Having worked with decision support software since the mid 1970s, both as a user and as a vendor, I had been very disappointed by the shallowness of the coverage of OLAP by industry analysts. Most had never even used an OLAP tool and they seemed to be more concerned with checklists of often-irrelevant, vendor-promoted features than how products really worked and what they were capable of doing for users. It seemed to me that this was the equivalent of a motoring magazine written by non-drivers, and no more useful. I was also concerned that vendor-sponsored ‘research’ documents seemed to be too prevalent then, as now.

Unlike most other information resources, the OLAP Report consciously maintains its independence by staying away from any kind of vendor sponsorship and advertisements. It is entirely funded through subscriptions, and if you are buying it you will find it worth its price.

A not-to-be-missed article on The OLAP Report website is “How not to buy an OLAP Product” that offers excellent advice on the planning and purchase of an OLAP solution.

The consequences of a bad decision either mean millions sunk into a complete failure, or even more dangerously: the project being declared a “success” due to political compulsions without any tangible business benefits. The latter is a fairly common scenario because heads would roll if anyone were to acknowledge a multi-million dollar goof up. So the farce goes on, and the vendor keeps earning their annual licensing revenues, just because the CxO is too scared to acknowledge that the king is naked.

The keys to a successful OLAP evaluation are:

• Evidence-based selection criteria: You need to have some measurable and demonstrable criteria for making the selection.
• An understanding of user needs (instead of OLAP as a fashion statement)
• Managing vendor distractions: You cannot let the vendor drive the evaluation and tell you what your selection criteria ought to be. “Projects where the vendors’ excellent sales efforts were a major factor in product selection were among those that achieved the least in business terms.”
• Checking Reference Sites: Not all the “references” may be happy/satisfied customers. Some actually are extremely unhappy, just that they cannot say it without looking dumb and losing their jobs
• Understanding Financial & Licensing Issues: “Remember that OLAP software license fees are only a small proportion of the total costs of a project.” Yes, commercial OLAP TCO goes into multi-million dollars.
• Bake-off or Proof of concept: Extremely important for comparing shortlisted vendors on a small project. But make sure that the POC does not get just patched up into the final system!!

If you are planning to implement a commercial OLAP solution, don’t forget to read The OLAP Report: How not to buy an OLAP product.

Or you can get an open source OLAP at a ridiculously low ownership cost. (See posts Open Source OLAP – Part I, and Part II)

Need help? Drop a comment and we could do something together.

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In this post we would be setting up OLAP reporting for a hypothetical retailer called FoodMart that sells various grocery products in a chain of stores across US, Canada, and Mexico.

Assuming that you are running MS Windows on your machine, we would need:

JDK 1.4.2 or above downloadable from Sun’s java download page (I used j2sdk1.4.2)

Microsoft Access to act as the data store (drop a comment if you do not have MS-Access and I can provide detailed instructions on setting it up on another database such as MySQL)

Tomcat 5 from apache.org. Go to the bottom and download Windows Binary Distribution (I am using jakarta-tomcat-5.0.28.exe).

Mondrian along with FoodMart data from sourceforge.net

So now that you have downloaded all the software required, we can go about setting things up.

Install JDK (say in c:\j2sdk1.4.2). This may require you to reboot your machine a couple of times. Do not install Tomcat yet.

Right click on My Computer, select Properties -> Advanced -> Environment Variables. Create a new environment variable JAVA_HOME and point it to your JDK instalation (c:\j2sdk1.4.2)

Now install Tomcat (say in C:\Program Files\Apache Software Foundation\Tomcat 5.0). It should get installed as a service.

Go to Control Panel -> Administrative Tools -> Services to check if Tomcat5 service is running. If not, start the service.

Unzip Mondrian2.0.1.zip somewhere (say C:\Mondrian). Copy mondrian.war file from C:\Mondrian\mondrian-2.0.1\lib folder and place it in the webapps folder of your tomcat installation (C:\Program Files\Apache Software Foundation\Tomcat 5.0\webapps).

Within the unzipped Mondrian (in demo/access folder), you fill find a MS Access database file called MondrianFoodMart.mdb. This is where the data is going to get picked up from once we create a ODBC DSN.

Go to Control Panel -> Administrative Tools -> Data Sources (ODBC) -> System DSN. Create a new ODBC DSN called ModrianFoodMart pointing to the MondrianFoodMart.mdb above. Make sure you get this step correct (drop a comment if you need help).

Okay, now time to go see the brand new reports by pointing your browser to http://localhost:8080/mondrian/. If everything has gone right, you should see a page with a couple of links there. Click the first link called “JPivot pivot tables” under the heading “Mondrian Examples”. You will see a nice little report showing Unit Sales, Store Cost, and Store Sales for our FoodMart.

The user-interface is quite intuitive, so play around by clicking on various buttons. Do not forget to try out the top-left button (OLAP Navigator) that allows you to define your own reports by selecting measures, rows, columns and filters.

Have a go. And do let me know.

The OLAP Reporting revolves around two simple concepts: Dimensions, and Measures.

A Measure is any business metric that you want to calculate and report on. It can range from simple stuff like Dollar Sales (total sales revenue), Unit Sales (no of units for a particular product sold), Profits, Current Inventory Level, etc. to more complicated computed fields like Average Cost, Average Profit per Unit, % Margin, etc.

It should be noted that a Measure can have different values depending upon the context – whether you are looking at All Locations or a particular City, or whether you are looking at annual figures or weekly figures, or daily figures, whether you are looking at a particular demographic segment, etc. A measure’s value depends upon the specific subset of the entire database that you are looking at (hence the term “slice-and-dice” commonly used with “cubes”). The specific context for the calculation of Measures is provided by Dimensions.

Dimensions help subset the database to get to the specific information you are interested in. You may want to subset by Geography, Time, Product/Service Offering, Customer Demographics, etc. For example, I may want to analyze Unit Sales (Measure) for a particular product (specified on Product Dimension) in New York (specified on Geography Dimension) for the month of Jan 2006 (Time Dimension). I could then drill-down on Time Dimension to get the daily sales for the product.

OLAP tools provide this functionality through a user friendly GUI. The commercial OLAP systems are extremely expensive, but that would change with the advent of open-source OLAP tools.

An excellent open-source OLAP server is Mondrian that allows you to do OLAP cube reporting through a JSP web-based interface called JPivot.

The two together provide an excellent reporting system that can be quickly deployed on an existing datawarehouse to deliver impressive reports to end users.

In the next post we will set up a quick reporting system using Mondrian, JPivot, Tomcat and MySQL/MS-Access.