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Top Data Visualization Tools

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Nothing embodies the old cliché “a picture is worth a thousand words” like data visualization.

You can perform data analysis by looking at a spreadsheet of numbers in rows and columns, squinting at each row to make sure you read it right. Or – far better – you look at a pie chart or bar graph and get the full picture immediately.

Data visualization is the process of representing data in graphical form, be they charts, graphs, sparklines, infographics, heat maps, or statistical graphs. Data presented in visual form is easy to understand and analyze. Relevant stakeholders can then use the findings to make more efficient real-time decisions.

Data visualization tools incorporate support for real-time and streaming data, artificial intelligence integration, collaboration, and interactive exploration to facilitate the visual representation of data.

Anyone performing numerical data analysis needs a visualization tools. No one has the time to review hundreds of lines of data, and human error is almost a guarantee. A visualization tool gives you the full or almost full story immediately.

There tends to be a separation between the data stores and the business intelligence tools and visualization tools. Sure, Teradata and Oracle will give you a visualization tool for their databases, but third party vendors specialize in comprehensive visualization and cross platform support.

Data visualizations like the one above present complex metrics in the context of visual relationships, enabling a faster and more intuitive approach to data mining. 

Top Data Visualization Tools

What follows is our top ten best data visualization tools, in no particular order:

Tableau

Tableau is by far the most popular data visualization tool, so much so that Salesforce bought it, and Salesforce is a SaaS company while Tableau is not. Tableau is usable by everyone from college students to data scientists.

It’s an easy-to-use tool that provides results quickly, in a wide variety of formats. It provides integration with all of the major advanced databases, including Teradata, SAP, My SQL, Amazon AWS, and Hadoop.

Microsoft Power BI

Microsoft has two major visualization tools, with Power BI on the high end. It provides classic data visualization tool elements like interactive dashboards and APIs for integration and is tightly integrated with the Microsoft data platforms like SQL Server and Sharepoint.

It operates a lot like Excel, so if you have cut your teeth on Excel the learning curve is shorter.

Excel

Beyond its primary use as a spreadsheet tool, Excel comes with very good basic data visualization tools and functions. It comes with 20 or more built-in charts, including pie charts, radar charts, histograms, scatter plots and more.

It’s a great beginner tool you probably already have, but it doesn’t scale well and if your data sets grow, you will likely want to upgrade to Power BI.

Sisense

Sisense is a data visualization tool is based on a business intelligence model that offers multiple tools for data analysis. The tool is pretty easy to set up and use, it can be installed in minutes and provides instant results, yet it has the advanced functionality seen in mature, high-end software like Tableau.

One of these features is in-chip processing which allows for faster, more efficient queries. It allows the users to export files in common formats like PDF, Word, Excel, and PowerPoint.

Zoho Analytics

Zoho Analytics also specializes in business intelligence visualizations, offering a number of different ways to chart your data and a variety of dashboards. It supports a broad number of different data sources and lets you prep your data within the platform.

Its real strength is an AI assistant called Zia that lets you ask questions to in natural language.

Google Charts

Finally we have Google Charts which lets you create interactive charts which include maps, bar charts, histograms and more. You can then embed these online and run them live. This is ideal for people who already use Google Workspace and want to integrate with many data sources.

Google Charts works with a wide variety of SQL databases and also has a number of data connectors for you to collect your data. On the downside, you need to know how to code to use it, which is likely a barrier for most beginners. And it isn’t as well supported as other products.

FusionCharts

FusionCharts is a JavaScript-based tool that offers more than 100 interactive charts and more than 2,000 maps, making it one of the most flexible tools out there. It also integrates with a number of other data visualization platforms, such as Angular, React, Vue, JQuery, PHP, Ruby on Rails, ASP.NET, Django.

While the software offers a large number of pre-set templates, it’s based in JavaScript, so you do have to know the language to make the most out of it.

Infogram

Infogram is a popular for creating reports, charts and maps. Its strength is in generating infographics and comes with more than 550 maps and 35 interactive charts. It has an easy-to-use interface and the data visualizations are considered easy to learn.

Another point in its favor is it comes with many different templates with aesthetically pleasing designs.

Looker

Looker is a comprehensive business intelligence tool with links to Snowflake, Redshift, and BigQuery along with over 50 SQL dialects, so you can connect with several databases at once, then export your results in any format.

It offers a real-time dashboard for data analysis to help you make business decisions based on the data visualization.

IBM Cognos Analytics

IBM Cognos Analytics is a cloud and on-premise-based business intelligence solution that uses an augmented intelligence-infused AI assistant that allows users to ask questions and get answers in natural language. It also recommends new visualizations and joins in data allowing users to unearth connections they might not anticipate.

It offers users a wide range of business analytics functionality and a full complement of essential analytics functions, including advanced dashboarding, data integration, reporting, exploration and data modeling.

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