Why Analytics Projects are a Mistake
Before you go and start a new analytics project, consider these sobering statistics. As far back as 2005 Gartner began ringing the warning bells.
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,
Five Reasons Your Data Analyst Can’t Analyze
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
Measuring the Cost of Doing Business With Insufficient Analytics
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
What you should know before you go sailing on the data lake
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
Dimensional Modeling: Introduction
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.
Have you ever fished in a Data Lake?
Why build a data warehouse when you can have _____. Fill in the blank with the latest marketing epiphany.
Early Arriving Facts / Late Arriving Dimensions
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
Top 3 Reasons Why Metadata is Key to Data Warehousing Success
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 is a data warehouse?
What exactly is a data warehouse? Why create a data warehouse? This short video provides non-technical answers that are easily understood by anyone.