Know what is Data Visualization, its types and different tools

We are living in a world where images speak louder than words. Advanced technologies help companies do more than just present attractive images. They help them to collect data from different sources, which augments their business in a big way.

This is how one explains data visualization: Businesses collect an enormous amount of data from a number of sources. Though companies collect the required data quickly and efficiently, challenges arise while explaining this data in a way that makes sense to both business owners and stakeholders. This is the challenge that data visualization helps them to address.

Data Visualization techniques help organizations overcome this difficulty in presenting data. Data Visualization is a graphical representation of information and data. It lets you interact with the data and it goes beyond analysis.
Data visualization professionals use several visual elements like charts, graphs, and maps to provide an accessible way to see and understand trends and patterns in data.

As Data Visualization has shown its impact on many fields, it has resulted in a huge number of job opportunities for IT professionals. Today many professionals are looking to taking up Data Visualization courses to pursue a career in this field.

Different types of Data Visualization:
Now let us look into some of the different types of Data Visualization techniques.

Bar chart: Bar charts are very popular graph visualization technique that allows the audience to quickly scan them for quick information. They are used to compare two or more values in the same category.

Line chart: Line charts are a simple way to represent the data. They are used to plot the dependence of one variable on another.

Pie chart: Pie charts are represented in a circular statistical graphic, which is divided into slices that illustrate numerical proportion. Pie charts help in a way to organize the data to see the size of a component relative to the whole. They are good at showing percentage or proportional data.

Maps: Maps Data Visualization techniques are the most widely used in different industries. Maps can be used to position elements on relevant objects and areas – geographical maps and building plans, etc.

Scatterplot: Scatterplot is another Data Visualization technique which is a two-dimensional plot representing the joint variation of two data items. This technique can be used when there is a large number of different data points, and you want to highlight similarities in the data set.

Apart from the above mentioned Data Visualization techniques, there are many other such techniques that can be used to represent the data. You can check these here.

Data Visualization tools

As a huge amount of data is generated all the time, it becomes important to present such valuable data in a pictorial form that anyone can easily understand. So, to make this happen, certain Data Visualization techniques are available that can are capable enough to achieve this.

Now let us look into some of the Data Visualization tools:

1. Tableau: Tableau is one of the widely used Data Visualization tools. Many startups, as well as tech giants, rely on this tool to create several
   interactive visualizations to enhance their business. This tool provides a user-friendly interface and a rich set of library of interactive visualizations that make it the most preferred Data Visualization tool.

   1. Plotly: Plotly is also a very popular Data Visualization tool. The major benefit of using this tool is that it allows the users to create charts using programming languages such as R and Python.

2. Power BI: Power BI with its unique features has become one of the most powerful Data Visualization tools that can handle a huge amount of data. This platform allows users to create customized reports from different sources. This tool is fully compatible with Azure and Microsoft services and it can also directly connect to existing apps and drive analytics to custom systems.

3. Google Charts: Google Charts is a Data Visualization that runs on HTML5 and SVG. The charts created using this tool are interactive and some of them are also zoomable.

4. Infogram: Infogram is a Data Visualization tool that allows users to create and share digital charts, infographics, and maps. Coding skills are not required to use this tool.

Apart from the above mentioned Data Visualization tools, there are still many others available, that can be used to create useful visualization that add great value for companies. You can check here for these.

Conclusion: Data Visualization technique plays an important role in efficiently presenting complex data so that it can be understood easily.

We hope that this guide is successful in providing some valuable information about the Data Visualization technique to our readers.

Looking at the number of job opportunities provided by the Data Visualization techniques, many IT professionals are willing to learn this wonderful technology. So, such professionals can take advantage of these online courses(simpliv website) on this particular technology that proves to be very beneficial to them.
If you think anything more information can be added here then please send them in the comment section.