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Why Big data is beneficial?

Definition-Big Data is also data but with a huge size. Big Data is a term that is used to describe a collection of data that is huge in size. And yet growing exponentially with time. In short such data is so large and complex. So none of the traditional data management tools are able to store it or process it efficiently. Let me explain with examples.

Examples of Big Data

Social Media:

The statistic shows that 500+terabytes of new data get ingests into the databases of social media site Facebook, every day. This data is mainly generated in terms of photo and video uploads, message exchanges as well as putting comments etc.

Facebook_ Big data

Moreover, A single Jet engine can generate 10+terabytes of data. In just 30 minutes of flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.

Big data example

Types of Big Data

Big Data finds in three forms:

  1. Structured
  2. Unstructured
  3. Semi-structured

Structured

Any data that can be store, access and process in the form of fix format is term as a ‘structured’ data. As time passes, talent in computer science achieve greater success in developing techniques. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent.

Here, An ‘Employee’ table in a database is an example of Structured Data

structure big data

Unstructured

Any data with unknown form or the structure classifies as unstructured data. In addition to the size being huge, un-structured data poses multiple challenges. These challenges in terms of its processing for deriving value out of it. An example of unstructured data is a heterogeneous data source. It containing a combination of simple text files, images, videos etc. Now day organizations have wealth of data available with them. But unfortunately, they don’t know how to derive value out of it. Since this data is in its raw form or unstructured format.

For Example: The output return by ‘Google Search’

Unstructured big data

Semi_structured

Semi-structured data can contain both the forms of data. We can see semi-structured data as a structured in form. But it actually not define with e.g. a table definition in relational DBMS. Example of semi-structured data is a data representation in an XML file.

Examples Of Semi-structured Data

Personal data stored in an XML file-

<rec><name>John</name><sex>Male</sex><age>35</age></rec>
<rec><name>Alia</name><sex>Female</sex><age>41</age></rec>
<rec><name>Sam</name><sex>Male</sex><age>29</age></rec>
<rec><name>Roy</name><sex>Male</sex><age>26</age></rec>
<rec><name>Elif</name><sex>Female</sex><age>35</age></rec>

Benefits of Big Data

Ability to process Big Data brings in multiple benefits, such as-

  • Businesses can utilize outside intelligence while taking decisions

Access to social data from search engines and sites. Such as facebook and twitter. These are enabling organizations to fine tune their business strategies.

  • Improved customer service

Additionally, Traditional customer feedback systems are getting replace by new systems design with Big Data technologies. So, In these new systems, Big Data and natural language processing technologies are use to read and evaluate consumer responses.

  • Early identification of risk to the product/services, if any
  • Better operational efficiency

Big Data technologies are use for creating a

  • staging area for new data before identifying what data to be moved to the data warehouse.
  • In addition, such integration of Big Data technologies and data warehouse helps an organization to offload infrequently accessed data.
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