Top 20 Data Visualization Tools

Why Data Visualization?

Data visualization in layman’s language describes any determined attempt to help people understand the significance of data by placing it in a visual context. The analytics is presented visually so that the decision-makers can grasp difficult concepts or identify new patterns in a short span of time. When something becomes too difficult to understand, then data visualization comes into the picture which simplifies everything to a concept that can be easily grasped. Data visualization basically puts the complex data into a graphical format, allowing the user to easily understand the state of business and identify patterns to bolster successful strategies. It also Identifies and improves the areas that need attention immediately. It gives better clarification on which all factors influence customer behavior. It helps to understand the product positioning in a better way. Predicts the sales volume quickly.

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Human eyes are more reactive to colors and patterns as compared to text, this is another reason why data visualization is getting more attention.  We can easily figure out the difference in colors, shapes because of human nature. It is human nature to quickly identify the trends by looking at graphs and figures. Now we can understand the need for good visualization tools in the world of a deluge of data. In big enterprises where we have different data sources that are also stored in different, it is very critical for a business to have some tool. which can extract data from different sources and present in some visuals which help the business to take strategic decisions based on charts. In Big data world, Data visualization tool has become an integral part of the technology stack of any organization.

Let's have a look at the below dashboard where we have presented some stats for Brazil using one of the popular data visualization tools Tableau. This dashboard is dependent on various data sources and data points but government agencies would not be able to calculate some important indexes by just looking at different data sources. Their job has been made easier by data visualization tools.

Data Visualization involves a Seven step process

• Acquire: Understanding and collecting the data that we are trying to visualize, including its size and uniqueness in a particular column from a file on a disk or a source over a network.
• Parse: Determining the data that we are trying to visualize and also the kind of information we want to communicate through a proper structure and arranging them into proper categories.
• Filter: Identifying the most informative indicator and separating the data along with filtering them basis the necessity.
• Mine: Applying the data in mathematical context through statistics or data mining.
• Represent: This step involves choosing the basic visual model, such as a bar graph, list, chart or a tree.
• Refine: This step emphasizes on improving the basic representation to make it clearer and more visually engaging for the viewer. It also involves the use of different color, sizes, scales, shapes, and labels to grab attention to the key messages
• Interact: The final step involves the methods of manipulating the data and also keeping control over what features need to be visible.

On the basis the statistics from Forbes, the top seven data visualization tools preferred by the users are explained below in a set pattern in order to have a better understanding of these tools :

1. Tableau

Tableau is the master of data visualization software with a large customer base of 57000 and more majorly because of its simplicity of use and ability to provide interactive visualizations far beyond the capability of other general BI solutions. The ability of Tableau in integration with a large number of advanced database solutions including Hadoop, Amazon AWS, My SQL, SAP, and Teradata help them in managing huge data along with fast-changing datasets that are used in Big Data operations, including artificial intelligence and machine learning applications. Efforts have been put in for research and testing enabling Tableau to create graphics and visualizations efficiently making them feasible for humans to understand.

Here are the Pros & Cons Of Using Tableau:

Pros:

• Excellent visualization abilities.
• Ease at use.
• High-quality performance.
• Feasibility to connect with multiple data sources.
• Informative community and forum.
• Responsive on Smartphones as well.

Cons:

• Very expensive and inflexible market cost.
• For scheduling and auto-refresh of reports - NO OPTIONS AVAILABLE.
• Restriction on visual imports.
• Formatting is difficult in the case of the column’s data.

Cost: $70 USD/user/month billed annually.

Open-Source/Licensed: Licensed. It has a free trial available.

2. QlikView

Qlikview tool is another major player and Tableau’s biggest competitor with a clientele of around 40,000 customers among 100 countries. The most appreciable feature of this tool is highly customizable set. It also has a wide range of features as it is a valuable advantage. Along with data visualization as one of its key components, it also offers powerful business intelligence, analytics and enterprise reporting capabilities. Qlik Sense,a sister package of Qlikview is used for handling data exploration and discovery.

