Best big data tools for data visualization

Introduction:

If described best, data visualization is known as the graphic representation of data. What data visualization involves is producing such images that can communicate the relationship among the data being represented to viewers of the images. A systematic mapping approach is used between graphic marks and data values in the creation of the visualization to communicate.
To visualize data, there are a variety of tools used and these tools are known as data visualization tools. It has been found out that using any of the best data visualization tools have greatly helped in dealing with huge data. So as a data scientist, it is very important for you to have a know how of these data visualization tools. Thus, today our topic of discussion is some of the data visualization tools that are used to represent data.

Data visualization tools:

Here we are going to mention six data visualization tools that can be used.

Tableau:

Tableau is one of the most powerful and fastest-growing data visualization tools that is used frequently in the Business Intelligence industry by tableau desktop specialist person. With this tool, you can without any inconvenience convert raw data into an understandable format. Furthermore, with tableau, data analysis is very fast and all of the visualizations created are in the form of dashboards and worksheets. Thus using tableau eases your life by converting huge data into a form that you can use to deduce results.

Python:

Python is an interpreted, high-level programming language released in the year 1991. This programming language is a general-purpose language use for developing desktop GUI applications. Besides that, Python is also used for developing different websites and web applications. Python being a high-level programming language lets you focus on the core functionality of the applications. This is done by taking care of the common programming tasks. It shows quite a productivity and is speedy and provides user-friendly data structures.

R:

R is also a programming language and one of the best business intelligence tools there is. It is a free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. Being a Statistical language, it has become a very popular tool for the data scientist. Thus, making this language widely used by statisticians and data miners to develop statistical software and data analysis.

D3.js:

D3.js is a JavaScript library that is being used frequently to manipulate documents based on data. You can create a variety of visual representations of data by using HTML, CSS, and SVG. These visual representations can be then viewed on any modern browser. Furthermore, D3.js also provides some effective features for the purpose of animations and interactions. With that, it can also be used to enhance your existing dashboards. It creates visualizations by binding data and graphical elements to the Document Object Model. In other words, it associates the data with the DOM and also allows you to manipulate, change, or add to the DOM.

Google Charts:

Google charts are also used to create visualizations and are known to be an interactive Web service. Through Google Charts, you can create graphical charts using the user-supplied information. The user first supplies all the required data and then a formatting specification that is expressed in JavaScript is embedded in a web page. Then in response, the service sends an image of the chart. Thus we can say that with Google Charts, your purpose of enhancing web applications is accomplished by adding interactive charting capability.

Watson Analytics:

Watson analytics, like any of the above mentioned BI tools, is also an equally competitive and efficient tool for data visualization. Precisely, it is a smart data discovery solution that is available on the cloud. It is used to guide data exploration and can also automate predictive analytics. With that, it is also used to create effortless dashboards and infographic creation. Thus with Watson Analytics, you become capable of getting answers and new insights that can help you make confident decisions in less time.

Conclusion:

By taking a look at all of these six business intelligence tools, we can say that each tool is effective and has its own functionalities and advantages. Hence, in the end, all these tools can make your life easier by dealing with data in a more efficient manner. So we would suggest you learn these popular data visualization tools in the most effective manner and make your life easier by putting in less effort to deal with huge data.