SlideShare a Scribd company logo
INTRODUCTION TO
DATA SCIENCE
FOR-IAN V. SANDOVAL
Asst. Professor II
Laguna State Polytechnic University
LEARNING OBJECTIVES
• Apprehend the field of Data Science impact and
importance in the society
• Reflect on its applications, importance and advantages
CONTENTS
• Why should study Data Science?
• How Does Data Science Impact Organizations?
• Application and Competitive Advantage of Data
Science in Organization
• Importance of Data Science to Society
• Road to Become a Data Scientist
WHY WE ARE TALKING ABOUT
DATA SCIENCE?
Source: https://bit.ly/31HBHuQ
WHAT IS DATA SCIENCE?
• “Data Science is a new term. But in the same sense as
Columbus was discovered NEW Continent 1000 years
ago.”
- Hector Garcia-Molina
Professor in the Departments
of Computer Science and
Electrical Engineering of
Stanford University
WHAT IS DATA SCIENCE?
• a multi-disciplinary field
that uses scientific
methods, processes,
algorithms and systems to
extract knowledge and
insights from structured
and unstructured data.
Source: https://bit.ly/30dekJB
WHAT IS DATA SCIENCE?
• a "concept to unify statistics, data analysis, machine
learning and their related methods" in order to
"understand and analyze actual phenomena" with data.
• employs techniques and
theories drawn from many
fields within the context of
mathematics, statistics,
computer science, and
information science.
Source: https://bit.ly/2YTRQ3w
WHAT IS DATA SCIENCE?
WHAT IS DATA SCIENCE?
Fourth Paradigm of Science
• Thousand of years
- Empirical
• Few hundred of years
- Theoretical
• Last fifty years
- Computational
- “Query the world”
• Last twenty years
- eScience (Data Science)
- “Download the world”
WHAT IS DATA SCIENCE?
Data Science and others
• Statistics
• Big Data Analytics
• Business Analytics
• Business Intelligence
• Data(base) Management
• Visualization
• Machine Learning
• Data Mining
• Artificial Intelligence
• Predictive Modelling
WHAT IS DATA SCIENCE?
Big Data Science Tasks
• Facebooks
• Amazon
• Google
• Linkedln
• Netflix
• Rozetka
• Microsoft
WHAT IS DATA SCIENCE?
Regular Data Science
• Data Analysis
• Modelling Statistics
• Engineering / Prototyping
WHAT IS DATA SCIENCE?
What do people look for in a data scientist?
WHAT IS DATA SCIENCE?
What do people look for in a data scientist?
WHAT IS DATA SCIENCE?
Data Science Roles
WHAT IS DATA SCIENCE?
Roles Required in Data Science Project
Source: https://bit.ly/2z5sYqf
WHAT IS DATA SCIENCE?
How to become a data scientist?
• Data Scientists need to know how to “CODE”
WHAT IS DATA SCIENCE?
How to become a data scientist?
• Other languages, tools, platforms and visualization
WHAT IS DATA SCIENCE?
Learning Data Science with Python - Libraries
WHAT IS DATA SCIENCE?
Learning Data Science with Python - Libraries
WHAT IS DATA SCIENCE?
Learning Data Science with Python - Tools
WHAT IS DATA SCIENCE?
How to become a data scientist?
• Learn to code
WHAT IS DATA SCIENCE?
Data Scientist need to comfortable with:
WHAT IS DATA SCIENCE?
Data Scientist need to learning machine learning &
software engineering
WHAT IS DATA SCIENCE?
Who are the Data Scientist?
WHAT IS DATA SCIENCE?
Who are the Data Scientist?
WHAT IS DATA SCIENCE?
Who are the Data Scientist?
WHAT IS DATA SCIENCE?
https://bit.ly/2P4eyl0
WHAT IS DATA SCIENCE?
WHAT IS DATA SCIENCE?
APPLICATION OF DATA SCIENCE
APPLICATIONS OF DATA SCIENCE
• Security
APPLICATIONS OF DATA SCIENCE
• Sports
APPLICATIONS OF DATA SCIENCE
• Banking and Finance
APPLICATIONS OF DATA SCIENCE
• Internet Search
APPLICATIONS OF DATA SCIENCE
• Digital Advertisements
APPLICATIONS OF DATA SCIENCE
• Recommender System
APPLICATIONS OF DATA SCIENCE
• Image Processing
APPLICATIONS OF DATA SCIENCE
• Speech Recognition
APPLICATIONS OF DATA SCIENCE
• Gaming
APPLICATIONS OF DATA SCIENCE
• Price Comparison Websites
APPLICATIONS OF DATA SCIENCE
• Airline Routing Planning
APPLICATIONS OF DATA SCIENCE
• Fraud and Risk Detection
APPLICATIONS OF DATA SCIENCE
• Delivery Logistics
APPLICATIONS OF DATA SCIENCE
• Internet of Things (IoT)
APPLICATIONS OF DATA SCIENCE
• Health Care
APPLICATIONS OF DATA SCIENCE
• Augmented Reality
APPLICATIONS OF DATA SCIENCE
• Self-Driving Cars
APPLICATIONS OF DATA SCIENCE
• Robots
IMPACT OF DATA SCIENCE ON SOCIETY
IMPACT OF DATA SCIENCE ON
SOCIETY
• Saving Energy
IMPACT OF DATA SCIENCE ON
SOCIETY
• Data-Driven Hospitals
IMPACT OF DATA SCIENCE ON
SOCIETY
• A Cleaner Environment
IMPACT OF DATA SCIENCE ON
SOCIETY
• Volunteer with a socially-oriented data science
program/organization
IMPACT OF DATA SCIENCE ON
SOCIETY
• Contribute via competitions
IMPACT OF DATA SCIENCE ON
SOCIETY
• Consider solutions to real-world problems that you
encounter
IMPACT OF DATA SCIENCE ON
SOCIETY
• Be thoughtful in professional work
IMPORTANCE OF DATA SCIENCE
IMPORTANCE OF DATA SCIENCE
1. Data science helps brands to understand their
customers in a much enhanced and empowered
manner.
2. It allows brands to communicate their story in such
a engaging and powerful manner.
3. Big Data is a new field that is constantly growing
and evolving.
IMPORTANCE OF DATA SCIENCE
4. Its findings and results can be applied to almost any
sector like travel, healthcare and education among
others.
5. Data science is accessible to almost all sectors.
Road to become a Data Scientist
REFERENCES
• https://slideplayer.com/slide/10398517/
• https://www.slideshare.net/ryanorban/how-to-become-a-data-scientist
• Dhar, V. (2013). "Data science and prediction". Communications of the ACM. 56 (12): 64–73. doi:10.1145/2500499.
• Hayashi, Chikio (1 January 1998). "What is Data Science? Fundamental Concepts and a Heuristic Example". In
Hayashi, Chikio; Yajima, Keiji; Bock, Hans-Hermann; Ohsumi, Noboru; Tanaka, Yutaka; Baba, Yasumasa (eds.).
Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge
Organization. Springer Japan. pp. 40–51. doi:10.1007/978-4-431-65950-1_3. ISBN 9784431702085.
• Davenport, Thomas H.; Patil, DJ (October 2012), Data Scientist: The Sexiest Job of the 21st Century, Harvard
Business Review
• Jeff Leek (12 December 2013). "The key word in "Data Science" is not Data, it is Science". Simply Statistics.
• https://www.analyticsvidhya.com/blog/2015/09/applications-data-science/
• https://www.edureka.co/blog/data-science-applications/
• https://dutchdatascienceweek.nl/2018/04/05/the-impact-of-data-science-on-society/
• https://www.educba.com/data-science-and-its-growing-importance/

