In this golden age of information, with more than 2.5 quintillion bytes of data produced by humans every day, harnessing insights from data has become a gold mine for organizations. Making informed decisions and capitalizing on opportunities is crucial to get ahead of competitors in this business world and businesses that realize this invest heavily in data analytics. Data is now a key business asset that is revolutionizing the way companies operate, actors most sectors and industries. Data analytics can help companies better understand their customers, products and what’s working in their business strategy, and what needs to be put in the closet. Today, many data analytics techniques use specialized systems and software that take raw data and uncover patterns to extract valuable insights from it. Here are some of the best open-source data analytics tools for 2023.
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Best Open-Source Data Analytics Tools for 2023
Apache Spark is one of the best open-source data analytics tools for 2023. It is a cluster computing framework that is used for real-time processing. It provides high-level APIs in Java, Scala, Python, and R. Apache Spark runs on Kubernetes, Apache Mesos, standalone, Hadoop, or in the cloud. Top companies including Oracle, Verizon, and Visa use Apache Spark for real-time processing of data with ease of use and speed.
Konstanz Information Miner (KNIME) is a free and open-source data analytics tool built for analytics on a GUI-based workflow. It has two software- the KNIME analytics platform and the KNIME server. With this open-source data analytics tool, you can work all the way from gathering data and creating models to deployment and production. Top companies including Siemens, Deutsche Telekom, and Novartis use KNIME as their data analytics tool.
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RapidMiner is a suite of cloud-based products that can be used to create an integrated platform for end-to-end analytics. It is awarded as a Visionary in the 2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. This open-source data analytics tool has various products including Studio, GO, Server, Real-time Scoring, and Radoop. Top companies including BMW, HP, and Sanofi use this tool for their data processing and Machine learning models.
Apache Hadoop is one of the popular open-source data analytics tools in the market. It is a software framework used for storage and processing big data across clusters of computers. It allows you to write and test distributed systems efficiently and it automatically distributes the data and works across the machines. Companies such as Marks and Spencer, Royal Bank of Scotland, and British Airways use Hadoop for performing quantitative analysis.
Pentaho is an open-source data analytics platform for data integration and analytics. With Pentaho, you can extract, prepare and blend your data seamlessly. The visualization and analytics feature will change the way you run your business. Although it is open-source, the enterprise edition is not free to purchase. Companies such as The American Red Cross, JPMorgan Chase, and Wells Fargo use Pentaho for their analytical needs.
These are some of the best open-source data analytics tools for 2023. Every business regardless of size and industry needs data analytics if they need to survive in this digital world. At Speridian, we understand how to translate organization-wide data into actionable insights and use business intelligence and data analytics for developing new products and services for enhanced customer experience. Our expertise in technologies like the Internet of Things (IoT), Machine Learning (ML), Artificial Intelligence (AI), Advanced Predictive Analytics, Azure Data Lake Analytics, Azure Synapse Analytics, Azure Log Analytics, and Cloud empowers customers to leverage the latest and greatest in analytics for improved decision making to uncover new opportunities. Contact us to leverage the power of analytics and boost your growth and revenue.