These days you can buy some really great analytics software. In the past ten years it has improved dramatically, and today it enables rapid report
Before you go and start a new analytics project, consider these sobering statistics. As far back as 2005 Gartner began ringing the warning bells.
(This is the final part of a three-part series illuminating the challenges of data analytics and describing a proven solution to the problem.) In part one,
In part one of this series, Measuring the Cost of Doing Business with Insufficient Analytics, I referenced a series of studies conducted over the past five
A recent survey conducted by CrowdFlower and summarized on Forbes found data scientists spend most of their time massaging rather than modeling or mining data for
The ”data lake”, a catchy new buzzword in analytics circles, has many people wondering if they still need a data warehouse. You may have heard
Why build a data warehouse when you can have _____. Fill in the blank with the latest marketing epiphany.
Metadata has the power to make or break a data warehouse. Like most innovation, a metadata driven approach to data warehousing solves common challenges by taking the process to a higher level.
We have all seen the job postings. “Immediate hire… ETL developer with 10 years’ experience.” Regardless of fast changing technologies there will be a need
Some of the most challenging data warehousing situations come in the form of external data mashups. Because the term “data mashup” has taken on a