Big Data visualization uses powerful computers to ingest raw data derived from corporations. This data is processed to form graphic illustrations that enable people to comprehend large amounts of information in seconds.
Below are some top technologies you can use for data visualization.
Tableau
Tableau eliminates the need for an advanced scholarship of query languages to understand big data. The platform readily provides a clean visual interface for that purpose. The data visuals formed come in the form of worksheets and dashboards.
In the Business Intelligence Industry, Tableau is often preferred for its high speed of data analysis. Also, its visual and designing capabilities surpass many data visualization technologies. However, there are also a few limitations to point out. Tableau comes with a high cost, security problems, inflexible pricing, poor customer support, etc.
Plotly
Plotly is a Python library that is used for interactive big data visualizations. It enables users to create superior graphs much faster and efficiently.
Plotly is renowned for many benefits, including user-friendliness, scalability, lower costs, cutting-edge analytics, and ease of customization. On the downside, Plotly doesn’t have significant community support compared to other data visualization platforms such as Tableau. Plus, there is not a perfect means of putting its visualizations into a presentation.
Several big data types have been mentioned above, along with some of the best tools that can be used for mining, analysis, storage, and visualization. They are all developed by a variety of big data companies. As mentioned before, it’s important to research further before picking any specific big data tool or technique. Each of them is unique and can be applied to specific businesses.
