10 Data Visualization Tools

  • Post last modified:19 May 2023
  • Reading time:23 mins read
  • Post category:Business Analytics
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Only in the movies is it feasible to read numerical streams. In the real world, organisations must rely on data visualisation tools to extract trends and patterns from raw data.

Working with various Big Data analytics systems necessitates the use of Big Data visualisation. Decision-making becomes considerably easier if the flow of raw data is represented with visuals.

To meet and surpass the customer’s expectations, Big Data visualisation tools should provide the following features:

  • The capacity to process many sorts of incoming data.

  • The ability to use numerous filters to fine-tune the results.

  • The capacity to interact with data sets during analysis.

  • The capacity to link to other software in order to accept incoming data or offer input.

  • The ability to give users collaborative alternatives.

Despite the fact that there is a plethora of specialised tools for Big Data visualisation, both open-source and proprietary, there is a group of them that stands out significantly, as they include all or some of the aforementioned qualities.

Data Visualization Tools

Here are 10 popular data visualization tools you might want to consider:


Tableau is a data visualisation platform that allows data analysts, scientists, statisticians, and other professionals to analyse data and form clear conclusions based on their findings. Tableau handles large amounts of data fast and produce the necessary data visualisation result.

Tableau is one of the popular evolving business intelligence and data visualisation tool. It is used to create and share interactive dashboards, which can depict the variation and density of data on various visual forms like charts and graphs. Tableau can acquire data from various sources like files, big data, relational data and then process it. Currently, it is positioned as industry leader in business intelligence and analytics.

Tableau is accessible for individual data analysts as well as corporate teams and companies on a larger scale. It offers a 14-day free trial before moving on to the premium version.

5 Main Tableau Products

Tableau offers five main products to fit into diverse data visualisation requirements for professionals and organisations. They are:

  • Tableau desktop: It is self-service business analytics and data visualisation that can be used by anybody. It translates data pictures into optimised queries. You can directly connect to your data from your data warehouse using Tableau desktop for up-to-date live data analysis. Queries can be performed in tableau without writing any code. Data from multiple sources can be imported into tableau’s data engine and then integrated to create an interactive dashboard.

  • Tableau server: It is enterprise-level tableau software. You can publish dashboards with Tableau desktop and then share them with others inside the organisation with the help of a web-based tableau server. Following are the components of tableau server:

    • Application server: It handles permission and browsing for web and mobile interfaces of tableau server.

    • Vizsql server: After receiving a request from clients, Vizsql server sends the query to data source and returns the result. The result set is then rendered as image and finally is presented to the user.

    • Data server: manages and stores data sources and metadata.

  • Tableau online: It has the same functionality as the tableau server but it is hosted by tableau in their cloud.

  • Tableau reader: It is a free application that can be downloaded from tableau website. It can be used to analyse the workbooks that have been saved with .tbwx extension. The only thing worth keeping in mind is that anyone who receives the workbook can use the tableau reader to open it. So, essentially, there is no security.

  • Tableau public: It is free download software from tableau’s website. Being “public” means anyone can post their visualisation and any one can view other’s workbooks. There is no feature which allows you to save your workbook; however, it allows you to block others from downloading it. Tableau public can be used for sharing any resource and its development.

SaS Visual Analytics (VA)

SAS Visual Analytics (VA) is a business analytics platform that provides data preparation, visual analysis, analytical applications, and dashboards that may be expanded with sophisticated analytics models. VA also facilitates the development of conversational interfaces and chatbots.

Customers may integrate live, interactive VA visualisations into their bespoke web apps using the Visual Analytics SDK, and a Microsoft 365 interface allows for the embedding of VA insights in Excel documents. SAS Viya, the company’s open, cloud-ready end-toend analytics platform, includes SAS Visual Analytics.

SAS is a privately held firm that was founded in 1976 and is a wellknown name in the analytics and business intelligence field. The vendor’s goal is to make analytics available to everyone and everywhere.

