What is Big Data Analytics? Everything You Need to Know

What is Big Data Analytics
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As the name suggests – BIG DATA – is basically the process of examining large and varied data sets so that it can be utilized by an organization to uncover hidden patterns, market trends, unknown correlations, customer preferences, and other useful information that can lead to more informed business decisions.

Business firms and enterprises that utilize Big Data Analytics usually reap a lot of benefits, covering the campaigns that are more effective, the finding of new income opportunities, better customer service delivery, more effective operations, and competitive advantages. Companies implementing Big Data Analytics have resulted in several business benefits because of it including effective improving customer service delivery, discovering new revenue opportunities, more effective operations, marketing campaigns, and competitive advantages. Companies have started looking out for more informed business decisions.

How Big Data Analytics Works and Key Technologies

Big Data analytics is a wide branch of technology that encompasses multiple entities governing its entire operation. There’s advanced analytics that applies to big data, but on the contrary, not a single rather several types of technology work together to help an organization get the most value from your information. Here are some technologies:

1. Data Management

Data constantly flow in and out of an organization, it’s important to establish repeatable processes to build and maintain standards for the quality of data. Data should be of high quality and well-governed before its reliable analysis. Then this reliable data is established as a master data management program that gets the entire enterprise in a flow.

2. Data Mining

It helps in the examination of large amounts of data to discover regular patterns in the available data. This data analysis is further used for various complex business questions. There is data mining software for such tasks. With the help of this software, we can easily sift through the repetitive noise and chaotic data, pinpoint more relevant data, use extracted information to assess likely outcomes, and then accelerate the pace of making informed decisions.

3. Hadoop

Hadoop is open-source software that has been designed to store a large amount of data and run applications on clusters of commodity hardware. It is now acting as the most widely used and key technology for doing business due to the constant increase of data volumes and varieties. The biggest benefit of using Hadoop is that its free and uses commodity hardware to store a large quantity of data.

4. In-memory Analytics

In this analytic, your data is analyzed from your system memory instead of your hard disk so that you can derive immediate insights into your data and act accordingly, quickly.

This technology is able to remove the analytical processing latencies and data preparations for testing new scenarios and thus creating models; bigger organizations cannot stay agile and make better business decisions without all these tasks. This analytic also enables them to run iterative and interactive analytics scenarios.

5. Predictive Analytics

This technology uses data, statistical algorithms, and machine-learning techniques for identifying the similar traits of future outcomes based on previous and historical data. This includes fraud detection, operations, risk, and marketing. The best assessment will lead the organization to a more confident environment of making the best possible business decisions.

6. Text Mining

Text data is analyzed from the web, comment fields, books, and other text-based sources using text mining technology. This leads to uncovering insights that go unnoticed. This technology utilizes machine learning / natural language processing technology to dive through documents – emails, Twitter feeds, blogs, competitive intelligence, surveys, and more in order to help the organization analyze large amounts of information and discover new topics and term relationships.

Trends in Big Data Analytics

Since the beginning of BIG DATA, it has started to change the way this world does business which also means it is changing technology and business practices.

Robert L. Mitchell, Computerworld contributor and chief editor of TechBeacon.com made a list of all the trends in the Big Data Analytics field which is based on input from IT consultants, leaders, and industry analysts:

  • Big Data Analytics in the cloud
  • Hadoop: The new enterprise data operating system
  • Big Data lakes
  • More predictive analytics
  • SQL on Hadoop: Faster, better
  • More, better NoSQL
  • Deep learning
  • In-memory analytics

The increasingly widespread use of Big Data Analysis solutions clearly indicates that Big Data is not just a craze rather it has now become a business practice that is here to stay because of the insights it provides to enterprises. These enterprises utilize these analytical tools to gain a competitive edge, improve sales and marketing team performance, increase revenue, and make proactive data-driven business decisions.


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