Skip to main content

What is Big Data ?

What is Big Data ?
It is now time to answer an important question – What is Big Data?

Big data, as defined by Wikipedia, is this:
“Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage,transfer, visualization, querying and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set.”
In simple terms, Big Data is data that has the 3 characteristics that we mentioned in the last section –
• It is big – typically in terabytes or even petabytes
• It is varied – it could be a traditional database, it could be video data, log data, text data or even voice data
• It keeps increasing as new data keeps flowing in
This kind of data is becoming common place in many fields including Science, public administration and business.
The ability to harness such data for better decision making is therefore in great demand in today’s world.

Where is Big Data Used ?
Big Data is most prevalent in consumer-centric industries that typically generate large volumes of data. Examples of
such industries are –
• Consumer products such as Proctor & Gamble
• Credit card and Insurance such as Capital One and Progressive Insurance
• E-commerce companies such as Amazon, Netflix and Flipkart
• Travel and leisure such as United Airlines and Caesars Casino
• Public utilities such as electricity companies
Big Data is also becoming increasingly important in industries such as –
• Telecom
• Media and Entertainment
• Education
• And healthcare
Within each of these industries, Big Data can be applied to various functions such as –
• Marketing – for example social media analysis to understand customer pulse
• Supply chain – for example better inventory management through GPS data analysis
• Finance – for example for fraud control
• Manufacturing – for example, to link manufacturing operations with the supply chain for better optimization
In this section, you have seen industries and functions where Big Data is making a significant impact.
Now let us get an overview of some of the technologies that are driving the Big Data revolution.

Comments

Popular posts from this blog

Basics Of Hadoop Ecosystem - 2

Basics of Hadoop Ecosystem – 2 Apache Ambari is a web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters. It has a very simple yet highly interactive UI to install various tools and perform various management, configuration and monitoring tasks.  Introduction: In part 2 of the blog series I will cover the other core components of a Hadoop Framework including querying part, external integration, data exchange, co-ordination and managing as well as monitoring of Hadoop Clusters. Please refer to Basic’s of Hadoop Ecosystem  Part 1 ... QUERYING: Pig seems quite useful however; I am more of an SQL person. For those of us who still like SQL, we have SQL for Hadoop. HIVE Hive is a distributed data warehouse built on atop of HDFS to manage and organize large amounts of data. It provides a query based on SQL semantics  (HiveQL)  which is translated by the runtime engine to Map Reduce jobs for querying the data. Sche...

Data Engineering - Tools & Intro

Data Engineering - Tools & Intro So I just realized that I am here after a month or so. I was busy at work and traveling. I am starting a kind of new series, I say it Data Engineering Series in which I will be discussing different tools. Of course, I am not able to discuss the entire concept of Data Engineering neither I know it as I will be learning myself. What is Data Engineering? Data Engineering is all about developing, maintaining systems that are responsible for transferring data in large volumes and make it available for analysts and data scientists to use it for analyzing and data modeling. Data engineering is a superset of Data Science or the subset, not clear to me but the collaboration of data engineers and scientists fruits useful data-driven solutions. Data Engineering tools It consists of several tools. Some are dealing with data storage while others with analysis and ETL. Ofcourse, Apache Kafka is one of them. The others tools that I might be covering are Apache...

Differences Between Hibernate and Spring Data JPA?

Differences Between Hibernate and Spring Data JPA? In this quick article, I would like to describe what is the difference between  Hibernate ORM framework  and  Spring Data JPA . Let's first know the definition of  JPA ,  Hibernate , and  Spring Data JPA , so this will make it easy to discuss the difference between Hibernate and Spring Data JPA. What Is Java Persistence API? The Java Persistence API provides a specification for persisting, reading, and managing data from your Java object to relational tables in the database. Read more about JPA at  JPA Tutorial - Java Persistence API  (you will learn everything about JPA here). What Is Hibernate Framework? Hibernate is an object-relational mapping solution for Java environments. Object-relational mapping or ORM is the programming technique to map application domain model objects to the relational database tables. Hibernate is a Java-based ORM tool that provides a framework for ma...