HomeOperations8 best data visualization tools and frameworks

8 best data visualization tools and frameworks

In today’s data-dependent business environment, having the right tool for your visualization needs can ensure that insights are gleaned from data, and are put to use effectively. To that end, data visualization tools play a crucial role in data exploration and in sharing insights. When it comes to data visualization tools, there are a variety of options for you to choose from. 

While some tools take a jack-of-all-trades approach with the visuals offered, others offer limited but high-quality options. Here are 8 options for data visualization tools and frameworks to consider:

1. Grafana 

Grafana is an Open source, cloud-native data visualization platform. It is widely used in the Kubernetes ecosystem to visualize real-time streaming data from Prometheus. The dashboards being built can be easily shared between teams or inside the same team, fostering a collaborative environment. The annotation options go a long way in making your visuals easily digestible. You don’t need to migrate data with panel plugins; users can hook your data sources to a user-friendly API while building the dashboard.

Grafana offers an alerting system that ensures that any change is monitored. You can also combine, rename, summarize, and even perform calculations on the data from various sources, making rendering data simpler. 

2. Kibana

Kibana is a visualization tool that works as a part of the Elastic stack, also called the ELK stack. In the ELK stack, Logstash (L) works as a pipeline to feed log data onto Elasticsearch (E), which can be used for querying, analysis, and as a database. You can use Kibana (K) to visualize log data on Elasticsearch and make dashboards with visuals of the resulting insights. It is important to note that since 2021, new versions of Kibana are no longer open source.

3. Tableau

Tableau is extensively used by businesses that deal with large data sets, and here is why:

  1. The dashboard acts as a one-stop solution to all visualization needs, irrespective of the specialization of the user
  2. interaction with data via data connectors like Salesforce, SQL server, GraphQL, Dropbox, and Amazon S3, to name a few
  3. Allows for data blending from different sources, easy collaboration, and an extensive range of visuals you can choose from
  4. The ask data feature lets you interact with the data and ask queries in natural language, demanding no coding proficiency. There is, however, a need for SQL knowledge
  5. Reliable and easy-to-connect support for when it is required

You have to factor in the licensing cost before getting Tableau for your organization, which is higher than similar tools. There is, however, a Tableau public version that is free to use with limited functionality. Another consideration is that full mastery of the Tableau dashboard takes time due to all the options available.

4. Infogram 

Infogram is a great option for smaller businesses that require very little time to start producing engaging visuals. Here are some key features:

  1. Known for its ease of use, you can start creating infographics quickly with this tool
  2. Affordable pricing for smaller businesses, along with plans available for bigger enterprises too
  3. Offers a range of professionally designed infographics you can download and share with paid versions
  4. The drag-and-drop feature is handy and reliable, making creating infographics quick

With Infogram, the options accessible depend on your chosen plan; many useful features must be paid for. There is no mobile app, and collaboration can be difficult as there isn’t any support for external graphics.

5. Datawrapper 

Datawrapper was made for a journalist to display their findings as visuals in newsrooms. It offers a user-friendly interface that doesn’t need a visualization expert around. Here are the five steps involved in creating the visuals you require:

  1. Locating the source of data
  2. Process the data to feed only what is essential
  3. Upload data onto Datawrapper by copying and pasting
  4. You can select the kind of visual to display your insights
  5. The process of publishing the visuals on websites and newsrooms is simplified too

Datawrapper offers a simple interface for people without coding or prior data visualization experience. At the same time, there is a free version with limited options, and access to the full feature set must be paid for.

6. D3.js

D3 is an open-source JavaScript library used to make visuals on your browser. It is a powerful visualization tool that excels at visualizing large data sets. D3 use to make visuals using web standards like HTML, CSS, and SVG. Here are some key features:

  1. Data-driven feature of D3 allows you to retrieve data from different web nodes and servers. Static data can be used too
  2. The library hosts a range of tools to make visuals of varying complexities, from tables to complex GIS maps. You can even make custom visuals
  3. It supports large data sets and makes use of predefined libraries, this allows you to reuse code
  4. DOM manipulation allows you to manipulate the elements of your website and manage the properties of its handlers

D3 is an effective framework to consider, while you will need coding skills, its online community and the support they offer make this framework worth looking into.

7. Chart.JS

Chart.JS is an open-source, community-maintained JavaScript library for making HTML-based visuals. Chart.JS simplifies visualization for you by providing a canvas element for dynamic images, this allows you to make visuals quickly. Chart.Js also supports all browsers making it a great option if accessibility is a priority. The main visuals offered here are charts and graphs, which are of good quality and can be used when publishing your findings. Finally, the documentation and the community make starting off with Chart.JS a very easy process.

8. Plotly

Plotly is an open-source module of Python, it allows a host of quality charts and graphs that can be published.

Here are a few of its features:

  1. Hover tool capabilities allows you to detect outliers and anomalies in a large dataset
  2. Only a few lines of code are enough to create aesthetic visuals 
  3. Easy modification and exporting of the visuals created
  4. Allows you to extensively customize the visual to make it more meaningful and understandable.

While you need to know how to write code to use this framework, the quality of the visuals and the ease of use make it an easy recommendation.


Receive our top stories directly in your inbox!

Sign up for our Newsletters