10 Best Big Data Analytics Tools

Here are ten big data analytics tools that are commonly used by organizations and businesses to manage, analyze, and visualize large datasets:

1. Hadoop: An open-source framework that allows users to store and process large amounts of data using a distributed computing model.
2. Apache Spark: An open-source data processing engine that is designed for large-scale data processing and analytics.
3. Tableau: A visualization and business intelligence tool which allows the users to create interactive dashboards and charts from large datasets.
4. Qlik: A data analytics platform that allows users to analyze and visualize data from various sources in real-time.
5. Power BI: A cloud-based data visualization and reporting tool from Microsoft that allows users to create interactive reports and dashboards.
6. Google Analytics: A web analytics service that provides insights into website traffic and user behavior.
7. Splunk: A big data analytics platform that allows users to search, analyze, and visualize machine-generated data from websites, applications, servers, and devices.
8. IBM Watson: A suite of artificial intelligence (AI) and machine learning tools that can be used for big data analytics and other data-driven tasks.
9. Databricks: A cloud-based platform for data engineering, data science, and analytics that is built on top of Apache Spark.
10. Talend: A data integration and management platform that allows users to extract, transform, and load data from various sources into a central repository.

Data scientists can create anything from the mountain of big data collected by using big data analytics. We consider several technologies used in this big data research to be big data analytics tools. Big data refers to these enormous volumes of structured, semi-structured, and unstructured data. To learn more about their customers, businesses study and use these data.