4 Data visualization tools to master in 2022

Data Visualisation is one of the pillars of Data Science and is a highly demanded skill

A human brain is a visual machine. It is faster for us to process visual information than to process scribbled information. The days of static presentations are over. The rise of data science courses has made all budding enthusiasts aware of the latest data visualization tools. This way of presenting data makes more sense to us. That is how businesses can identify patterns and trends more easily, which leads to better decisions. 

Most data analytics courses teach basic data visualization tools (usually already found in Excel, or otherwise) to aspiring data scientists.

These tools will help you succeed in the field of data science and analytics.

You can begin your data science and analytics journey by mastering these four data visualization tools.

TABLEAU

The Tableau visualization tool is one of the most powerful, reliable, and easy-to-use tools on the market.

The software eliminates the need for coding thanks to its drag-and-drop functionality. To illustrate everything in a graphical format, it pulls data from Excel spreadsheets, texts, and even PDFs.

While Tableau Desktop uses a few programming languages, the majority of the code is written in C++. In the end, you will be able to develop dashboards that combine all of your results for a "one-time view". A real-time change can also be made to the outcomes, which will reflect the change instantly. By doing so, you can avoid having to rework the same data from scratch.

Tableau offers a 14-day free trial here.

MICROSOFT POWER BI

Microsoft's Power BI is a credible business intelligence software that keeps everything at your fingertips. With its super-user-friendly interface, it can extract data from any existing source.

It is interactive, so final touch-ups can be made at the last minute without having to start over.

Several programming languages are supported by Power BI, including DAX, M, and R. DAX. 

Using the tool, on-premises and cloud-based data warehouses can be combined. The data is extracted from cloud-based sources, such as Salesforce CRM, and automatically restored. A wide selection of diagrams and illustrations is available. Looking for more information? Here's a link to a free trial.

PLOTLY

Plotly allows you to style interactive graphs and charts in a Jupyter notebook. It helps users understand prevalent data and convert it into beautiful, easy-to-understand visual representations.

Plotly is constructed using Python and the Django framework, with a front end using JavaScript and the visualization library D3.js, HTML, and CSS.

Additionally, the software supports API libraries for Python, R, MATLAB, Node.js, Julia, and Arduino, as well as a REST API. This allows multiple team members to share documents online.

QLIK

The tool works well even with large datasets without any hiccups. Using various types of plots, Qlik automates the data and blends it into interactive information. Hardware costs aren't too high either.

C++ is used to encrypt QlikView Desktop and QlikView Server services. Software is supported by Microsoft Windows and Microsoft Windows Server machines for accessing the Qlik Management Console (QMC) and hub: Microsoft Internet Explorer 11, Microsoft Edge, and Google Chrome.

With minimal supervision and several checks, it modifies the data according to your needs accurately. You do not need any prior training to use this software. Interested in exploring more? Take a look here to see how it works!

FINAL WORDS

There is a high demand for data scientists, business analysts, and data mining experts (among others). You'll be able to stay ahead of the curve easily if you equip yourself with one of these tools. 

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