BI Tools: The Bridge Between Big Data and Understanding
There are many business intelligence (BI) tools that can be used for visualizing and analyzing large datasets, also known as big data. Some popular BI tools for big data visualization include:
- Tableau: This is a powerful data visualization tool that allows users to create interactive dashboards, charts, and maps. It can connect to a variety of data sources, including big data platforms like Hadoop and Spark.
- Qlik Sense: This BI tool allows users to create dashboards and visualizations using drag-and-drop functionality. It can handle large datasets and has connectors for various big data sources.
- Power BI: This Microsoft BI tool allows users to create interactive dashboards and reports using a variety of visualization types. It has connectors for big data sources like HDFS and Azure HDInsight.
- Looker: This BI platform offers a range of visualization options and allows users to create custom dashboards and reports. It has native support for big data sources like Redshift and BigQuery.
- Datawrapper: This is a tool for creating simple and clear charts and maps that can be easily embedded in websites or shared. It has a range of data import options, including support for big data sources like Google Sheets and Google BigQuery.
It’s important to note that these are just a few examples of BI tools that can be used for big data visualization. There are many other options available, and the right tool for your organization will depend on your specific needs and requirements.
The tools and technology utilised for the collecting, integration, visualisation, and analysis of unstructured data are collectively referred to as business intelligence. Effective BI tools are essential in today’s world of ever-growing free-flowing data in order to maximise the knowledge that resides in raw, unprocessed data. The goal of data visualisation is to identify patterns, trends, and correlations between various data sets that are impossible to study using only plain (non-graphic) data.