Post: A Review of Author Sanjeev Datta’s IBM Cognos Insight

IBM Cognos Insight, by Sanjeev Datta.  Published 2012 by Packt Publishing.

IBM Cognos Insight by Sanjeev Datta Over the past couple of days, I have had the pleasure to review IBM Cognos Insight by Sanjeev Datta of PerformanceG2.  I was very excited to learn of this book, not only because I wanted a better understanding of Cognos Insight software, but also because Sanjeev Datta is clearly one of the thought leaders in Business Analytics.  So I picked up the book with exceedingly high expectations, and I laid it down with no disappointments. Datta’s IBM Cognos Insight is a very clear and concise jump start to utilizing Cognos Insight software.  I don’t recall ever before reading a technical book that spans a mere 120 pages, yet still manages to fully meet its stated purpose.  It is impressive, and Mr. Datta should be proud of this accomplishment.

IBM describes Cognos Insight as, “a personal analytics solution that empowers users to independently explore, analyze, visualize and share data without relying on IT for assistance.”  It is clear that IBM is targeting this product at the sophisticated business analyst.  It is also clear that some modest instruction on the tool will yield a high ROI for these users. This book provides that instruction for these business users and ensures that they can use this tool in an effective manner.

The book opens with a quick introduction to business analytics and specifically the IBM Cognos product portfolio, but the author does not dally in this area or get drawn into an extended discussion of the overall business analytics landscape.  He does explain how (and why) Cognos Insight fits into IBM’s product tapestry.  The following chapter walks the reader through the various flavors of Cognos Insight (personal edition versus standard edition) and how to download and install Cognos Insight.

The main meat of the book starts in chapter three.  Chapter three is a tutorial on navigation and usability.  Here Datta does a very nice job of weaving a few basic OLAP concepts into a simple instructional manual on how to use Cognos Insight which should make Cognos Insight accessible to all users regardless of background.  The chapter is stuffed with screenshots and examples; hence, it is very easy to follow and like the rest of the book is a very quick read.

Chapter four is my personal favorite.  Here Datta uses an example dataset (provided with the book) and walks his reader through doing a full analysis for a hypothetical company.  He shows how to use Cognos Insight to reach strategic decisions for the business.  I am hesitant to substitute my judgment for the author’s, but I would suggest you read this chapter before chapter 3.  Many readers may be able to skim chapter one, use chapter two to get Cognos Insight installed, and then jump into chapter 4.  This would provide an exceedingly fast start on the tool.  You could then return to chapter three to round out your knowledge.

Datta closes with a nice discussion on how to use Cognos Insight in an enterprise environment.  He shows how to use the “personal analytics” tool to collaborate with others and how to integrate it with other tools in the Cognos lineup.  This knowledge will be essential to anyone working in a large corporate environment, but I would save it until you have exhausted the learning from chapters three and four.

As I said in the open, I think this is an excellent work. If you are providing Cognos Insight to your business analysts, you should seriously consider providing this book as well.

You can purchase IBM Cognos Insight at http://www.packtpub.com/ibm-cognos-insight/book. Follow Sanjeev on twitter https://twitter.com/1dsanjeev.

Scroll to Top
As the BI space evolves, organizations must take into account the bottom line of amassing analytics assets.
The more assets you have, the greater the cost to your business. There are the hard costs of keeping redundant assets, i.e., cloud or server capacity. Accumulating multiple versions of the same visualization not only takes up space, but BI vendors are moving to capacity pricing. Companies now pay more if you have more dashboards, apps, and reports. Earlier, we spoke about dependencies. Keeping redundant assets increases the number of dependencies and therefore the complexity. This comes with a price tag.
The implications of asset failures differ, and the business’s repercussions can be minimal or drastic.
Different industries have distinct regulatory requirements to meet. The impact may be minimal if a report for an end-of-year close has a mislabeled column that the sales or marketing department uses, On the other hand, if a healthcare or financial report does not meet the needs of a HIPPA or SOX compliance report, the company and its C-level suite may face severe penalties and reputational damage. Another example is a report that is shared externally. During an update of the report specs, the low-level security was incorrectly applied, which caused people to have access to personal information.
The complexity of assets influences their likelihood of encountering issues.
The last thing a business wants is for a report or app to fail at a crucial moment. If you know the report is complex and has a lot of dependencies, then the probability of failure caused by IT changes is high. That means a change request should be taken into account. Dependency graphs become important. If it is a straightforward sales report that tells notes by salesperson by account, any changes made do not have the same impact on the report, even if it fails. BI operations should treat these reports differently during change.
Not all reports and dashboards fail the same; some reports may lag, definitions might change, or data accuracy and relevance could wane. Understanding these variations aids in better risk anticipation.

Marketing uses several reports for its campaigns – standard analytic assets often delivered through marketing tools. Finance has very complex reports converted from Excel to BI tools while incorporating different consolidation rules. The marketing reports have a different failure mode than the financial reports. They, therefore, need to be managed differently.

It’s time for the company’s monthly business review. The marketing department proceeds to report on leads acquired per salesperson. Unfortunately, half the team has left the organization, and the data fails to load accurately. While this is an inconvenience for the marketing group, it isn’t detrimental to the business. However, a failure in financial reporting for a human resource consulting firm with 1000s contractors that contains critical and complex calculations about sickness, fees, hours, etc, has major implications and needs to be managed differently.

Acknowledging that assets transition through distinct phases allows for effective management decisions at each stage. As new visualizations are released, the information leads to broad use and adoption.
Think back to the start of the pandemic. COVID dashboards were quickly put together and released to the business, showing pertinent information: how the virus spreads, demographics affected the business and risks, etc. At the time, it was relevant and served its purpose. As we moved past the pandemic, COVID-specific information became obsolete, and reporting is integrated into regular HR reporting.
Reports and dashboards are crafted to deliver valuable insights for stakeholders. Over time, though, the worth of assets changes.
When a company opens its first store in a certain area, there are many elements it needs to understand – other stores in the area, traffic patterns, pricing of products, what products to sell, etc. Once the store is operational for some time, specifics are not as important, and it can adopt the standard reporting. The tailor-made analytic assets become irrelevant and no longer add value to the store manager.