
The Key to Analytics That Everyone Should Understand
(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,
(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
What is a dimensional model? What is a data warehouse? This video introduces dimensional modeling while setting the stage for the series of dimensional modeling training videos to follow.
Why build a data warehouse when you can have _____. Fill in the blank with the latest marketing epiphany.
A resilient ETL process deals with data quality issues without causing a process failure while also meeting business requirements. One issue that should be anticipated
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.
What exactly is a data warehouse? Why create a data warehouse? This short video provides non-technical answers that are easily understood by anyone.
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
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