Pros:

• User-Friendly Tool.
• Simple and Hassle-free maintenance.
• Many attractive and colorful data visualization options available.
• Can launch both direct and indirect data searches.
• Cost-effective.

Cons:

• Inefficient in real-time data analysis.
• Limits related to RAM
• Non-reliable and unsatisfactory customer support.
• Lacks the modern interface for eg: Drag and drop.

Cost: $15 USD/user/month billed annually.

Open-Source/Licensed: Licensed. It has a free trial available.

3. Power BI:

It is Microsoft offering in data visualization. It is basically a  business analytics service that delivers insights to quick and fast decisions. Their visuals prove to be stunning and can be shared with other end-users on any of the devices. Visually exploring and analyzing data on-premises and in the cloud—all in one view.

Pros

• It is very easy to use and business analyst can create dashboards with very ease. There is no specialized technical support required to use power BI.
• The seamless integration with existing application makes it very useful. We can easily create a rich personalized dashboard with enterprise-level customization.
• The underlying data on which dashboards are created can be easily set for auto-refresh and allow users to publish latest reports securely.
• The Power BI comes with two variants, on-premise, and cloud offerings. There is no memory and speed constraint due to the cloud offering of Microsoft. Due to cloud offerings data is easily retrievable and analysis is also completed in quick time.
• It has inbuilt support for integration with MS excel.
• Due to coming from Microsoft family, it is compatible with Excel, Azure and Microsoft SQL Server.
• It supports a broad range of  backend databases like Excel, SQL Server, Access, Azure, Adobe Analytics, Github, Google Analytics, Oracle, PostgreSQL, Salesforce, Teradata, and so on

Cons

• The power BI does not support records having a size greater than 250 MB.
• The power BI can work with single dataset at one point. It can not work with multiple datasets.
• There is also a limitation on dataset size. The maximum size of dataset supports in Power BI is 1 GB.
• The performance is not good with a large amount of data if we compare with some top data visualization tools. Although cloud offerings are much better than on-premises.

The pricing plan :

There are three pricing plans for Power BI:

• Power BI Desktop: It is free for single-user usage and includes features like data cleaning and preparation, custom visualisations and allowing users to publish reports to the Power BI service.
• Power Bi Pro: This plan costs $9.99 per user every month along and comes with data collaboration, data governance, building dashboards with a 360-degree real-time view, and allows the user to publish reports anywhere. It is free for the first 60 days after which you will need to buy the subscription.
• Power BI Premium: The premium plan starts at $4995 a month for every dedicated cloud compute and storage resource.

4. Fusioncharts

Widely-recommendable, charting and visualization package based on Javascript. It has established itself as one of the most popularly used products of its kind in the paid-for market. It has the ability to frame 90 different types of charts and can integrate with a large number of platforms and frameworks giving a great deal of flexibility. The most important feature of FusionCharts that has made it popular in the market is to not to start each new visualization from scratch. Rather the users can pick from a range of “live” example templates by simply plugging in their own data sources as and when required.

Pros:

• Active community.
• Supportive Helpdesk.
• customized for unique and specific implementations.
• Integration with most of the platforms is easier.
• Easily integrate with most of the platforms.

Cons:

• Font and resizing are the areas of concern.
• Very expensive solution.
• Not very easy to set-up.
• The Interface is a little outdated.

Cost: $497 USD/user/month billed annually.

Open-Source/Licensed: Licensed.

5. Highcharts

Like FusionCharts this also runs based on the Javascript API and integrates easily with jQuery. Research suggests that its website claims to be used by 72 of the world’s 100 largest companies. It is often especially chosen when a fast and flexible solution needs to be rolled out, with a minimum need for specialist data visualization training before it can be put to work. 

The key to success of this API is its focus on cross-browser support which commonly means anyone can view and run its interactive visualizations. This unique feature is not available even in newer platforms.

