The Importance of Big Data Analytics in The World of Technology

The Importance of Big Data Analytics – Data is a collection of information that describes an event both in detail and in general. Data consists of structured data and unstructured data. In addition, there are various forms of data, some in the form of text, audio, video, images, numbers, and many others. 

Then what is meant by big data? Big data, as the name implies, is a very large collection of data and has certain characteristics that characterize it. Big data analytics is the process of extracting useful information by analyzing large data to produce certain information.

Big data is now familiar to most people, especially for people who are directly involved in the world of data. 

The development of big data is one of them influenced by the increasing development of increasingly sophisticated technology that produces so much data. Big data processing certainly cannot be separated from data science. 

Data science itself is a combination or combination of several sciences such as mathematics, statistics, computer science, business, etc. In this article, we will recognize several things related to big data analytics and its application. Come on, see with DQLab!

The Importance of Big Data Analytics

The Importance of Big Data Analytics in The World of Technology

Big data analytics is the process of processing or analyzing large data (big data). The Importance and purpose of big data analytics, among others, is to find hidden patterns, market trends, and so on so that they can be used for decision making by a company. 

Big data analytics is important to do so that the available big data is not just wasted, therefore it needs to be processed using several techniques and tools that suit your needs.

Big Data Analytics Steps

The process of data analysis, both small data and big data, certainly has several stages or steps that need to be taken so that the results of the analysis are not ambiguous. Big data analytics steps include data acquisition, which has two components namely 

  1. Data identification is carried out by analyzing two data formats, namely born digital and born analogue data. Born digital is information captured through digital media, while born analogue data is information in the form of images, videos, and other formats.
  2. Data collection , this data collection is accompanied by data storage identified as big data. The method for collecting and storing data is called storage and massive parallel processing (MPP)

Big Data Analytics Implementation

As we have previously known, many companies are currently using big data analytics, be it in the fields of banking, commerce, communications, media, etc. 

Big data analytics can be used to monitor financial markets through network activity monitors. Meanwhile, in the field of trading, big data analytics is used to monitor the stock market, ensure that there are no illegal trades, etc. 

The relationship between Big Data and Data Science

Big data is needed in data processing which aims to produce information for companies and individuals. To process big data, data science is needed. 

Data science is a science that studies data based on various fields of knowledge such as mathematics, statistics, programming, business knowledge, information systems and others. 

This is because it is very unlikely that someone will process big data manually, therefore this is where the important role of data science is in big data.

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