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«October 2015»

Data Warehouse from the Ground Up at SQL Saturday Orlando, FL on Oct. 10th

SQL Saturday #442SQL Saturday #442 is upon us and yours truly will be presenting in Orlando, Florida on October 10th alongside Mitchell Pearson (b|t). The session is scheduled at 10:35 AM and will last until 11:35 AM. I’m very excited to be presenting at SQL Saturday Orlando this year as it’ll be my first presenting this session in person and my first time speaking at SQL Saturday Orlando! If you haven’t registered yet for this event, you need to do that. This event will be top notch!

My session is called Designing a Data Warehouse from the Ground Up. What if you could approach any business process in your organization and quickly design an effective and optimal dimensional model using a standardized step-by-step method? In this session I’ll discuss the steps required to design a unified dimensional model that is optimized for reporting and follows widely accepted best practices. We’ll also discuss how the design of our dimensional model affects a SQL Server Analysis Services solution and how the choices we make during the data warehouse design phase can make or break our SSAS cubes. You may remember that I did this session a while back for Pragmatic Works via webinar. I’ll be doing the same session at SQL Saturday Orlando but on-prem! ;)

So get signed up for this event now! It’s only 11 days away!

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Create Date Dimension with Fiscal and Time

Here are three scripts that create and Date and Time Dimension and can add the fiscal columns too. First run the Dim Date script first to create the DimDate table. Make sure you change the start date and end date on the script to your preference. Then run the add Fiscal Dates scripts to add the fiscal columns. Make sure you alter the Fiscal script to set the date offset amount. The comments in the script will help you with this.

This zip file contains three SQL scripts.

Create Dim Date

Create Dim Time

Add Fiscal Dates

These will create a Date Dimension table and allow you to run the add fiscal script to add the fiscal columns if you desire. The Create Dim Time will create a time dimension with every second of the day for those that need actual time analysis of your data.

Make sure you set the start date and end date in the create dim date script. Set the dateoffset in the fiscal script.

Download the script here:


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Hierarchy Types in SSAS

  • 22 July 2010
  • Author: kylewalker
  • Number of views: 29503

One of the most powerful tools in the BI stack is the SSAS cube.  The cube is a collection of related dimensions and measures that, once completed, can provide an enormous about of data that can be sliced just about any way you want it...  Oh, and it'll do it just as fast as you can click your mouse.  Now like I said, within a cube there are dimensions.  These are a lot like the ones you'll see in your data warehouse.  A lot of times, within dimension, you'll find hierarchies.  Hierarchies are logical entities that an end user can use to analyze fact data.  These entities can be made of one or multiple levels and can manifest itself in one of three ways: balanced, unbalanced, or ragged.

A balanced hierarchy is one that all of the branches of the hierarchy reach to the same level and each member's parent belongs to the level immediately above it (no gaps in levels).  One common example of a balanced hierarchy can be found in a date dimension.  Here is an illustration of what I'm talking about:

Date Dimension

As you can see, all of the branches reach an equal length and there are no gaps in levels.

The second type of hierarchy is unbalanced.  In an unbalanced hierarchy, all of the branches of the hierarchy don't reach to the same level but each member's parent does belong to the level immediately above it.  One example of this type of hierarchy is an employee hierarchy.  There may be some positions on the same level that don't have direct reports, while others do.  Here is an illustration:

Employee Dimension

The last type of hierarchy is called ragged.  In a ragged hierarchy, each level has a consistent meaning from branch to branch, but one or more branches might have a missing level.  An example of this may be a geography hierarchy, as seen below.

Geography Dimension

I hope this sheds some light on the different types of hierarchies you'll be working with on your next SSAS project.

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