What is Big Data?

Big data is a term used to describe a collection of unstructured, organized, and semi-structured large amounts of data that have been gathered by many organizations and contain a wide range of information. The Fresh York Stock Exchange (NYSE), for instance, produces around one terabyte of new trade data each year as an example of big data.

Big Data can also be described by the following categories:

  • Volume: - As it relates to the volume of data a firm or organization has, it is the most significant big data attribute. Terabytes, gigabytes, zettabytes, and yottabytes are units of measurement for data volume. The volume of the data is a very important factor in assessing its value.
  • Variety: - Another feature of big data informs us of the various data types obtained by various sources. As it affects performance, it is the biggest problem the data industry is currently facing.
  • Velocity: - It speaks about how quickly data is generated and processed. Any big data process must have high velocity. It establishes the true potential of the data. 

Importance of Big Data

Organizations may harness their data and use big data analytics to find new opportunities. This results in wiser company decisions, more effective operations, greater profitability, and happier clients. Businesses that employ big data and advanced analytics benefit in a variety of ways, including cost reduction, quicker and better decision-making, the development and marketing of new goods and services, etc. 


Latest technologies used in big data industry 

  • Artificial Intelligence: - It is one of the trending technologies. Big Data is playing a key role in the advancement of AI through its two subgroups: Machine Learning and Deep Learning. 
  • Machine Learning: - It refers to the ability of computers to learn without being monotonously programmed. Applying this to Big Data analytics enables systems to analyse historical data, recognize patterns, build models, and predict future outcomes.  Deep learning is a type of machine learning that mimics the working of human brain by creating artificial neural networks that use multiple layers of the algorithm to analyse data. 
  • Predictive analysis is a subpart of big data analytics, and primarily works towards predicting future behaviour by using prior data. It works by leveraging Data mining, Machine Learning technologies, and statistical modelling along with some mathematical models to forecast future events.  With the help of predictive analytics models, organizations can organize historical as well as the latest data to strain out trends and behaviours that could occur at a particular time.  
  • HADOOP: - It is currently one of the evolving big data tools. It is an open-source software framework developed for storing and processing Big Data by Apache Software Foundation. Hadoop processes and stores data in a distributed computing environment across the cluster of commodity hardware Hadoop is a profitable, fault-tolerant, and highly available framework that can process data of any size and format and is a very unfailing storage tool, also enables you to cluster several computers to analyze large datasets in parallel and more quickly. 
  • MongoDB: - Released in February2009, Mongo is an open-source software to store large scale data and allow to work with the data efficiently is a document-oriented, NoSQL database written in C, C++, and JavaScript and easy to set up. MongoDB is a profitable and highly reliable Big Data technology. It has a powerful query language that supports geo-based search, aggregation, text search, graph search, and more. 
  • R: - It denotes to an open-source project and programming language. A free software that is mainly used for statistical computing, visualization, and integrated developing environments like Eclipse and Visual Studio assistance communication. It has been increasing popularly over the past few years in universities and colleges. According to specialists, the R programming language has the most prominent language across the world. Data miners and statisticians widely use it to design statistical software, primarily in data analytics.  
  • Blockchain: - It is a distributed database system that stores and manages the transaction. This technology plays a crucial role in working towards reducing fraudulent transactions and helps increase financial security. 


In applying the analytical power of Big Data Technologies to their supreme potential, businesses can guarantee that their success in every aspect of operations will reach new altitudes, and they can continue to become more competitive in the marketplace.

About Rang Technologies:
Headquartered in New Jersey, Rang Technologies has dedicated over a decade delivering innovative solutions and best talent to help businesses get the most out of the latest technologies in their digital transformation journey. Read More...