During our various consulting assignments, we have come across this question many times. QlikView (QV) is often compared with other traditional BI tools like SAP BO (BO), IBM Cognos (Cognos), Microsoft BI (MSBI), etc.
In this post, I will try to analyse if QV can at all be compared with other BI tools, or it should be used as a complementary tool along with others.
First, let us try to find out if there are some advantages of QV over other traditional BI tools.
- It has been observed that QV enables rapid implementation and hence it takes around 1/6th of the time taken by others. A similar comparison can be drawn on the implementation cost.
- As QV is a user-driven business discovery tool, it just takes around 1/5th of the time to gain proficiency compared to other traditional tools
- Due to fast implementation, the success rate is around 95%. However, others are estimated to have less than 50% success rate.
- Also, the total cost of ownership is estimated to be around 40% or less, in comparison
Now, let us try to find out other high level differences:
- QV is an in memory (RAM) BI tool. Data is loaded in memory and available for instant associative search and real-time analysis with a few clicks. However, the conventional BI tools are based on disk-based memory.
- QV has a unique drill feature which is called Associative Search. While, no such features are available in traditional BI.
- It is also observed that QV is User & Insight Driven. Whereas, the conventional ones are IT and data driven
- Offline Analysis – Once data is refreshed, users can do their analysis offline also. However, this feature is found missing in most of the popular BI tools
Finally, let us see if QV can be considered as a comparable option with other conventional BI tools. We will analyze by looking at the requirements for each category, and also by finding out the implementation procedure differences between them.
- For QV, dashboards, business discovery and online analysis are the primary requirements, catering to the ‘C’ level executives. However, the traditional BI tools are mainly driven by the operational reporting requirements, along with analysis views / dashboards.
- In case of QV, the majority of the users are from the higher level of organization hierarchy. Whereas, the case is totally different for conventional BI tools, with more users at the lower levels of the organization structure.
- The implementation time / cost are not the main priority, when the traditional BI is chosen. However, QV provides a considerable saving.
- For implementation, QV does not require a separate data warehouse (DWH) creation, a separate reporting database, separate ETLs (Extraction, Transformation and Loading) to be written, or separate database software and a DBA (Data base Administrator). This all are required in the other case.
- Though QV does require extra RAM, compared to the conventional BI tools
Thus, looking at the above points we can conclude that QV, in every case, cannot be considered as an option for the traditional BI tools. If one is clear with the requirements and priorities of the organization, it would be easier to decide after going through the above mentioned points.
Also, another point to consider here could be that QV can also be used as a complementary solution, along with the traditional BI. This model is being followed by many companies today and they are able to extract the maximum out of the BI implementation efforts.
So, after my 11 years of IT consulting experience and going through the points as listed above, I think we have the following options:
- QV, or
- SAP BO (or other conventional BI tools), or
Nishi Kant Sharma