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Data Visualization explains data graphically by the use of diagrams, charts, tables, comparisons, images and graphs.

Does crunching numbers work for you? You can spot anomalies and trends from huge stacks of data in a matter of seconds?

Great, you are a Data Scientist!

But believe us, that’s not the case with the remaining majority. They need a little boost to understand your analysis or to do any of their own.

People respond to visuals more than numbers or text. It’s easier to explain yourself through charts, graphs, infographics, Venn diagrams, color maps and pie charts. It is also easier to retain information for a longer time when you’ve ingested it through visuals.

why data visualization, how does data visualization help me?, importance of data visualization

Understanding Data Visualization…

Data visualization is representing data in pictorial form. Heavy datasets and their subsequent analysis are better represented through Data Visualization tools.

Information communicated through graphs, columns, pie charts, Venn diagrams, color maps, network maps, trees, frequency polygons, box-and-whisker plots, lines, surface or volume scatter plots are easier to wrap your head around.

If you want to read more about the types of Data Visualization, do check out our article here!

Top 10 Data Visualization tools

These rankings follow no specific order. Do check them out.

1. Tableau

Tableau is one of the most popular Data Visualization tools used in business intelligence. It has a lot to offer individual users as well.

You can use either an online or a public version of Tableau depending on your needs. The interface is interactive and easy to use.

As a newbie, you don’t need a thorough knowledge of database management and graphs to get started.

Tableau supports a host of file types and data imports from various servers. There is enough scope to play around in the tableau dashboard with multiple views for your data.

Tableau dashboard

Tableau has a no-brainer drag and drop interface which significantly reduces both time and effort.

How Tableau stands out? 

Check out map visualization in Tableau. It’s one of the easiest chart types to create as Tableau has innumerable pre-packaged geographical coordinates of the world.

2. Spotfire

TIBCO’s Spotfire is speeding among popular Data Visualization tools. Spotfire has an interactive dashboard that is impressive for data exploration.

Spotfire has lesser room for customization than it’s other counterpartsSpotfire is great for building and comparing models using graphs.

However, working knowledge of statistical analysis will come in handy when trying your hands at this tool. 

Here’s how predictive modelling in Spotfire looks like:

spotfire dashboard

How Spotfire stands out?

The tool is great for predictive modeling. Spotfire lets you use R, S+, SAS, or MATLAB functions directly from the software and is great for statistical analysis.  

3. QlikView

QlikView dashboards are smart and interactive!

They are great at discovering hidden and underlying trends, so much so that if you type a word in the search bar, QlikView will generate all possible relationships, trends and associations of the word within your data set. 

QlikView is great at discovering relationships and subsequently cuts down on your analysis time. QlikView allows for scripting which means you can customize the tool to perform calculations and data manipulation with a few lines of code.

This is how it sets its niche against Tableau’s drag and drop option which limits customization.

How QlikView stands out? 

QlikView is fast.

This is often credited to it being an in-memory tool which does not require data warehouses or data cubes. For a newbie, data warehouses can be thought of as repositories of data coming from different sources while data cubes are a representation or imagination of data based on the number of dimensions in your data.

QlikView must need some data layer, at least! QlikView uses its own QVDs which are simply data files with an extension .qvd.

QVDs are QlikView’s trademark way of processing and storing data. This is the secret behind QlikView’s super fast speed!

Data Visualization through QlikView Vs. QlikSense4. Microsoft Power BI

Microsoft has been a force to reckon with when it comes to Business Intelligence and Analytics.

Power BI, the brainchild of Microsoft, is being used widely by organizations for creating beautiful visuals and advanced insights.

Power BI can be accessed through a windows application called Power BI Desktop, online through Power BI service or through IOS and android apps.

Power BI offers a single-pager dashboard called canvas which houses and displays different reports and hence data sources as tilesPower BI’s data visualization features are stunning with a template library of visuals available under Power BI custom visuals.

Power BI dashboard, Power BI application, Power BI example

How Power BI stands out?

Microsoft Power BI is absolutely free to use. Microsoft has been universally easy to use and Power BI follows suit.

Power BI connects seamlessly with other Microsoft products and deserves a special mention when it comes to user experience.

