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10 Most Helpful Tools For Big Data Professionals

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Paulo Guimarães

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Advanced problems need advanced solutions, this is what we all have heard at some point in time. Businesses also require modern solutions to cater to the market challenges. But, what do businesses require the most? Well, ‘Data’ has become the main focus of every organization irrespective of its size. As users are growing at rocket speed, so does the data which needs to be carefully collected and analyzed for the business purpose.

To leverage this large amount of data and to use it for business growth companies are using Big Data. It assists, amongst other things, professionals to approach their target audience and potential customers with a deep understanding of their immediate needs.  This made organizations to invest Big Data Analytics market that is going to reach US$ 105.08 Billion by the year 2027 at a CAGR of 12.3%.

So, to channelize this data into meaningful information for the companies few advanced tools are required. These development tools integrate and streamline the organization’s work. So, let’s get started! Leverage these 10 Big Data tools.

Apache Hadoop

According to Finances Online, Big Data promotes 13% more effective research and development, 17% improved business efficiencies, and 12% better product/services. It proves helpful in faster innovation, growth, and development. This is possible through the processing of a large amount of data with the support of Hadoop. This tool can process a huge amount of data and it is a 100% open-source framework.

The great thing about Hadoop is that it improves authentication, promotes faster and flexible data processing, offers the ecosystem for meeting the analytical needs of professionals, and helps in the seamless integration of other modules to work with this tool.

Apache Spark

This Big data tool is great to work with numerous data stores and HDFS. It seamlessly integrates with Apache Cassandra and OpenStack Swift. This tool is capable of handling real-time and batch data. Even the processing of the data is quite fast as compared to traditional disk processing. The Spark Core is the heart of any project and facilitates scheduling, transmitting distributed tasks, supports Input/output functionality, it runs easily upon the single local system for making testing and development seamless, and enables professionals to write down the applications in distinct languages.

Apache Storm

To process the ‘unbounded data stream’, this real-time framework helps in channelizing the company’s database. It also supports the versatile type of programming languages and real-time streaming of the data. Storm’s incredible features include scalability, guaranteed processing of Tuple, support the DAG topology, runs on JVM platform, consists of ‘fault-tolerance’ feature, and much more.

Cassandra

Another open-source and free big data management tool. Apache Cassandra uses the Cassandra Structure Language or CQL to interact with the database of an organization. It has a ‘NoSQL DBMS constructed system’ to manage the data spread across the commodity servers, used by high-profile companies like Facebook, Accenture, Honeywell, etc. Cassandra also offers many benefits like simple ring structure, log-structured storage, massive data handling system, linear scalability, etc.

Cloudera

The companies that require the data for versatile purposes can use this tool to create a distinct data repository. This tool was developed in 2008 and is a great support system for Apache Hadoop. Cloudera’s combination with Apache Hadoop will assist in the reduction of the business risks and transforms the organizational work 360-degrees. It will help businesses in gaining a competitive advantage over their competitors. Cloudera can be deployed and managed across Google Cloud Platforms, AWS system, and Microsoft Azure.

Flink

Apache Flink is again an open-source framework and a robust Big Data tool. This functions as the distributed engine for the ‘stream processing’ and carries out the stateful computation of the organization’s data. The beneficial thing about this tool is that it runs smoothly in all the ‘cluster environments’ like Apache Mesos, Hadoop, Kubernetes, and YARN. Also, this tool quickly recovers all the data failures, performance of tasks at the memory speed, supports flexible windowing, includes the libraries for all the commonly used cases, and much more.

HPCC

This Big Data tool is developed by LexisNexis risk Solution. It uses a single architecture, single platform, and single programming language for data processing. HPCC offers higher redundancy, optimizes the codes for automatic processing, used for complex data processing over ‘Thor Cluster’, renders enhanced performance and scalability, and the Graphical IDE simplifies the development, testing, and debugging.

Knime

Konstanz Information Miner or Knime is an open-source Big Data tool that is used for research, integration, data analytics and mining, enterprise reporting, CRM, business intelligence, and text mining. It seamlessly operates over OS X, Linux, and Windows. Moreover, it has a very ‘rich algorithm’ set, encourages automation, integrates with other languages and technologies, organizes the workflow, etc.

Lumify

This secure and scalable Big Data open-source tool is great for integration, analysis, and visualization. Primarily the features it includes are automated layouts, search for full text, integration with the mapping systems, collaboration in real-time, it has a dedicated open-source community of data professionals,  supports visualization in the 2D, and 3D graphs, and performs well with the AWS system.

MongoDB

MongoDB is best to work with the databases that frequently change and vary in data as they are unstructured or semi-structured. It acts as a contemporary alternative to the databases. This Big Data tool is best used to store data from CMS websites, Mobile Apps, product catalogs, and much more. One thing about MongoDB is you cannot get started with this tool instantly as Hadoop. You need to learn this tool from very basics and work on its queries too.

Bottom Line

The above compilation of the best Big Data tools supports in carrying out different integration and analytics functionalities for the organizations. These tools truly promise great outcomes once used according to the business’s requirements. Companies can gain a competitive edge by using these tools and changing the business scenario for the market. As these tools are open-source and a few of them are free, so professionals can find them in their respective technological communities too.

 

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