What is Big Data : Source of Big Data , Pros and Cons.

What is Big Data?

Big data is data that is very large in size. Normally, When the data is in ZETTABYTE or in TERABYTE that data is called Big Data. And Big Data is a combination of  Structured Data, Unstructured Data, and Semistructured Data.

Sources of Big Data

Big Data comes from various platforms like Social Media, Big Malls, etc. But the Bulk Big Data is generated from three sources: Social Data, Machine Data, and Transactional Data.

Social Data – Social Data is data that is generated from social sites publicly for Example Instagram posts, Facebook, etc this kind of data is social data.

Machine Data – Machine data is data that is generated by the machine automatically, for example, we do some activities on our phone like searching for shoes, etc then the machine is collected our data and shares it with the organization that kind of data is machine data.

Transactional Data – Transactional data is data that is captured from the transactions it records the time of the transaction, Place of the transaction, Price of the transaction, Payment Method of Transaction, etc.

Use of Big Data 

The use of Big Data is finding important insights or useful insights from the data by using the latest and advanced tools like Apache Hadoop, Tableau, Spark, etc. With these tools, we get important or useful insights from the Data. And that insight is used by the Organisations for showing relevant advertisements to the relevant users and in this way the organization is using Big Data and making the Organization more profitable. Improving decisions taking of the Organization

Advantages of Big Data 

  • Big Data analysis – we can easily understand and target users according to their interests so relevant customers see relevant ads. 
  • Big Data is also improving the healthcare system through the availability of records.
  • Big Data is also improving an organization’s business strategy by the help of customer data organizations can improve their business strategy.
  • Big Data helps in controlling online reputation means you can run a campaign in which people say about your company that data you can use to make your company’s reputation good.


Disadvantages of Big Data 

  • Storing Big Data can cost lots of money.
  • Big Data is Complex, Unstructured.
  • In Big Data lots of data is waste that is not useful for organizations.
  • Hard to get important insight from Big Data.
  • Big Data analysis also violates principles of privacy.
  • Getting important insights from Big Data is time-consuming.

History of Big Data 

The Big Data term has been used since the 1990s and the credit goes to John R. Mashey for making the term popular. Data is not a term that people start using in the 20s people is using data from a very early phase to take a good decision for their business to grow but now the data is generated in very huge amount so that’s why we called a big data and that data is very huge in size even with the latest and advance technologies it’s hard to handle that data. In 2013 the total amount of data generated is 4.4 zettabytes approx and in 2020 the data generated in the world is 44 zettabytes approx so we see that our data generated globally is increasing rapidly. In 2005 Hadoop was introduced for handling big data then we start using the term Big Data a lot by this tool Big Data becomes easy to manage and getting insight is easy so then this term has become popular this is the history of Big Data.

Why Big Data is Needed 

Big Data is used to know the Customer’s interests, Customer choices what customer is think to buy what customer searches on his phone all the things we know by this help of Big Data analytics by the help of analytics tools we get useful insight and that insight company is used for improving their operations, provide better customer service, create personalized marketing campaigns, and all the things companies do to increase their profits and revenue so basically in this way we use Big data to make organizations more profitable. This is the primary use of Big Data.