Data processing and visualization tools

Visualization is critical for data analysis. It provides a first line of attack, revealing intricate structures in data that cannot be absorbed otherwise. We discover unimaginable effects and question those that have been imagined."

William S. Cleveland (de Visualizing Data, Hobart Press)

Over the years an enormous amount of public information has been generated and stored. This information, if viewed in a linear fashion, consists of a large number of disjointed numbers and facts that, out of context, lack any meaning. For this reason, visualization is presented as an easy solution towards understanding and interpreting information.

To obtain good visualizations, it is necessary to work with data that meets two characteristics:

• It has to be quality data. They need to be accurate, complete, reliable, current and relevant.
• They have to be well treated. That is, conveniently identified, correctly extracted, in a structured way, etc.

Therefore, it is important to properly process the information before its graphic treatment. The treatment of the data and its visualization form an attractive tandem for the user who demands, more and more, to be able to interpret data in an agile and fast way.

There are a large number of tools for this purpose. The report "Data processing and visualization tools" offers us a list of different tools that help us in data processing, from obtaining them to creating a visualization that allows us to interpret them in a simple way.

What can you find in the report?

The guide includes a collection of tools for:

• Web scraping
• Data debugging
• Data conversion
• Data analysis for programmers and non-programmers
• Generic visualization services, geospatial and libraries and APIs.
• Network analysis

All the tools present in the guide have a freely available version so that any user can access them.

New edition 2021: incorporation of new tools

The first version of this report was published in 2016. Five years later it has been updated. The news and changes made are:

• New currently popular data visualization and processing tools such as Talend Open Studio, Python, Kibana or Knime have been incorporated.
• Some outdated tools have been removed.
• The layout has been updated.

If you know of any additional tools, not currently included in the guide, we invite you to share the information in the comments.

In addition, we have prepared a series of posts where the different types of tools that can be found in the report are explained: