Data Visualization is basically putting the analyzed data in the form of visuals i.e – graphs, images. These visualizations make it easy for humans to understand the analyzed trends through visuals.
Data Visualization is very important when it comes to analyzing big datasets. When data scientists analyze complex datasets they also need to understand the insights collected. Data Visualization will make it easier for them to understand through graphs and charts.
Tableau is often regarded as the grand master of data visualization software and for good reason. Tableau has a very large customer base across many industries due to its simplicity of use and ability to produce interactive visualizations far beyond those provided by general BI solutions. It is particularly well suited to handling the huge and very fast-changing datasets which are used in Big Data operations, including artificial intelligence and machine learning applications, thanks to integration with a large number of advanced database solutions including Hadoop, Amazon AWS, My SQL, SAP and Teradata. Extensive research and testing has gone into enabling Tableau to create graphics and visualizations as efficiently as possible, and to make them easy for humans to understand.
Qlik with their Qlikview tool is the other major player in this space and Tableau’s biggest competitor. The vendor has over 40,000 customer accounts across over 100 countries, and those that use it frequently cite its highly customizable setup and wide feature range as a key advantage. This however can mean that it takes more time to get to grips with and use it to its full potential. In addition to its data visualization capabilities Qlikview offers powerful business intelligence, analytics and enterprise reporting capabilities and I particularly like the clean and clutter-free user interface. Qlikview is commonly used alongside its sister package, Qliksense, which handles data exploration and discovery. There is also a strong community and there are plenty of third-party resources available online to help new users understand how to integrate it in their projects.
Like FusionCharts this also requires a licence for commercial use, although it can be used freely as a trial, non-commercial or for personal use. Its website claims that it is used by 72 of the world’s 100 largest companies and it is often chosen when a fast and flexible solution must be rolled out, with a minimum need for specialist data visualization training before it can be put to work. A key to its success has been its focus on cross-browser support, meaning anyone can view and run its interactive visualizations, which is not always true with newer platforms.
Datawrapper is increasingly becoming a popular choice, particularly among media organizations which frequently use it to create charts and present statistics. It has a simple, clear interface that makes it very easy to upload csv data and create straightforward charts, and also maps, that can quickly be embedded into reports.
Sisense provides a full stack analytics platform but its visualization capabilities provide a simple-to-use drag and drop interface which allow charts and more complex graphics, as well as interactive visualizations, to be created with a minimum of hassle. It enables multiple sources of data to be gathered into one easily accessed repositories where it can be queried through dashboards instantaneously, even across Big Data-sized sets. Dashboards can then be shared across organizations ensuring even non technically-minded staff can find the answers they need to their problems.