5. IBM Cognos Analytics 11.1

IBM Cognos Analytics 11.1 is a fresh face and has a lot to offer than its predecessors. The new version offers data exploration and data visualization backed by augmented intelligence and natural language processing.

Okay.. relax! what that means is that users can interact with the tool, ask questions and get their queries answered just like regular, human interaction.

The tool offers an AI assistant that understands your data, compiled from various sources and offers help in modelling, exploring and visualization.

IBM cognos dashboard

IBM Cognos Analytics 11.1 also offers the coveted drag-and-drop capabilities to create new dashboards and reports.

How IBM Cognos Analytics 11.1 stands out? 

AI-backed dashboards that suggest data patterns and possible relationships while also answering questions posed by the users.

6. Alteryx

Alteryx is like other user-friendly Data Visualization tools that do not require you to have well-developed Data Visualization skills. Here again, the dashboard is enabled with drag and drop functionality to speed things up.

Alteryx comes in handy in joining and blending data from various sources, data warehouses and cloud applications.

what is Alteryx, Alteryx performance, Alteryx advantages

How Alteryx stands out? 

Alteryx is lauded for its lean and clean graphical user interface. Alteryx caters to users from all possible backgrounds and does not require a lot of coding itself.

7. D3.js

D3.js helps you create state-of-the-art graphics.

Mike Bostock developed D3.js in 2011 and it has come a long way since. D3.js stands for Data-driven documents written in a javascript. D3.js is open source and free to use. You can work with source code and add your own features.

The tool gives you complete freedom to change your visualization to match your story-telling. The full range of possibilities of customization outshines the competition.

learn D3.js

How D3.js stands out?

D3.js has a steep learning curve. With more and more user-friendly Data Visualization tools bringing us easy-to-use dashboards, D3.js is losing popularity for being more technically complex to use.

8. Sisense

Sisense is yet another powerful business intelligence tool that is flexible enough to be interactive and supportive to newbies while also performing a series of robust functions for more seasoned users.

Sisense has an in-chip engine which makes data sourcing, preparation, and dashboarding absolutely effortless. 

Sisense is unbelievably fast. It consolidates data from a host of different sources in no time. It also helps its users to disseminate their visualization to others.Sisense Dashboard

How Sisense stands out?

Sisense offers industry and role-specific dashboards too. Each of these dashboards is as involving as they are interactive. They are designed in a way to be most helpful to all kinds of users.

9. SAP Lumira

SAP Lumira is known for its simplistic user interface. The dashboard is clean and minimalist with four tabs:

  • prepare
  • compose
  • visualize
  • share

Add ease of use to this self-service tool and that’s the reason it’s a popular choice for data exploration.

SAP Lumira’s design applications and well-guided navigation paths are easy to follow and experiment with.  

Lumira lets you gather data from various source types including CSV files, SAP HANA, MS Excel, Freehand SQL and SAP business objects universe. It creates beautiful storyboards with its visualization features and empowers its users with customization options.

SAP Lumira dashboard

How Lumira stands out?

Lumira is easy to learn and use. It offers a number of support videos in case the users get stuck.

10. Kibana

Kibana uses Elasticsearch for sourcing the data. Kibana has rich capabilities to perform data analytics and visualization on this data.

It is an open-source platform and works in tandem with Elasticsearch. Elasticsearch is a search engine. You can use Kibana to search, view, and work with data stored in the search engine’s indices.

dashboard in Kibana data visualization tool

How Kibana stands out?

Kibana is among great Data Visualization tools when it comes to time-series analytics, application monitoring, and operational intelligence cases.

Wrapping up…

These Data Visualization tools are fun to attempt and explore. They are designed to create a powerful story-telling experience and display your outputs in the most riveting way.

If you are intrigued by the color, taste, coherence and edge that Data Visualization brings to your analysis, you should also check out Plot.ly.

Plot.ly, a Python library along with Dash, a Python framework helps create astounding visuals with its interactive user interface, dashboards and displays, like sliders, drop-down menus, and graphs, to your Data Analytics code.

We hope you enjoyed our list and learned a thing or two about the competitive Data Visualization tools in the market.

Do check out these Data Visualization tools and let us know all about it in the comment section!

Author

Content Writer @ INSAID. A machine learning buff who loves to read, write and explain everything AI!

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