Important for Master of Library and Information Science

1. PRESENTED BY : RAVI P SHARMA
MLIS, DLIS BANARAS HINDU UNIVERSITY
PRESENTED TO : SRIRAM PANDEY SIR
DLIS BANARAS HINDU UNIVERSITY

2. CONTENT
1. DEFINITION
2. EVOLUTION OF BIG DATA
3. BIG DATA: LIBRARIAN SHIP
4. TYPES OF BIG DATA
5. CHARECTERSTICS OF BIG DATA
6. APPLICATION OF BIG DATA
7. REFERENCE

3. What is BIG data ?
❖ Big data is a combination of structured, semi-structured and
unstructured data collected by organizations that has the potential to be
mined for information and used in machine learning projects, predictive
modeling and other advanced analytics applications.
❖ According to Gartner, the definition of Big Data :
“Big data is high-volume, velocity, and variety information assets that
demand cost-effective, innovative forms of information processing for
enhanced insight and decision making.”
Big data

4. According to a study by Boyd & Crawford:-
It rests on the interplay of:
❖ Technology: maximizing computation power and algorithmic accuracy
to gather, analyze, link and compare large data sets.
❖ Analysis: drawing on large data sets to identify patterns in order to
make economic, social, technical, and legal claims.
❖Mythology: the widespread belief that large data sets offer a higher
form of intelligence and knowledge that can generate insights that were
previously impossible with the aura of truth, objectivity, and accuracy.
CONTD...

5. ❖ Very first time the word BIG DATA usedby the scientist of NASA in 1970s decade in
USA.
❖ In modern Era in 2001 Doug Laney, who is an analyst with the Meta Group,
publishes a research note titled “3D Data Management: Controlling Data Volume,
Velocity and Variety.
❖ In 2005 Gartner popularised 3Vs as included three other V’s to different
descriptions of Big Data including Veracity, Value and Variability.
❖ In the same year the Practical big data comes as developers like You tube and
Facebook . They generated large amount of Big data day to day in operations.
❖ Now The 3Vs dimensions has expended including Validity, Venue, Vocabulary and
Vagueness.
❖ In 2010 The Cloud is estimated to contribute more than 1 Exabyte of Data.
Evolution of big data

6. There are two ways of defining big data in librarian-ship:
1.DATA ORIENTED: For Data-orienteddefinitions,Big data
is considereddata or informationwith certain features (e.g. large
volume,increasing rapidly).
2.ABILITY ORIENTED: For Ability-orienteddefinitions,Big
data is definedas the technology to handle the data.
BIG DATA IN LIBRARIAN SHIP

7. BIG DATA IN LIBRARIAN SHIP
There are two ways of defining big data in librarian-ship:
1. DATA ORIENTED: For Data-oriented definitions, Big data
is considered data or information with certain features (e.g. large
volume, increasing rapidly).
2. ABILITY ORIENTED: For Ability-oriented definitions, Big
data is defined as the technology to handle the data.

8. CONTD...
❑Big data is reshaping the patterns libraries have and use for carrying out their duties.
❑The current model for libraries is transforming into Library 4.0, an intelligent library which
can analyze information and present findings to the users.
❑It is implied that digitalization contributes to the advent of big data in libraries because
libraries need to manage big datasets during digitalization.
❑It can be concluded that big data is considered data to be processed with developed
technologies in librarianship.
❑It is implied that digitalization contributes to the advent of big data in libraries because
libraries need to manage big datasets during digitalization.

9. INFLUENCE OF BIG DATA IN LIBRARIAN SHIP
❑ There is a major connection between library data and web big data.
❑Regular increasing amount of library collection data can be considered Big data.
❑Libraries not only need to make data accessible but also the reusability of data for
establishing links between library data and other data sets.
❑ Libraries are entering the era of big data. There are four main reasons for such data richness:
1. Easier access to the internet owing to its world wide availability.
2. The affordability and applicability of digital devices.
3. The increasing amount of digital resource types.
4. The most spread of data utilization.

