Big Data, Data Visualization, Machine Learning & Artificial Intelligence have been explained with history, definitions, categories and applications.

2. WHAT IS BIG DATA ?
• Large volume of data-
• Inundates a business on a day-to-day basis

3. HISTORY OF BIG DATA
• The concept - Early 2000s
• Doug Laney (Industry Analyst) articulated the now-mainstream definition of big
data as the three V’s:
 Volume: : Organizations collect data from a variety of sources, including business transactions, smart
(IoT) devices, industrial equipment, videos, social media and more
 Velocity: : With the growth in the Internet of Things, data streams in to businesses at an unprecedented
speed and must be handled in a timely manner
 Variety: Data comes in all types of formats-from structured, numeric data in traditional databases to
unstructured text documents, emails, videos, audios, stock ticker data and financial transactions.

4. TYPES
• Structured Data: Any data that can be stored, accessed and processed in the form
of fixed format is termed as a ‘structured’ data.
• Un-Structured Data: Any data with unknown form or the structure is classified
as unstructured data.
• Semi-Structured Data: Related to the data containing both the formats referenced
over, that is, unstructured and structured data.

6.  Graphical representation of information and data.
 By using visual elements like charts, graphs, and maps,
data visualization tools
 Essential to analyze massive amounts of information and
make data-driven decisions.

7. Applications
 Understanding and increases effectiveness
 Human mind learns fast from visuals than that from text and tables
 Fast and effective
 Healthcare Industries
 Military
 Finance Industries

9. Machine learning (ML)
 study of computer algorithms that can improve automatically through
experience and by the use of data
 Machine learning algorithms build a model based on sample data,
known as training data
 Machine learning algorithms are used in a wide variety of
applications, such as in medicine, email filtering, speech recognition,
and computer vision

10. Categories
 Supervised learning (SL) is the machine learning task of learning a
function that maps an input to an output based on example input-
output pairs
 Unsupervised learning, also known as unsupervised machine
learning, uses machine learning algorithms to analyze and cluster
unlabeled datasets
 Semi-supervised learning offers a happy medium between supervised
and unsupervised learning. During training, it uses a smaller labeled
data set to guide classification and feature extraction from a larger,
unlabeled data set

11. Working
 A Decision Process
 An Error Function
 An Model Optimization Process
 Speech recognition
 Customer service
 Computer vision
 Recommendation engines
 Automated stock trading
Applications

13. Definitions
 John McCaty- Dartmouth Conference (1956)
“AI is science and engineering of making intelligent machines”
“AI is a technique of getting machines to work and behave like humans.”

28. BIBLIOGRAPHY (Big Data)
 https://thumbs.dreamstime.com/b/big-data-analytics-bi-business-intelligence-concept-chart-graph-icons-virtual-screen-big-
data-analytics-bi-business-126811848.jpg
 https://teklink.com/wp-content/uploads/2021/02/Data-Science-and-Advanced-Analytics.jpg
 https://wallpapercave.com/wp/wp3188042.jpg
 https://www.mobivity.com/hubfs/Imported_Blog_Media/01-25-Hero.jpg

29. BIBLIOGRAPHY (Data Visualization)
• https://www.educba.com/benefits-of-data-visualization/
• https://www.google.com/url?sa=i&url=https%3A%2F%2Fvenngage.com%2
Fblog%2Fdata-visualization%2F&psig=AOvVaw3yn-
f_OPl8qoIs3k07Vg3y&ust=1630389210404000&source=images&cd=vfe&ve
d=0CAsQjRxqFwoTCJidtqSH2PICFQAAAAAdAAAAABAP
• https://www.google.com/search?q=apllicatin+of+data+visualiation+in+real
+life&rlz=1C1ZKTG_enIN926IN926&sxsrf=AOaemvJLHyEUZd9KI80jpTQSf-
VBl74zKQ%3A1630303139609&ei=o3MsYZjWJLuV4-EP-
KGUyAY&oq=apllicatin+of+data+visualiation+in+real+life&gs_lcp=Cgdnd3M
td2l6EAMyBAgAEA06BwgAEEcQsAM6BwgjELACECc6CAgAEA0QBRAeOgYIA
BAWEB5KBAhBGABQh1VY9Hpg6XxoAnAAeACAAeoCiAHsFZIBBzAuOS40LjG
YAQCgAQHIAQjAAQE&sclient=gws-
wiz&ved=0ahUKEwjYs4y8iNjyAhW7yjgGHfgQBWkQ4dUDCA8&uact=5

30. BIBLIOGRAPHY (Artificial Intelligence)
 https://www.youtube.com/watch?v=oV74Najm6Nc&t=40s
 https://static.wikia.nocookie.net/marvelcinematicuniverse/images/f/f3/Iron_Man_on_the_Couch-
IM3.jpg/revision/latest/scale-to-width-down/1000?cb=20150326160337
 https://cdn.quotesgram.com/img/63/51/1909949645-Iron-Man-Jarvis-Live-Wallpaper-
2.pnghttps://www.ramascreen.com/wp-content/uploads/2016/01/Iron-Man-e1451896699100.jpg
 https://www.sentinelassam.com/wp-content/uploads/2020/03/Artificial-Intelligence.jpg
 https://d1m75rqqgidzqn.cloudfront.net/wp-data/2020/09/09202218/iStock-1207062970.jpg
 https://cssh.northeastern.edu/philosophy/wp-content/uploads/sites/11/2020/05/Ai-startups-tech-Peter-Rejceck-shutterstock-
1290615073-1068x601-1.jpg
 https://cssh.northeastern.edu/ethics/wp-content/uploads/sites/31/2020/07/ai@2x.png
 https://cdn.arstechnica.net/wp-content/uploads/2020/03/old-facebook-design-notifications-640x308.png
 https://hub.packtpub.com/wp-content/uploads/2018/03/iStock-692834394-696x464.jpg
 https://www.logodesignlove.com/images/monograms/tesla-logo-01.jpg
 https://youtu.be/eUd6p2Zf8MA

31. Baljeet Kumar Badal-20MBAOPE17
Akash Shimpi-20MBAOPE001
Shubham Pund-20MBAOPE052
Gourab Talapatra-20MBAHHM010
Om Chaudhary-20MBAHHM18
Kaushal More-20MBAOPE029
Vivek Phalke -20MBAHHM32
Presenters

32. THANK YOU