When used wisely, data is a true golden resource for various business purposes across all industries. However, raw data isn’t useful in itself.
It’s hard to understand it without context and practically impossible to grasp as far as large datasets are concerned.
Data must be processed and analyzed to offer meaningful insights and that’s where data visualization comes into play - it helps to visually represent specific information within a given dataset.
Visualization makes data more accessible and allows businesses to draw insights to make informed decisions. With data visualization tools, software engineers dig deep into Big Data and extract relevant information in a way that is useful, making it a necessity for any data-driven business.
There are a number of data visualization tools available on the market. In this article, we present a list of the tools we consider the best. They differ in the feature sets they offer and thus some will be better for particular use cases than others.
If you’re looking for a BI analysis tool without a steep learning curve, then Tableau is a great choice. It’s one of the most popular solutions that enables the creation of interactive dashboards with charts, maps and graphs based on a variety of different sources.
It offers excellent visual image capabilities. Tableau is great for artificial intelligence, machine learning, and Big Data applications. It integrates with multiple advanced databases, including Teradata, SAP, Amazon AWS, and MySQL. It also offers a CRM software.
Cons of Tableau? The vast pool of features may somewhat slow down the adoption. Also, it is rather pricey in comparison to other market options. However, Salesforce, its owner, also offers a free version called Tableau Public, but users should bear in mind that anything they create with this option will be available to everyone.
Microsoft Power BI
Power BI is Microsoft’s powerful contribution to the pool of data visualization tools. This excellent business solution allows to extract information from raw data and structure procedures dependent on it. It can aggregate data from a variety of resources, including marketing and sales services, to produce reports, predictive analytics and self-service analytics.
On top of that, it natively integrates with other Microsoft services that are useful in creating visualizations, dashboards and reports. It’s simple and suitable for a non-technical audience. It can be installed in the cloud, or on-premises and is mobile-friendly and acts as a centralized repository for all your data.
Power BI is certainly one of the best and, as it supports Salesforce, Teradata, Oracle, PostgreSQL, Google Analytics, Azure and numerous other databases, it’s also one of the most complete tools.
Power BI offers a free trial and two valuing plans - overall, it’s more affordable than most of the tools on our list. There is also a free version with limited features. It’s only downside is that it cannot work with multiple and varied datasets.
Google’s free tool for data visualization easily integrates with other Google products and third party solutions. DataStudio is one of the few solutions available completely free of charge in its full functionality. It’s easy to get and quick to deploy and Google also regularly releases new features.
DataStudio is highly customizable and dynamic; it will automatically update your reports if there are any changes in data sources. It is perfect for marketing and sales analytics.
One of the disadvantages of the platform is a steep learning curve when it comes to using specific data sources. If you need support with the tool, you will have to consult other users, as Google doesn’t provide customer support for this tool. Using third-party sources may also be problematic as they sometimes disconnect from the platform.
The platform is based on HTML5/SVG technology and, of course, is compatible with other Google products. It easily integrates data to produce visually attractive graphs and charts. Users can choose from 18 different types of those charts for great visualization efficiency.
What may be inconvenient about the tool is the lack of customization options. Users must also be connected to the internet to prepare their visualizations.
Project Jupyter is among the top rated open-source solutions for teams proficient in one or more programming languages. The creators of the project aim to offer open standards and web services for interactive computing that work with all programming languages. Thus, Jupyter allows to share documents that, in addition to different types of visualizations, contain live code, equations or narrative text.
The solution is used by organizations like IBM, Google or Berkeley in machine learning, data transformation, data cleansing, numerical simulation and many more functions.
The Jupyter project features JupyterLab (an interactive development environment), Jupyter Notebook (an app dedicated to sharing computational documents) and Voilà (a dashboard for presenting the documents). The only downside of the tool is lack of support for collaboration.
If you’re looking for an open-source data visualization tool, then Plotly is your best option. It enables complex visualizations thanks to full integration with programming languages like Python, Matlab or R. It can be installed in the cloud and on-premises.
It’s an excellent solution for organizations looking to visualize data in an interactive way and further collaborate on it online. The visualizations are easily shareable thanks to server hosting (every graph will have its own URL). Plotly offers a highly-interactive interface and high-quality image export.
The downsides of Plotly? The free version is rather limited; you’d still have to pay to unlock its full potential. It may also be slow at times, and some of its display elements may be distracting, but otherwise the interface is easy to use.
Grafana is another open-source option for data analytics that creates informative graphs and visualizations, also from time-series database data. With the free option, engineers can display, query and examine logs, metrics and datasets from any location.
The Grafana Enterprise Stack, which is a paid version, permits companies to analyze company data sources, benefit from centralized authentication and expand on permissions as required. The team also offers onboarding for core staff and 24/7 support.
Grafana also has a cloud platform for logging and metrics, powered by OpenSaas. If you choose this quick, fully-controlled and easily-accessible option, you’ll be able to enjoy all the features of Grafana while Grafana Labs will host and manage the software for you.
