QlikTech’s QlikView reporting and analysis tool is among a new class of Business Intelligence (BI) software tools. As Ben Harden reported in a recent blog post, BI vendors like SAP, Microsoft, and IBM have traditionally sold “to the IT enterprise, but companies like QlikTech and Tableau are targeting the business and bypassing IT. Their tools are quicker to stand up, more intuitive and don’t need the configuration, support, and hardware that the bigger players require.”

A Quick Overview

At first look QlikView is fairly accessible to those experienced with BI tools. A “.qvw” QlikView file contains three classes of user-facing components: a script-based data integration language that runs when the user requests a “reload”, a data modeling component that looks deceptively like a relational data modeling tool, and a familiar array of data visualizations: graphics, charts, lists, etc.

I’ve recently posted a couple of articles at this site on data quality, this is the final one in a series of three.  Previous posts presented these ideas:

• Yes, there is a business case for improving data quality, and we’ve got business value examples. If you look for real money where you anecdotally know there are data quality problems, you’ll likely find it in high costs of data correction and rework, and savings related to business process improvements that reliable data enables.
• There are distinct things an organization can do to reap benefits of improved data management and data quality.  (1) Get started in the first place, (2) find the tangible benefits, (3) cross the departmental silos that exist in every large organization, and (4) promote sound data management practices.
• Impacts of poor data quality can seem abstract in a large organization. They aren’t for a small business owner.  Say you have a carpet cleaning business.  What if you knew 10% of your customer bills were wrong, but you weren’t sure by how much or in which direction?  First you’d panic. Then you’d rush to fix the problem.