Pros:

• Customization can be done readily and easily.
• The graphs look attractive.
• A variety of options for charts are available.
• .Easy and flexible to use.

Cost: $430 USD/user/month billed annually.

Open-Source/Licensed: Licensed.

6. Data Wrapper

Datawrapper is gaining popularity especially among media organizations which require frequently the use to create charts and also present the statistics of different data’s. Another vital feature added in Data Wrapper is that it is simple with a clear interface that makes it very easy to upload csv data.

The end-user can also create straightforward charts, and even maps, that can be quickly embedded into reports for presentation.

Pros:

• No installation required for creating a chart.
• This toll is adequate for beginners.
• Available free of cost for use.
• Media Industry is the major end-user of this Data Visualization tool.
• Charts can be embedded in a short span of time.

Cons:

• A complex chart such as Sankey cannot be built using this tool.
• Data security is an area of concern since its an open-source.
• The free version does not support customization, exporting or printing of charts.

Cost: $29 USD/user/month billed annually.

Open-Source/Licensed: Open-Source.

7. Plotly

Plotly is an open-source tool that enables sophisticated and complex visualizations, because of its ability to integrate with analytics-oriented programming languages such as Python, R, and Matlab.  Plotly is preferred by users for creating, disseminating, and modifying graphical and interactive data online. It can even be installed on the premises. It can be deployed in the cloud. This way it is useful for data mining scientists who are always looking out for ways to organize and present data without actually involved in coding. Plotly users also have the right to collaborate among themselves for building, sharing, and editing maps and charts. This additional feature boosts the speed of visualization as well as the presentation of data in a unique way also maximizing efficiency from each member by ensuring that each of them has their own designated set of tasks.

Pros:

• Charts can be easily shared with the cloud account of the user.
• Editing can be done with charts online by the end-users.
• Quality images are exported during publication.
• Fully interactive interface.
• Since they are hosted on a server, can be easily shared 

Cons:

• At times speed becomes a concern since the charts are interactive and require more power as compared to the static chart.
• There are limitations to the free version.
• Due to different screen flashing at a time, the first sight might create some distraction and confusion.

Cost: $420 USD/user/year billed annually.

Open-Source/Licensed: Open-Source.

8. Sisense

Sisense provides excellent instant insight for anyone and anywhere within the organization. It has the capacity to visualize dashboards and reports and summarize the statistics of any piece of data, even the uncover underlying trends & patterns and helping the decision-makers to conclude with the data-driven statistics.

Pros:

• A boon for analysis on huge datasets.
• User- friendly interface.
• Excellent customer support.
• Upgrades quickly.
• Easy customization and flexibility are available with the product.

Cons:

•  Maintaining and developing analytic cubes is a challenge.
• No option for supporting the time format.
• Limited version of visualizations.
• If cube rebuilding is required then the cube becomes inaccessible for that duration.

Cost: The  cost of the product varies case by case basis depending upon the two factors:

1. Data size 
2. The number of users.

Open-Source/Licensed: Licensed. It has a free trial available.

9. IBM Watson: 

It is a supercomputer offered by IBM which leverages artificial intelligence and analytical components. It is named after IBM founder Thomas J Watson…

Basis the user’s data, it helps us to discover the pattern and insight of the available statistics.

Its intelligent and self-service application guides the user to the complete insight discovery process. Both structured and unstructured data can be easily extracted since the application uses natural language processing.

The biggest highlight of this process is that this application provides the new and of the user data.

Pros:

• Capability of Natural Language Processing.
• Can be accessed from different devices.
• Helpful in predicting the future of business and making decisions accordingly.
• Format of information is visually appreciable for the viewers.
• Dashboards have the capability of self-service.

Cons:

• Inefficient customer support.
• English Language application is only available. (Limitation for other language users).
• Maintenance cost is high.
• Structured data are not available directly.

Cost: $80 USD/user/month billed annually (For professional version).

