- 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.
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.
Customer Service and Technical Support
Technical support is very geographically oriented, but isn’t truly 24X7.
Initial setup was not intuitive, but straightforward for a Qlik admin expert.
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
Evaluate visualization tools based on your organization need and appetite to spend on BI technologies overall (DB, etc.)
Which version of this solution are you currently using?