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What is BIG DATA? Introduction, Types, Characteristics, Example
- Details
Before we go to introduction to Big Data, you first need to know
What is Data?
The quantities, characters, or symbols on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media.
Now, let's learn Big Data introduction
What is Big Data?
Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity that none of traditional data management tools can store it or process it efficiently. Big data is also a data but with huge size.
In this tutorial, you will learn,
- What is Data?
- What is Big Data?
- Examples Of Big Data
- Types Of Big Data
- Characteristics Of Big Data
- Advantages Of Big Data Processing
Examples Of Big Data
Following are some of the Big Data examples-
The New York Stock Exchange generates about one terabyte of new trade data per day.
Social Media
The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day. This data is mainly generated in terms of photo and video uploads, message exchanges, putting comments etc.
A single Jet engine can generate 10+terabytes of data in 30 minutes of flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.
Types Of Big Data
Following are the types of Big Data:
- Structured
- Unstructured
- Semi-structured
Structured
Any data that can be stored, accessed and processed in the form of fixed format is termed as a 'structured' data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent, typical sizes are being in the rage of multiple zettabytes.
Do you know? 1021 bytes equal to 1 zettabyte or one billion terabytes forms a zettabyte.
Looking at these figures one can easily understand why the name Big Data is given and imagine the challenges involved in its storage and processing.
Do you know? Data stored in a relational database management system is one example of a 'structured' data.
Examples Of Structured Data
An 'Employee' table in a database is an example of Structured Data
| Employee_ID | Employee_Name | Gender | Department | Salary_In_lacs |
|---|---|---|---|---|
| 2365 | Rajesh Kulkarni | Male | Finance | 650000 |
| 3398 | Pratibha Joshi | Female | Admin | 650000 |
| 7465 | Shushil Roy | Male | Admin | 500000 |
| 7500 | Shubhojit Das | Male | Finance | 500000 |
| 7699 | Priya Sane | Female | Finance | 550000 |
Unstructured
Any data with unknown form or the structure is classified as unstructured data. In addition to the size being huge, un-structured data poses multiple challenges in terms of its processing for deriving value out of it. A typical example of unstructured data is a heterogeneous data source 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.
Examples Of Un-structured Data
The output returned by 'Google Search'
Data Growth over the years
Benefits of Big Data Processing
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 like facebook, twitter are enabling organizations to fine tune their business strategies.
- Improved customer service
Traditional customer feedback systems are getting replaced by new systems designed with Big Data technologies. In these new systems, Big Data and natural language processing technologies are being used to read and evaluate consumer responses.
- Early identification of risk to the product/services, if any
- Better operational efficiency
Big Data technologies can be used for creating a staging area or landing zone for new data before identifying what data should 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.
Summary
- Big Data definition : Big Data is defined as data that is huge in size. Bigdata is a term used to describe a collection of data that is huge in size and yet growing exponentially with time.
- Big Data analytics examples includes stock exchanges, social media sites, jet engines, etc.
- Big Data could be 1) Structured, 2) Unstructured, 3) Semi-structured
- Volume, Variety, Velocity, and Variability are few Big Data characteristics
- Improved customer service, better operational efficiency, Better Decision Making are few advantages of Bigdata