10. TYPES OF BIG DATA
STRUCTURED
UNSTRUCTURED
SEMI-STRUCTURED

11. TYPES OF BIG DATA
❖ STRUCTURED
❖ UN-STRUCTRED
❖ SEMI- STRUCTURED

12. STRUCTURED DATA: Structured is one of the types of data by which we can
be processed, stored and retrieved the data in fix format.
Example: Students details in the database, Relational data in excel sheet etc.
UNSTRUCTURED DATA: Unstructureddata refers to the data lacks any
specific form or structure what so over. This makes it very difficult and time
consuming to process and analyze unstructureddata.
Example: Email, PDF, Media logs etc.
SEMI-STRUCTURED DATA: Semi-structureddata pertains to the data
containing both the formats: structured and unstructureddata. We can see it as
a structured in form but it is actually not defined.
Example: Personal data stored in XML file, HTML etc.

13. charecterstics of big data
Each one having their own responsibilityand playing differentrole as shown following:

14. Example: E- commarce company Amazon handles in 15 Million customerclick
stream user data per day to recommendproducts.
Extremely large file volume of data is a major characteristic of a big data.
▪ Volume of the Big Data refers the amount of data
generated that must be understood to make data based
decisions.
▪ A text file is a few Kilobytes, a sound file is a few
Megabytes while a full length movies is few Gigabytes.
▪ The size of Big Data is usually larger than Terabytes and
Petabytes.
1. VOLUME:

15. GROWTH OF BIG DATA VOLUME

16. 2. VELOCITY:
▪ Velocity of Big Data measured how fast(speed) data is
produced or generated.
▪ Velocity deals with the pace at which data flows in from
sources like business processes, machines, networks and
human interaction with things like social media sites, mobile
devices, etc.
▪ The flow of data is massive and continuous.
Example: 72 hours of video are uploaded to YouTube every minute. This is the
velocity extremely high velocity of data is another major characteristic of big data.

17. EXAMPLES OF BIG DATA VELOCITY

18. 3. VARIETY:
▪ Variety refers the type and nature of the data.
▪ It can be structured, unstructured, and semistructured data that is
gathered from multiple sources.
▪ While in the past, data could only be collected from spreadsheets and
databases, today data comes in an array of forms such as emails, PDFs,
photos, videos, audios, SM posts, and so much more.
Example: High variety of data sets would be the CCTV audio and video files that are
generated at various locations in a city.

19. GROWTH OF BIG DATA VARIETY

20. 4. VERACITY:
▪ Veracity of Big Data refers the quality of the data that is being
analyzed.
▪ Veracity of Big Data also refers to the biases and abnormality in
data.
5. VALUE:
▪ Value of Big Data refers to the usefullness of the gathered data.
▪ It refers to the worth of the extracted data. Large amounts of
data are useless unless we use it correctly.

21. APPLICATION OF BIG DATA
In today’s world, there are a lot of big data. Big companies utilize those
data for their business growth.

22. ▪ E- COMMERCE SECTOR: Amazon, Walmart, Big Bazar etc.
▪ TELECOM SECTOR: Reliance JIO, Airtel, VI etc.
▪ MEDIA AND ENTERTAINMENT SECTOR: Netflix, Amazon Prime,
MX Player etc.
▪ EDUCATION SECTOR: Byju’s, You Tube, Doubtnut etc.
▪ HEALTH SECTOR: MRI, CT SCAN, OTHER REPORTS
▪ IT SECTOR: ARTIFICIALINTELLIGENCE

23. REFERENCE
▪ JOURNAL OF LIBRARY AND INFORMATION SCIENCE
▪ ARTICLES RELATED ON BIG DATAS
▪ WIKIPEDIA
▪ GOOGLE SEARCHES
▪ YOU TUBE

24. THANK
YOU...💐💐
THANKS!!