Open-Source/Licensed: Licensed. 

10. RAW- Rawgraphs

This tool works on delimited data like CSV file or TSV file. It even works on copy /paste data as well. It acts as a missing link between spreadsheets and data visualization. Though Rawgraph is a web application yet the data security is not at all a concern. Wide range of conventional and non-conventional layouts are also available.

With the blink of an eye, the visual feedback is available. If the user is not happy with the visuals then another mapping can be done immediately.

Pros:

• Excellent platform for graphic and keeping/reading/arranging the user’s data.
• Easy readability and ability to rearrange the visual graphics.
• Adoptable mapping options available.
• Sharing data becomes feasible.
• The biggest advantage is its property of being scalable.
• Simple interface.
• It can be easily edited with vector graphic application and also can be imported,

Cons:

• Log scales are not available.
• At times it is limited in terms of visualization.
• Not as per user intuitive.

Cost: Not available

Open-Source/Licensed: Open-Source.

11. Visual.ly:

Visual.ly aims at becoming the largest community for creating, promoting and sharing data visualizations. It is the content service in a visual format. They have dedicated big data visualization service and a very impressive portfolio. An online process is streamlined we can easily outsource our data for visualization to a third party wherein the input of the project can be shared and the creative team is available to assist for the entire duration of the project. Visual.ly even sends email notifications for all the achievements and milestones achieved through the users' data along with sharing the constant feedback by the creative team. The biggest advantage of the Visual.ly is their distribution network for showcasing the outcome of the project once it’s completed.

Pros:

• Link opportunities are more.
• Better quality output.
• Good graphics are easier to produce.
• Less time-consuming.

Cons:

• Few embed options are available.
• They usually illustrate one point instead of multiple points.
• There is a limitation in the scope of the product.

Cost: Need to check.

Open-Source/Licensed: Need to check

12. Google Charts:

It basically creates a pictorial and graphical presentation of the data shared by the user. Google Charts have been coded with  HTML5 and SVG and aims at total cross-border compatibility along with Android, iOS including older Internet Explorer versions supported via VML. All the charts created are interactive with an additional feature of zoom. They are very user-friendly accompanied by their site features - a really appreciative comprehensive gallery where we can see the data visualizations and interactions at our disposal.

Pros:

• Very easy data integration.
• Data graphs are visually appealing.
• Can be incorporated into a variety of websites.
• Compatibility with other Google products.

Cons:

• At times the look and feel of the graphs are way too modern.
• Feature of exporting the chart should be more straightforward.
• Lack of demos on advanced tools.
• Lack of customization ability.
• They require network connectivity for data visualization.
• Not feasible with a mobile application.

Cost: Free trial available,

Open-Source/Licensed: Licensed. 

13. Zoho Reports:

Zoho reports are very well known as Zoho Analytics. They have an online reporting and business intelligence service that helps get the new insights on the users’ data. It helps in creating and sharing powerful, ad hoc reports within minutes, without any IT help. Data of users can be easily imported from applications and databases, even behind firewalls.

Pros:

• With little extra effort, new reports can be created. 
• Basis the need, existing report can be easily modified. 
• Features like report sharing, scheduling of emails are extremely useful features.
• In the case of a bigger database, space is not the concern.
• Quick and prompt level-1 customer support.

Cons:

• Report sharing becomes cumbersome with larger groups of data
• Training for new Zoho Reports' users should be potentially more effective.
• At times the main dashboard becomes more confusing with a larger number of data.

Cost: $25  USD/user/month billed annually (For professional version).

Open-Source/Licensed: Licensed. 

14. JupyteR:

It is basically a web application that supports the open-source. The major highlight is creating and sharing documents which have a live code,  narrative text, equations, and visualization. JupyteR stands for IPython (Interactive Python). In multiple programming languages, it is used for interactive computing. Also, it was originally developed for the Python programming language. It is serving Uses include: data transformation along with cleaning, simulation of numerical, modeling of statistics, data visualization, machine learning, and many more.

