Comparing Data Visualization Software: Here Are The 7 Best Tools For 2018

Credits : Forbes

 

Visualization is an essential element of any Big Data and analytics strategy. The most up-to-date, real time information and advanced analytics solutions are an expensive waste of money if you can’t communicate the results clearly and effectively to the people whose job it is to put them to work.

Data visualization tools are constantly evolving to the point where they are no longer the sole domain of the formally trained BI analyst or data scientist. Increasingly businesses are understanding the value of putting analytics at the fingertips of all segments of the workforce and today’s tools are a reflection of this.

Here’s an overview of my top 7 paid-for visualization solutions, and for those on a tight budget look for my round-up of free tools coming soon.

Microsoft Power BI

PowerBI is an all-in-one BI and analytics platform provided as-a-service or as a desktop client but it is particularly highly rated for its visualization capabilities. Visualizations are created directly from reports and can be shared with users throughout your organization. As well as a large number of inbuilt visualization styles, new ones are constantly being created by the AppSource community or if you want to get your hands dirty with coding, they can be created from scratch using the Developer Tools and shared with other users. It also includes a natural language interface allowing visualizations of varying complexity to be built from simple search terms. It is consistently rated as one of the easiest to use tools for visual data exploration.

Tableau

Tableau is often considered the gold-standard of data visualization tools and as such it enjoys wide deployment with a reported 57,000 active user accounts. Much of its appeal stems from its flexibility and while it may not be as beginner-friendly as some packages, a vast support network exists in the form of its global community of users, spread across many industries.

In particular its power means it is well suited to Big Data operations involving fast, constantly changing datasets, and as such it is designed to easily plug in to a large range of industry-standard databases such as MySQL, Amazon AWS, Hadoop, SAP and Teradata. Three basic distributions are available – Desktop, Server and cloud-based Online. New additions to the service this year include the Hyper in-memory capabilities designed to greatly speed up analysis of large data sets.

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