Anyone who evaluates data using well-known visual analytics tools such as Tableau or Qlik Sense wants to create, quickly reach the limits of applications — at the latest as soon as he works with unstructured or incomplete data sets. To avoid frustration, we tested both tools for their data preparation options and created a short list of best practices.
How much does it cost me to use the tool? Who should work with it: marketeers or IT professionals? And can I also manage my data in the cloud? Many factors play a role in choosing the right tool for visual analytics. b.telligent consultant Daniel Erlhöfer explains the technical side of Tableau and Qlik Sense in this blog post: What are the differences in the data preparation of both tools?
Tableau is the solution for users who want quick results without a long learning period.
The basis of every visualization in Tableau is a consolidated data table. This is either obtained directly from a data source or generated from tables of one or more data sources using basic data modeling functionality. Tableau offers a variety of interfaces to connect data sources, modeling is semi-automated, and additional columns can be calculated using an SQL-like scripting language.
But anyone who hopes to be able to create extensive data models with complex calculation logic in Tableau will not be happy with the tool. Both interaction with the tool and its functionality quickly reach their limits. Tableau is most effective when a few and well-structured data tables are to be connected and evaluated without in-depth technical knowledge. However, for all other purposes, Tableau offers the ETL solution Tableau Prep on.
If you only need ETL logic to process data for Tableau: Yes. By adding Tableau Prep to Tableau, many weaknesses in the area of data preparation are addressed. With its appealing user interface, Tableau Prep enables even novice users to transform data sets. In terms of available program interfaces, processing logic and user-friendliness, the product is very successful. By additionally using Tableau Server, automated data processes can be set up and rules defined for access to the resulting data sources in a short period of time.
However, care should be taken here too, as Tableau Prep offers full-fledged ETL functionality, but was not designed as an isolated ETL solution. The generated data sets are only output in file form or as a data source for Tableau. In effect, only those ETL processes that serve as preparation for data processing in Tableau can be covered.
Qlik Sense is the first choice for professional users; with a bit of technical knowledge, larger projects can also be tackled.
Just like in Tableau, data preparation in Qlik Sense is done by connecting external data sources. Here, too, it is a prerequisite that the data is available in tabular form. The user is free to design the data load via the user interface or a script. Qlik Sense offers a comparatively wide range of options for designing the internal data model according to your own needs, which means that even more extensive projects can be implemented.
Getting started with Qlik Sense takes a bit more time; this also provides professional users in particular with more functionality and control. However, Qlik Sense is also limited when it comes to turning insufficiently structured data sets into a processable form. The tool is therefore ideal for implementing larger data models and more complex custom calculations.
If you already have well-structured data sets, you won't be disappointed with the tools available in Tableau and Qlik Sense. If such data sets are not available or if the connection of further, previously unknown data sources is planned, integration can be very complex in individual cases. A careful review of the database is always appropriate.
Of course, other aspects also play a role when looking for the right visualization tool. Factors such as appearance, user experience and costs, for example, are relevant to a decision. However, existing experience with the respective tool should also be taken into account. In fact, it has been shown time and time again that a variety of small or major problems arise during implementation and during operation. An employee familiar with the system environment and the tool should not be underestimated in such cases!
In summary, Tableau is ideal for simple and visually appealing analyses that are based on up to ten tables. With the additional purchase of Tableau Prep and Tableau Server, it is sometimes possible to create very extensive environments, including automatic data loading. Qlik Sense can also be used to handle complex modeling tasks without the need for additional licenses. However, comprehensive ETL logic must be dispensed with. If you don't just want to prepare data for use in a visual analytics tool, you should therefore consider using an independent data hub and process your data separately from the data visualization.
Don't hesitate to enlist the help of our experts. With our experience with various system landscapes, we help you to manage complexity.
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