QlikView Review
In-memory allows fast slicing and dicing of data.

Valuable Features:

  • In-memory performance – It allows slicing and dicing of a huge volume of data in the dashboard very fast if designed optimally.
  • Scripting – It provides a flexible data-preparation layer, along with the ability for data integration from multiple data sources. This enables creating a reporting data model inside QlikView from a transactional system without impacting the performance of the transactional system, if designed correctly.

Improvements to My Organization:

Overall, it enabled connecting the entire spectrum of data into a single dashboard in:

  • Finance – connecting sub-ledger txn details all the way to GL
  • Supply Chain

Room for Improvement:

  • Self-service capability is very limited, though it has been improved in QlikSense. However, it will require an additional license & server to set it up.
  • Dashboard capabilities and features are not on par with Tableau, though the same has been attempted in QlikSense. However, Tableau still has better dashboard features.
  • Real-time analysis with live connection (direct discovery) is very limited.
  • The current version is missing a variety of connectors and they need to be procured separately.
  • Not adaptive to display across various screen resolutions

Use of Solution:

I have used this solution for two years.

Deployment Issues:

Initially, there was an issue with LDAP and SSO integration (a compatibility issue with an earlier version of SiteMinder).

Initial setup was non-clustered and we encountered performance issues. It resolved once we moved to better infrastructure in a clustered environment of QlikView.

Technical Support:

Technical support is very geographically oriented, but isn’t truly 24X7.

Initial Setup:

Initial setup was not intuitive, but straightforward for a Qlik admin expert.

Implementation Team:

A vendor team implemented the solution.

Other Solutions Considered:

I evaluated Tableau. However, we selected Qlikview because:

  • Tableau’s current recommendation is to build dashboards directly on top of the reporting DB (for example – data mart or consumption layer) to avoid doing complex logic or transformation inside the tool and using a hybrid approach of live connection and extract. Tableau is currently not an extract-heavy tool. However, with the recent HyPer acquisition, we are expecting some changes.
  • Incremental loading (updates and deletes) inside Tableau is a challenge, which can be achieved very easily in QlikView.
  • Limitation in Tableau on # of columns and rows in table view

Other Advice:

Evaluate visualization tools based on your organization need and appetite to spend on BI technologies overall (DB, etc.)

Disclosure: I am a real user, and this review is based on my own experience and opinions.


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