Pros:

• Prototyping can be concluded quickly and easily.
• The end result of the application is visually interesting.
• Insight of the data can be easily shared.

Cons:

• Tricky collaboration.
• At times reviewing of codes becomes difficult.
• More often there comes the challenge of complexity during production.

Open-Source/Licensed: 100% Open source and free for all users.

15. Dundas BI:

Dundas BI comes with highly-customizable visualizations along with interactive charts, gauges, maps, scorecards and many more. In addition to that, there is also granular control over almost all visual design elements. Dundas BI also align them to the enterprise reporting needs in a dedicated reports designer. There is lots of flexibility while creating multi-page reports or ad-hoc reports. In short form, the complex views are available in simplified form for the user.

Pros:

• Lots of Flexibility in the functionality.
• Anything imagined can be possible through the licensed version.
• Variety of charts and data sources are available along with flexibility in design.
• N numbers of built-in options for extracting, modifying and displaying data are available.

Cons:

• Predictive analytics is missing.
• Too massive to fully exploit the capabilities of a software developer.
• 3D Charts are not supported in this application.
• Non-essential upgrades need to be removed.

Cost: $99 USD/user/month billed annually (For professional version).

Open-Source/Licensed: One-time license.

16. Visme:

Visme has transformed the way of creating & sharing very engaging Presentations along with Infographics and other visual formats. The content creation tool is the most popular tool being used by IBM, General Dynamics, and Accenture and 1.7 million other users. The stories and the boring data’s are being translated into engaging Visuals. The visually available product can be either published online or embed to any site and can be download for offline use.

Pros:

• Customer user-friendly dashboard making the designs of collateral extremely easy and within a short span of time.
• Templates and individual graphics, stats, objects are adaptable easily. 
• They are immensely helpful in providing ideas for formatting and structuring the graphic.
• Visme sets a benchmark in itself by providing templates for presentation slides.

Cons:

• At times it becomes difficult to select particular sections when there are many layers in a particular image.
• Not much effect on the social templates
• Often it acts a little funky when on clicking the image.

Cost: $70 USD/user/month billed annually (For professional version).

Open-Source/Licensed: Licensed. 

17. Grafana:

Bafana is commonly used for the purpose of dashboard and graph composing. It focuses on providing ample ways to visualize time series metrics, mainly though graphs. They even support ways to visualize data through a pluggable panel architecture. At present,   rich support for Graphite, InfluxDB, and OpenTSDB and even supports other data sources via plugins.

In a layman language, it is a tool in the Monitoring category of a tech-savvy user. They can create, edit, search and save the dashboards.

Pros:

• Possibility of templating.
• Feature of importing and exporting the dashboard available.
• Rearranging the panel with drag and drop feature.
• Column span and row heights can be modified.
• Can be easily deployed.

Cons:

• Dashboard URL keeps on changing.
• Irregularities in case of notifications.
• Data storage is a cause of concern hence used with Graphite.

Open-Source/Licensed: Open-source.

There are other tools as well. Please find below some other alternatives we have on data visualizations:

18. ChartBlocks:

It offers an online charting service. We need to upload our data then we can easily create interactive charts based on uploaded data.

19. NVD3: 

It is a dynamic collection of components, with the aim of keeping these components very customizable. The highlight of the project is its attempt to build reusable charts.

 20. Leaflet:

It is basically designed keeping in mind the simplicity, performance, and usability. Leaflet is defined as mobile-friendly interactive maps leading the market with open-source JavaScript.

21. N3-charts: 

They are generally used for creating beautiful charts in Angular JS application with the use of JavaScript library.

With so many options available, it becomes difficult sometimes to choose the right visualization tool for organization. The organization needs to carefully select the tool which can fulfill their requirement.  The tool should be able to extract data from different platforms stored in different formats. The enterprise structure also helps in deciding the best data visualization tools.

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