Big Data is a large amount of data collected in real-time in various formats and structures. Latest technologies have simplified data gathering from multiple sources. Data warehouses and data lakes can store this data on-premises or on the cloud.
However, the collected data is of no use to the business until it is analyzed. Basic data analytics tools like MS Excel cannot process Big Data due to the excess volume and complex nature of data. Big Data needs tools designed explicitly for the purpose.
Big Data Analytics is a type of advanced analytics where statistical algorithms, what-if models, and predictive analysis are used to identify the patterns, trends, and correlations between different elements.
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Big Data tool is a software used to clean, format, and process vast data in real-time. It is an analytical system capable of understanding complicated information and deriving actionable insights from it. Big Data tools help enterprises make data-driven decisions and increase returns.
The US economy faces around $3.1 trillion yearly losses due to poor data quality. The losses can be minimized by adopting a data-driven model and investing in the right Big Data tools.
Organizations have begun understanding the importance of Big Data Analytics tools and technology. An Executive Survey report by New Vantage says that 97.2% of enterprises are investing in Big Data and artificial intelligence.
Big Data tools can help businesses with the following:
Picking the right Big Data tools for the business is crucial. The accuracy of Big Data analytics and derived insights depends on the tools used for the process. In this blog, our expert talks about the best Big Data analytics tools preferred by numerous enterprises from around the globe. There are numerous tools available in the market. However, our list has been compiled based on the data and usage details collected from enterprises.
Apache Hadoop is one of the best open-source Big Data analytics tools in the market. It’s written in Java and is used to handle clustered file systems through the MapReduce programming model. Hadoop is cross-platform software used by more than half of the Fortune 50 companies.
Apache Storm is another open-source Big Data tool that offers the best real-time processing capabilities. The Storm has cross-platform abilities and provides distributed stream processing. It’s written in Java and Clojure and is fault-tolerant.
Atlas.ti is known as a comprehensive all-in-one software for research. It is used to research markets, understand user experience, and help with academic research and qualitative analytics. The software is available in two versions- desktop for on-premises use and web version for cloud applications.
Tableau falls in the category of leading tools for Big Data visualization and is available in three versions- Tableau Desktop, Tableau Server, and Tableau Online for cloud solutions. The open-source version of the software is known as Tableau Public. The data visualization tool works with data of all sizes and formats and provides real-time reports through the interactive dashboard.
Apache Cassandra is a free, open-source software that deals with vast volumes of data on several servers connected to one another. The NoSQL DBMS uses CQL (Cassandra Structure Language) to share information with the databases in the enterprise. Low latency is one of the significant advantages of using Cassandra.
Rapidminer is an open-source Big Data analytics tool that SMEs and large enterprises alike can use. It’s a perfect choice to use with data science models, predictive analytics, and new data mining models in the business. Rapidminer helps with data preparation, implementing machine learning, and deploying models.
Knime is Konstanz Information Miner, open source Big Data software used for analytics, reporting, and data integration. The tool helps integrate machine learning and data mining models. Knime is the best choice for research, BI, CRM, etc. It has a rich algorithm set and is still easy to use in the enterprise. It is a free tool that comes with GNU General Public License.
If you’re looking for quick and secure data platforms, Cloudera is the answer. Cloudera is free and open-source software that works with any data environment and encompasses Apache Hadoop, Spark, Impala, etc. Data collection, processing, managing, modeling, and distribution are easily performed using Cloudera.
Oracle Data Miner is used by data scientists for business and data analytics. It provides the easy drag and drop feature to make changes to the editor interface and customize the reports. The Big Data tool is an extension of the Oracle SQL Developer and deals with graphical workflows.
Apache Samoa stands for Scalable Advanced Massive Online Analysis and is an open-source software tool used for data mining and machine learning. It is a well-known platform that allows data stream mining of Big Data. Data classification, clustering, regression, and development of new ML algorithms can be performed using Apache Samoa.
Apache Spark is an open-source Big Data analytics tool that deals with machine learning and cluster computing. Spark has gained fame for being a lightning-fast analytics engine that can process massive amounts of Big Data with the utmost ease.
Apache Kafka is a publish-subscribe messaging system that sends messages from one endpoint to another. It works online and offline and prevents data loss by replicating the messages on disk storage and within the cluster. Apache works seamlessly with Spark and Storm to process and distribute Big Data analytics within the enterprise.
Apache Hive is an open-source cross-platform data warehousing tool used to facilitate data summarization and analytics in large volumes. It is fast and assists in managing large datasets with ease. Apache Hive manages data stored in other Apache systems such as Hadoop, Hbase, etc. It accepts input C questions and runs the analytics on a cluster to deliver the answer to the query.
Big Data management and analytics tools have been developed to handle Big Data operations in an enterprise. To summarize, big data management is useful for a retrospective analysis of enterprise data and its operations. It’s vital to consider factors like flexibility, scalability, licensing rights, cost of investment, and maintenance before choosing a suitable software tool.
Check out the trial versions of the software to get a better idea. You can work with Big Data solution providers to improve the quality and accuracy of data analytics and adopt the data-driven model in the enterprise. It helps optimize resources, increase productivity, and speed up returns.