Developer

This article includes essential knowledge about big data technology and what it is about. Its working process, types, advantages, the leading technologies, and prospects are all mentioned briefly. Read till the end to find out all about it.

Top 11 Big Data technologies in 2021

Big data technologies are specific data indicators, which help different companies gain insights and make better business decisions, leading to greater ROI. They even help online games like Book of Ra. Gaming spheres use big data technologies to detect scammers on the site and give a secure gaming environment to the players and fully immerse yourself in the world of gaming with the best gaming earbuds. But that's not it; there's way more to know, so keep reading.

joysticks

Source: https://pixabay.com/photos/game-console-sony-video-games-6603120/

What Is Big Data technology?

According to Gartner's Big Data Technology definition, it is a high-volume and variety of information, asserting cost-effective, innovative forms of information processing required for enhanced decision-making. One of the foremost big data technology advantages is that they can efficiently track and analyze massive data flow. Thus, it implies that with lots of data increasing exponentially in size with time, big data technology application becomes highly necessary.

Components of Big Data technologies

The traditional method of input processing proves ineffective when the data flow is humongous. That is when big data technologies become the need of the hour. Therefore, knowing about them is required for any business. They can be split into two big data technology components. They are as follows:

  1. Operational Big Data Technologies: It provides information regarding the info generated daily. They mainly include the online shopping transactions through Amazon, Flipkart, etc., or any other type of online payment, social media, booking online railway or movie tickets, or any info from some specific establishment used for analysis through big data technology-based software.
  2. Analytical Big Data Technologies: It is the real investigator of huge info. The most important work is the Analytical Big Data, the advanced adaptation of Big Data Technologies. Thus, it is quite complex as compared to the Operational one. The big data technology examples for the Analytical part include weather forecasting, stock marketing, time series analysis, and medical-health records.
Monitor

Source: https://pixabay.com/photos/stock-trading-monitor-business-1863880

The 11 Best Big Data Technologies

According to the current big data technology news and our survey, we have decided on the 11 top names that greatly influence the market and the IT sector. They are as follows:

  • Artificial Intelligence (AI): Artificial Intelligence is an interdisciplinary branch of science. It deals with the development of smart electronic devices that would carry out tasks that require human intelligence. AI is present everywhere now, starting from Apple's Siri to self-driving cars.
  • Hadoop Ecosystem: It is open-source software. It allows the processing of numerous data sets across many clusters of computers, with just simple programming models. It efficiently detects any problem at the application layer. There are five components available in the module. They are: Hadoop Common, Hadoop Distributed File System, YARN, MapReduce, and Ozone.
  • R Programming: R is well-designed programming software that includes various mathematical symbols and formulae and is helpful in the case of statistical computing in the programming language. This platform provides a wide range of functionalities like - classical statistical tests, linear modeling, non-linear modeling, time-series analysis, clustering, and graphical techniques.
  • MongoDB: MongoDB is a popular open-source information analysis tool and is document-oriented. It manages unstructured or semi-structured inputs for application developers and creates innovative products and services in the global market. It is also used to store them in JSON-like documents, thereby allowing dynamic and flexible schemes.
  • Data Lakes: It is a system of storage in raw format. It stores transformed input used for visualization, reporting, and machine learning. It can include several types of data - unstructured (emails, documents, PDFs), structured (rows and columns), semi-structured (JSON, logs, CSV, XML), and binary (audio, video, images).
  • Blockchain: Blockchain is the leading technology involved in cryptocurrencies like bitcoin. It distinctly stores structured information - once the data are written, it can never be altered or deleted. It makes it a highly secure and reliable ecosystem, perfect for big data technology in banking, finance, Insurance (BFSI), and other securities. It also has a role in the social welfare sectors like education and healthcare.
  • Predictive Analytics: Predictive analytics predicts future events based on previously stored info. It is powered by technologies including machine learning, and data, mathematical and statistical modeling. To formulate predictive models, one must know regression techniques and classification algorithms.
  • Apache Spark: It is a real-time input processing framework with built-in features for machine learning, SQL, graph processing, and streaming analytics. It can carry out operations like credit card fraud detection and eCommerce recommendation as well. 
  • Prescriptive Analytics: Prescriptive analytics is one of the most popular technologies in the current year. It guides and suggests the best possible courses of action directed towards favorable results in a given situation. For example, it can help companies respond to any market change.
  • In-memory Database: In-Memory Computing (IMC) is an example of an In-memory Database. Through it, several computers spread across various locations and share valuable input processing tasks. The info can be accessed instantly and at any scale.
  • Microsoft MCSE Data Management and Analysis: This big data technology will easily help you manage and analyse bulk data. SQL Management, Machine Learning, and Business Intelligence Reporting are essential tasks you can do using this software.
Developer

Source: https://pixabay.com/photos/software-developer-web-developer-6521720

Future Prospect

Big data technology in the future will not be the same as it is now. New and better ones keep emerging and replacing the existing ones for good. The change is taking place very rapidly as many big data technologies are stretching at a wider scale to meet the demands of the fast-developing IT industries. Hence, to keep at par with the fast-moving world, transforming classic info analysis models to revolutionize big data, new technology is needed. For more details regarding the same, you can go through authentic sites like Jigsaw Academy.

Final Overview

Thus, this article has tried to teach all the important points regarding Big Data Technology. The big data technology's meaning, usefulness and types, and every other required detail are mentioned here. Please write to us in the comments below whether this review proved effective to you and how. Also, remember to share it with others.

{"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}

About the author 

Thomas Glare

Thomas Glare has more than 10 years of experience in writing about IT technology and security issues. He always pays attention to details and his researches are magnificent.

You may also like:

George Firican

09/26/2022

Best Free Resources for Data Science

Best Free Resources for Data Science

George Firican

09/03/2022

How to Grow a Data Culture

How to Grow a Data Culture
>