I’ve long had a love affair with the stars. Seeing something so timeless and far reaching puts life in perspective. For as long as I can remember, I’ve been able to identify and appreciate a number of constellations as they run across the night sky. My kids have been able to identify Orion for as…
Month: July 2017
Those Who Don’t Know History Are Doomed to Repeat It…
In our daily work, we’re constantly bombarded with requests for short time periods – rolling 30 days, last month, last quarter, year to date, rolling 13 months, etc. All of these are fine for their defined purposes – reporting. It’s often called Business Intelligence, or Analytics, and there are some pieces of both within these…
…But Those Who Understand History Can Make It Repeat In Their Favor.
Bear with me reader, for this article will be a meandering journey through history – but the ending is relevant to your daily client needs – even if your customer doesn’t know it yet. I often get into debates with people over how much history data is relevant, which I go into detail on in…
Shoot for the Star Schema!
The phrase “Shoot for the stars!” has long been associated with trying to achieve something thought impossible, with the idea that while you may not get all of the way there, by aiming for something grandiose, you will at least achieve more than if you set your goals at something easily accomplished. In more recent…
Because You Know It’s All About the Grain
The most important question to answer when designing a fact table is to determine what the grain of the transaction you wish to record is. Quite literally, it’s all about the base grain. If you select too high of a grain, the you lose your ability to drill down into more detailed analysis. If you…
Just the Facts, Jack!
While we’ve previously discussed the importance of determining the grain of your fact table, we really didn’t cover exactly what data elements should go into the table. One of the reasons much of this site will concentrate on dimensions is because the dimensional data keys are integral to the fact table build. Once you determine the…
I’m Sorry, You’re Just Not My Type 1 Data…
Type 1 data is something you’ll hear frequently when talking about OLTP (OnLine Transactional Processing) systems, and it can be common within a data warehouse as well. What is it? Type 1 data is essentially a permanent “current record” within a dimension. When a change occurs to a dimensional record, the change overwrites the previous…
I’m Looking for More of a Type 2
We covered Type 1 Data in a previous article. So now that you know what Type 1 data is, what is Type 2? Also known as a slowly changing dimension (SCD), Type 2 dimensions simply are dimensional records that represent a unique value at a specific and unique point in time. The key advantage to this…
Rock the Data! 