SAS Viya is an open and cloud-ready end-to-end analytics platform that strives to meet the analytical demands of all sorts of clients. It was created as a massively parallel, distributed environment that links to a variety of data sources and may be run on-premises or in the cloud.

SAS has made a point of developing an open architecture that not only supports SAS code but also languages such as R, Python, Java, and Lua natively or via APIs to improve scalability and satisfy data scientists’ desire for these tools. Viya is made up of a collection of microservices and an in-memory engine called SAS Cloud Analytics Services (CAS) that may run on a single system or across several machines.


Qlik is a software firm that mainly deals in data visualisation, executive dashboards, and self-service business intelligence.

Gartner consistently ranks Qlik as one of the top data visualisation and business intelligence (BI) suppliers in the industry, alongside Tableau and Microsoft. QlikView, the company’s main product, enables visual data exploration, self-service BI reporting, and the creation and sharing of data dashboards.

Qlik Sense, the company’s second key service, provides for more free-form analytics and allows customers to construct data and web applications via API connections. Qlik Sense may be installed either on-premises or in the cloud. The firm also runs a product called Data Market, which gives QlikView customers access to a selected list of publicly available data sets such as census data, financial data, and business filing data.

Both main products are powered by Qlik’s own data engine, which links to data repositories and saves data in memory. This enables users to apply visualisations and alter dashboards with a drag-anddrop interface rather than the need to write code to manipulate data. Qlik’s software, like that of other data visualisation tools such as Tableau, is usually deployed first by specific lines of business rather than as part of a centralised IT initiative.

This provides the advantage of allowing projects to move more rapidly, but it also increases the danger of data governance issues, such as repeated analyses, data silos, and analyses performed on old datasets. However, after the benefit of business-line deployments is shown, some businesses prefer to standardise the technology across all divisions.

QlikView, being a self-service BI technology, is typically easy enough for most corporate users to use without having significant data analysis or programming expertise. It is frequently used in marketing, human resources, and sales departments, as well as in executive dashboards to allow upper-level management to monitor overall corporate activities.

While no particular skills are necessary, most companies give training to business users before granting them access to the program. Qlik conducted an initial public offering (IPO) in July 2010, but was later sold to private equity company Thoma Bravo.


R analytics is data analytics performed using the R programming language, which is an open-source language used for statistical computation or graphics. Statistical analysis and data mining applications typically employ this programming language. It may be used in analytics to find trends and create useful models. R is not only useful for analysing data in businesses, but it can also be used to aid in the construction and development of software applications that do statistical analysis.

R, which has a graphical user interface for programmed development, provides a wide range of analytical modelling approaches, including traditional statistical tests, clustering, time-series analysis, linear and nonlinear modelling, and others. The interface consists of four windows: the script window, the console window, the workspace window, the history window, and tabs of interest (help, packages, plots, and files). R enables the creation of publication-ready plots and visualisations, as well as the storing of reusable analytics for future data.

R has grown in popularity over the years and is still a popular analytics language at many institutions and schools. It is now widely recognised in academia and among organisations all over the world for providing solid, trustworthy, and accurate analytics. While R programming was often thought to be difficult to learn for non-statisticians, the user interface has gotten more user-friendly in recent years.

It also now supports extensions and additional plugins such as R Studio and R Excel, making learning easier and faster for novice business analysts and other users. It has become the industry standard for statistical analysis and data mining projects, and its use is expected to increase as more R-trained analysts enter the profession.


Python is a prominent multi-purpose programming language that is extensively used for its versatility as well as its large library collection, which is useful for analytics and sophisticated computations.

Because of Python’s versatility, it offers dozens of libraries dedicated to analytics, including the widely used Python Data Analysis Library (also known as Pandas).

The majority of Python data analytics libraries are developed in some way from the NumPy library, which contains hundreds of mathematical computations, operations, and functions.

