1. OpenRefine

This is a popular data analysis tool that is suitable for all kinds of analysis-related tasks. This means that even if you have many different data types and names, this tool can group items using its powerful clustering algorithm. Once the clustering is completed, the analysis can begin.

2. Hadoop

Big data and Hadoop are inseparable. This software library and framework can distribute large data sets across computer clusters using simple programming models. It is particularly good at processing large amounts of data and making it available to local devices. As the developer of Hadoop, Apache is also constantly enhancing this tool to improve its actual effectiveness.

3. Storm

Storm, also from Apache, is another great real-time computing system that can greatly enhance the processing of unlimited data streams. It can also be used to perform a variety of other big data-related tasks, including distributed RPC, continuous processing, online machine learning, and real-time analysis. Another big advantage of using Storm is that it integrates a lot of other technologies to further reduce the complexity of big data processing.

4. Plotly

This is a data visualization tool that is compatible with languages ​​such as JavaScript, MATLAB, Python, and R. Plotly can even help users who do not have the skills or time to write code to complete dynamic visualization processing. This tool is often used by the new generation of data scientists because it is a business development platform and can quickly understand and analyze large-scale data.

5. Rapidminer

Another essential tool for big data processing, Rapidminer is an open source data science platform that works through visual programming mechanisms. Its functions include modifying, analyzing and creating models, and can quickly integrate results into business processes. Rapidminer is currently attracting much attention and has become a reliable tool in the minds of many well-known data scientists.

6. Cassandra

Apache Cassandra is another tool worth paying attention to because it can effectively and efficiently manage large-scale data. It is a scalable NoSQL database that can monitor data in multiple data centers and has been used by well-known companies such as Netflix and eBay.

7. Hadoop MapReduce

This is a software framework that allows users to write applications that process large amounts of data concurrently in a reliable manner. MapReduce applications are mainly responsible for completing two tasks, mapping and reducing, and thus provide a variety of data processing results. This tool was originally developed by Google.