Advantages of Big Data Analytics

Advantages of Big Data Analytics

Advantages of Big Data Analytics

Collecting lots of diverse types of data very quickly does not create value. You need analytics to uncover insights that will help your business.

Big Data grows daily through an inexhaustible data source such as the Web, databases, click tracks, social networks, call centers, geospatial data, semi-structured data (XML, RSS), audio and video, the data generated by the thermometers, data of navigation of websites during a certain time, among others.

There are some benefits of Big Data analysis for organizations; Through a survey conducted by TDWI (The Data Warehousing Institute) in relation to the marketing area, when asked: "Which of the following benefits would occur if the organization implements some form of Big Data analysis?". 61% responded that it influences socially; 45%, there will be more business views; 37% leaned toward automated process decisions in real time; 29% mentioned that planning and review would be improved, and 27% said consumer behavior would be understood.

The purpose of data analysis is to examine large amounts of data with a variety of classes, in order to discover information that is relevant and useful to the company, so that it allows you to make the best decisions and obtain competitive advantages compared to others from his class.

Data analysis is performed using database technologies such as NoSQL, Hadoop, and MapReduce, which support Big Data processing.

For data management it is necessary to have two basic components, both hardware, and software; With respect to the former, there are technologies such as Mass Parallel Processing (MPP) architectures, which quickly aid in their processing. For the management of unstructured or semi-structured data, it is necessary to resort to other technologies; It is here that new techniques and technologies such as MapReduce or Hadoop appear, designed for the management of structured information, unstructured or semi-structured.

Today, Hadoop shows significant advantages over Structured Query Language (SQL) databases, which are presented as a design for structured information management, where the data resides in relational tables that have a defined structure since it was designed to Unstructured or semi-structured information such as text documents, images and XML files.

Hadoop can handle all types of disparate systems data: structured, unstructured, log files, images, audio files, email files, communications, almost anything you can imagine, regardless of their native format.

Hadoop is a framework used to write and run distributed applications that allows you to process large amounts of data. Hadoop consists of two modules: Hadoop Distributed File System (HDFS), and HadoopMapReduce.

Hadoop Distributed File System (HDFS: Hadoop Distributed File System): A highly scalable, scalable file system with a distributed architecture; Can store up to 100 TB in a single file, which is not so easy on other types of file systems. In addition, it gives the appearance of being working in a single file, but what you really have is that they are distributed on several machines for processing.

When HDFS was created, three objectives were proposed:

• Allow files to be processed in sizes from gigabytes (GB) to petabytes (PB).
• Read data at high speeds.
• Ability to be executed in a machine, without requesting special hardware.

Said all this, the primary goal of big data analytics is to aid companies in making more informed business decisions by enabling them to access a large volume of transactional data. This provides them with the opportunity to drive innovation and to make the best possible decisions based on these data results. Make informed predictions and deliver actionable intelligence. Find patterns and relationships while lowering costs. Gain business insight from a steady influx of information.

Companies that know how to take advantage of Big Data analytics can improve their strategy and thus stay in the market position, because it will use new knowledge, with the large volume of data or information that handles daily, which initially were not given enough importance, for not having a technological tool that allowed to process it. With Big Data technology, companies can offer better products, develop excellent relationships with their customers, and become more agile and competitive.