Python analytics tools have grown in popularity as a result of the computer language’s extensive use and adaptability in generating multiple solutions. Because it is a true general-purpose language, it can bring more capability to data analytics software than domain-specific languages with limited scope and capabilities.

Furthermore, Python’s performance capabilities are far higher than that of other prominent data analytics languages, and its interoperability with a wider range of other languages means that it is just more convenient in most circumstances.

Python’s low use of memory and other processing resources allows it to swiftly outperform languages designed expressly for statistical research, such as MATLAB or R.


Excel is a Microsoft software tool that utilises spreadsheets to organise numbers and data using formulae and functions. Excel analysis is used by organisations of all kinds to undertake financial analysis all across the world.

Excel is commonly used for data organisation and financial analysis. It is utilised in all business functions and at all sizes of businesses.

Excel contains a plethora of functions, formulae, and shortcuts that may be utilised to enhance its functionality. Excel is widely used in financial and accounting operations. In fact, many businesses use Excel spreadsheets for their whole budgeting, forecasting, and accounting activities.

While Excel is characterised as a “data” management tool, the most usually managed data is financial data. Excel is the ideal financial program, according to CFI. While there are other pieces of financial software that are designed to do certain tasks, Excel’s biggest suit is its resilience and openness. Excel models may be as strong as the analyst desires.

Accountants, investment bankers, analysts, and workers in many sorts of financial careers rely on Excel to do their everyday tasks.

SAP Analytics Cloud

SAP Analytics Cloud is a new solution in the SAP portfolio designed to fulfil the demands of cloud-based data visualisation. It is provided as an all-inclusive, SaaS-based package. It addresses data visualisation, financial planning, and predictive analytics requirements. Its primary role is to generate data reports.

SAP Analytics Cloud is a cloud-based solution that combines business intelligence, enhanced and predictive analytics, and planning. It offers sophisticated analytics across the company as the analytics layer of SAP’s Business Technology Platform.

SAP Analytics Cloud, abbreviated as SAC, is SAP’s cloud data visualisation product. What is its power? SAP Analytics Cloud integrates the following features in a single application:

  • BI (Business Intelligence)
  • Predictive Modelling
  • Planning

When it comes to business intelligence, SAP provides a comprehensive solution. SAC, which is available in SaaS mode online, is becoming increasingly significant in the SAP ecosystem. It is eventually expected to become the SAP Cloud suite’s BI reference tool.

SAP Analytics Cloud employs business intelligence and data analytics tools to assist you in evaluating your data and creating visualisations in order to forecast business outcomes. It also gives you the most up-todate modelling tools, which assist you by alerting you to potential data problems and classifying various data metrics and dimensions. SAP Analytics Cloud also recommends Smart Transformations to the data, which result in improved visualisations.

If you have any worries or business concerns regarding data visualisation, SAP Analytics Cloud ensuring complete client satisfaction by handling the client requests by using conversational artificial intelligence and natural language technology. You may use this platform for free for the first 30 days before paying `1639.53 per month for the Business Intelligence package.

Microsoft Power BI

Microsoft Excel is a spreadsheet program, not a data visualisation tool, in the purest sense. Nonetheless, it provides helpful data visualisation features. Given the widespread usage of Microsoft products in the industry, you may already have access to it.

According to Microsoft’s documentation, Excel can be used to create at least 20 different types of charts from data in spreadsheets. These range from simple alternatives like bar charts, pie charts, and scatter plots to more complex ones like radar charts, histograms, and tree maps.

Excel has restrictions in terms of what you can generate. If your company needs a more sophisticated data visualisation tool but wants to stay within the Microsoft environment, Power BI is a great option. Power BI was designed primarily as a data analytics and visualisation tool, and it can import data from a variety of sources and create representations in a variety of formats.


Sisense Fusion is an AI-powered software solution that consistently injects intelligence in the appropriate place at the correct time. Sisense is a business intelligence-based data visualisation solution that offers a variety of tools to help data analysts simplify difficult data and get insights for their companies and outsiders.

