_Usage_Trend.png)
Hadoop recently turned eight years old, but it was only 3-4 years ago that Hadoop really started gaining traction. It had many of us “older” BI/DW folks scratching our heads wondering what Hadoop was up to and if our tried-and-true enterprise data warehouse (EDW) ecosystems were in jeopardy. You didn't
![What is reference data? What is reference data? IT person works from laptop.](https://blogs.sas.com/content/datamanagement/files/2014/07/614409740-702x336.jpg)
David Loshin defines reference data and sets up a working definition for his next set of posts.
![A simple technique for improving data accuracy Businessman appears happy that he has been able to improve data accuracy](https://blogs.sas.com/content/datamanagement/files/2014/02/565888093-702x336.jpg)
Dylan Jones says one way to improve data accuracy is to increase the frequency and quality of reality checks.
![Why can’t we predict the weather? Child looking at a storm on a tablet](https://blogs.sas.com/content/datamanagement/files/2013/12/137546680-702x336.jpg)
This is the time of year when we like to make predictions about the upcoming year. Although I am optimistic about the potential of predictive analytics in the era of big data, I am also realistic about the nature of predictability regardless of how much data is used. For example, in