Data visualization has turned into an irreplaceable standard for today's business intelligence (BI). Data visualization software also has an important part in big data and advanced analytics projects. Here are the most innovative data visualization tools.
Data visualization refers to the presentation of data in a graphical or pictorial format. It assists people in understanding the significance of data by projecting it in a visual context. Trends, patterns and correlations that might go unnoticed in a usual text-based data presentation can be identified and located easily with data visualization software.
Data visualization has turned into an irreplaceable standard for today's business intelligence (BI). Data visualization tools now play an integral role in democratizing data and analytics, opening up access to data-driven insights to workers throughout an organization. The ease in operating these tools, compared to the traditional statistical analysis software or the older BI software, has caused a spike in the number of businesses using data visualization tools by themselves, without any IT support.
Data visualization software also has an important part in big data and advanced analytics projects. During the initial years of the big data trend, businesses accumulated gigantic sets of data and soon required a way to get quick overviews of the massive troves of information. This is where visualization tools came to the rescue.
Here are some of the most innovative and renowned data visualization tools suitable for handling the kind of complex data we handle today. With features like charts, graphs, infographics and videos, and for the more advanced ones – virtual reality and augmented reality – these tools offer effective modes of communication. All the tools listed below are paid for; however, they do have free trials or licenses for personal use.
Tableau boasts a customer base of more than 57,000 active accounts, throughout different industries. Particularly, the enormous and very quickly changing data that is used in the typical big data operations can be handled efficiently by this software. Tableau incorporates an array of advanced database solutions like Amazon AWS, SAP, Teradata, etc., which arms it well enough to deal with artificial intelligence and machine-learning applications. Tableau is proven very effective to produce visuals and graphics that make data easily understandable.
With its clean, minimal interface, Datawrapper is very user friendly. You can simply upload CSV data and produce plain charts and maps, which are can be easily integrated into reports. This tool has been gaining popularity especially in media organizations that employ it to produce statistics and charts that are suitable to present to common folks.
Highcharts is the go-to when quick and flexible solutions are needed at hand. It requires a minimal amount of specialist data visualization training for the user to access it. The feature that sets it apart from its competitors is its cross-browser support, which means anyone is able to access and run the visualizations, which is unusual for visualization tools.
5. TeamMate Analytics
TeamMate Analytics incorporates over 150 audit tools. It runs on top of Excel, which allows users to easily analyze data and produce significant visualization without requiring much specialization training. It offers a free trial, and its data visualization features include analytics, filtered views, relational display and simulation models.
Sisense has a simple, uber-friendly drag-and-drop interface, which is able to create more complex and layered charts and graphics, along with interactive visuals, without requiring much effort. It incorporates a full stack analytics platform. With Sisense, it is possible to gather numerous data sources into one single, easily accessible repository, where it can be reviewed instantly through dashboards, regardless of whether it is a big data-sized set. These dashboards can then be sent across different organizations enabling employees, even the ones who are nontechnical-based, to find solutions to their problems.
Data visualization is the decked-up face of data analytics. It doesn't interfere with numbers or the questions, but simply gives you a different point of view. If your organization needs advanced data analytics, then the self-service BI tools that are better known for their number-crunching capabilities rather than their visualization abilities should be your go-to.
If your objective is to bring an easier but deeper understanding of your organization's data to a wider spectrum of employees, then data visualization is highly important. However, just any visualization tool might not sit appropriately with each and every context. It is necessary to know your audience and opt for visualizations that are best for communicating with them.