Another good open-source data visualization tool is Chart.js. Its vast community of contributors is certainly one of its greatest advantages. Chart.js offers highly responsive charts (there are eight different types: line, bar, bubble, scatter and more) displayed in the browser. It has a solid ecosystem with wrappers for Vue, Ember, React, Omi, Angular and more.
Qlik View & Qlik Sense
If you want to boost your organization’s BI capabilities, Qlik View and Qlik Sense will certainly help with the discovery efforts. The latter is an advanced, AI-powered platform that, in addition to visualizations, offers:
- Mobile analytics
- Data modeling
- Advanced governance features
- Interactive dashboards
which helps businesses to uncover various patterns. At the same time, the tool can be used by both expert and beginner data analysts.
Qlik view is it’s predecessor, also a BI analysis tool, but it offers fewer features.
On the downsides, QlikSense has a steep learning curve, as its workflows are sophisticated, and it uses many and large data sources for analytics. The platforms come in different tiers, so businesses of any size will find a suitable option, but must bear in mind that robust functionality comes at a high price.
D3.js is for developers’ use only; it has a steep learning curve and requires good familiarity with the tool in order to create some of the charts, as they may require additional data processing. It does offer good documentation, but doesn’t offer support. Alternatively, if you lack development skills, it’s possible to use certain apps (eg. NVD3) to create charts with D3.js.
Google’s Looker has a unique modeling language and uses the fastest analytic databases to yield accurate results in real-time. It is a simple, browser-based data visualization tool that allows developers to select, customize and create diverse interactive visualizations, as well as graphs and charts.
The visualizations and models are indeed easily customizable - also for beginner programmers with limited SQL knowledge. ILooker is straightforward and easy to navigate. In addition, it can be integrated with big data databases and platforms.
The downside? The simple platform doesn’t offer much flexibility.
If you have ever used Hubspot or Databox for your sales and marketing efforts, then Zoho Analytics will feel familiar.
It’s a good option for those organizations that want to visualize business intelligence and report on profits, revenue, sales, marketing and pipelines via intuitive and user-friendly dashboards, charts and graphs. It enables easy collaboration across and outside the organization - users can share reports and dashboards with a few clicks.
Zoho Analytics permits the use of external sources, such as MySQL, Oracle and Google Sheets. The platform has several pricing tiers for different operational scale and feature requirements. It also offers a free version that can be used to create a limited number of reports, which can be a good testing option.
Infogram is among the widely-adopted tools - its customers include companies like MSN, Deloitte, Nielsen, SKyscanner and more. The web-based solution makes visualizing data and creating infographics anything but difficult (it features a drag-and-drop editor).
It’s an excellent option for creative professionals that work with data to produce infographics and shareable reports. The latter can be incorporated and developed and provide metrics on viewer interaction.
Infogram offers various pricing tiers, including a free version as well as one for enterprises with robust features.
With a super clean and intuitive user interface, Datawrapper is certainly one of the easiest to use from the options available on the market. It’s a no-code, browser-based tool, so it’s perfectly suitable for individuals without coding skills and those less tech-savvy.
Apart from charts and graphs, it also allows to create responsive maps and infographics from Google Sheets, Excel, PDFs, CSV and web sources. The Guardian, Wall Street Journal, The Washington Post, Buzzfeed and many other organizations use it, as it’s perfect for working in a fast-paced environment.
Datawrapper offers custom layouts and a wide variety of charts and graphs to choose from, but it is somewhat limited when it comes to customizing fonts and colors. On the downside, the tool requires manual data uploads as it doesn’t integrate with external sources.
The choice of data visualization tools is vast and every organization. All the solutions we recommend will help teams make informed decisions, as they gain at-a-glance insights and better understanding of business-critical data.
Here’s a quick recap at our top recommendations and how they compare:
- Tableau: one of the most popular BI solutions without a steep learning curve,
- Microsoft Power BI: a robust solution that aggregates data from a variety of resources; offers predictive analytics
- Google DataStudio: highly customizable, dynamic and available for free
- Google Charts: a free product with unmatched cross-platform compatibility
- Jupyter: a top-rated, open-source solution for programmers
- Plotly: one of the best open source options for organizations, offering easy-to-share visualizations
- Grafana: an open-source data visualization tool with a dedicated enterprise version
- Chart.js: an open-source data visualization solution with a solid ecosystem and a vast community of contributors
- Qlik View & Qlik Sense: and advanced, AI-powered BI platform,
- D3.js: an advanced tool for developers only
- Looker: a browser-based data visualization tool that offers a unique modeling language
- Zoho Analytics: highly-collaborative BI platform, similar to Hubspot and Databox
- Infogram: widely-adopted, browser-based, perfect for creatives
- Datawrapper: super intuitive, no-code, browser-based tool, perfect for the tech-unsavvy