Sisense thinks that, in the end, every firm will be data-driven, and every product will be in some way tied to data. As a result, it makes every effort to deliver various data analytics tools to business teams and data analytics so that they may assist in transforming their organisations into data-driven enterprises of the future.

Sisense is simple to set up and use. It may be implemented in less than a minute, and data analysts can complete their tasks and acquire findings immediately. Sisense also allows users to export their files in a variety of formats, including PPT, Excel, MS Word, PDF, and others. Sisense also offers round-the-clock customer help in the event that a user has a problem. By completing a form, you can request a pricing quotation.

Sisense Fusion Embed enables you to safely integrate analytics into any ecosystem. Regardless of your technology stack, integrate analytics directly into your products. Deploy on any cloud or on-premises, with a single tenant or multi-tenant architecture, while maintaining complete control with end-to-end governance and security that is completely automatable through rich APIs.

Sisense democratises enduser reports, allowing anyone to gain access to the data and critical insights that help them run their business. To personalise BI report content, regulate report distribution lists, add filters to study just necessary details in particular groups, and experiment with frequency and format, use reporting software with extensive features. The end result is a report that is tailored to the proper audience and has the relevant information, making decision-making what it should be in a data-driven firm.

For each unique dashboard, business analysts must configure and maintain reports for each end-user (email content, subscription, and scheduling frequency). Business users rely on business analysts to make any necessary adjustments to report parameters, such as unsubscribing from a report. When the owner distributes the report to the firm, all users of a dashboard receive it in mass distribution.

This method is time-consuming and tiresome, and it permits data to be transferred to superfluous personnel, thus jeopardizing the company’s security policy and exposing client data to unauthorised staff.

Sisense has an answer. Sisense End-User Report Management, a BI reporting solution built inside the Sisense data and analytics platform, gives business analysts management over the analytics reports that are developed and disseminated. Business users may now receive pertinent information when (scheduling frequency), how (email, pdf), and where (laptop, mobile, tablet) they desire.

IBM Cognos Analytics

IBM® Cognos® Analytics combines reporting, modelling, analysis, dashboards, storytelling, and event management to help you better understand your organisation’s data and make more informed business choices.

IBM Cognos Analytics is a business intelligence platform powered by artificial intelligence that, among other things, provides data analytics. You can see and analyse data, as well as share actionable insights with anybody in your business.

Even if you have little or no experience with data analytics, you can utilise IBM Cognos Analytics because it interprets the data for you and provides actionable insights in clear English. You may also share your data in the cloud with other people and send graphics via email or Slack. You may also import data from spreadsheets, the cloud, CSV files, or on-premises databases, and merge relevant data sources into a single data module.

Administrators set up security and control data sources after installing and configuring the program. You may begin by uploading local files and incorporating visualisations into dashboards or stories. Modelers are the next step in the process for enterprise-level data. Report authors can generate reports for business users and analysts once data modules and packages are accessible.

The system is constantly maintained by administrators. You begin by checking in to the Welcome portal from your desktop or mobile device, regardless of whether you are an analyst, report author, data modeler, or administrator. There are coach marks in the user interface to assist you to figure out where you are.

You use several portions of the user interface depending on the task you accomplish. Access to the various portions of the interface is controlled by IBM Cognos Analytics capabilities, and you only see the interfaces that you work with.

Article Reference
  • Dougherty, J., & Ilyankou, I. (2021). Hands-On Data Visualization: Interactive Storytelling From Spreadsheets to Code. O’Reilly.

  • Schwabish, J. (2021). Better Data: A Guide for Scholars, Researchers, and Wonks. Columbia University Press.

  • King, T. (2021, October 1). The ultimate list of 21 free and open-source data visualization tools. Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors. Retrieved January 27, 2023, from https://solutionsreview.com/business-intelligence/the-ultimate-list-of-open-source-and-free-data-visualization-tools/

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