More Related Content

What's hot (20)

PDF
Data science presentation
MSDEVMTL
 
PPTX
Data science
SouravSadhukhan6
 
PPTX
Data science applications and usecases
Sreenatha Reddy K R
 
PPTX
Introduction to data science
Sampath Kumar
 
PPTX
Introduction of Data Science
Jason Geng
 
PDF
Introduction to data science
Tharushi Ruwandika
 
PPTX
Introduction to Data Analytics
Dr. C.V. Suresh Babu
 
PPTX
Introduction to data science.pptx
SadhanaParameswaran
 
PDF
Introduction on Data Science
Edureka!
 
PPTX
Data analytics vs. Data analysis
Dr. C.V. Suresh Babu
 
PPTX
1. Data Analytics-introduction
krishna singh
 
PDF
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...
SlideTeam
 
PPT
Data Preprocessing
Object-Frontier Software Pvt. Ltd
 
PPTX
Big Data Analytics
RohithND
 
PDF
Machine Learning Deep Learning AI and Data Science
Venkata Reddy Konasani
 
PPTX
Text MIning
Prakhyath Rai
 
PPTX
Machine Learning Algorithms | Machine Learning Tutorial | Data Science Algori...
Simplilearn
 
PDF
Support Vector Machines ( SVM )
Mohammad Junaid Khan
 
PPTX
History of AI
Megha Sharma
 
Data science presentation
MSDEVMTL
 
Data science
SouravSadhukhan6
 
Data science applications and usecases
Sreenatha Reddy K R
 
Introduction to data science
Sampath Kumar
 
Introduction of Data Science
Jason Geng
 
Introduction to data science
Tharushi Ruwandika
 
Introduction to Data Analytics
Dr. C.V. Suresh Babu
 
Introduction to data science.pptx
SadhanaParameswaran
 
Introduction on Data Science
Edureka!
 
Data analytics vs. Data analysis
Dr. C.V. Suresh Babu
 
1. Data Analytics-introduction
krishna singh
 
Artificial Intelligence Machine Learning Deep Learning Ppt Powerpoint Present...
SlideTeam
 
Big Data Analytics
RohithND
 
Machine Learning Deep Learning AI and Data Science
Venkata Reddy Konasani
 
Text MIning
Prakhyath Rai
 
Machine Learning Algorithms | Machine Learning Tutorial | Data Science Algori...
Simplilearn
 
Support Vector Machines ( SVM )
Mohammad Junaid Khan
 
History of AI
Megha Sharma
 

Similar to Introduction to Data Science (20)

PPTX
03-introductiontodatascience-190819220727.pptx
aashammariaziz
 
PPTX
Data Science.pptx
CarolineRebeccaD
 
PPTX
Digital project planning and pedagogy
librarianrafia
 
PPTX
Data Science and AI in Biomedicine: The World has Changed
Philip Bourne
 
PDF
Current Disruptions in Media: Earthquakes or New Openings? Stanford as Catalyst
Martha Russell
 
PDF
Getting Started in Data Science
Thinkful
 
PDF
Big Data & DS Analytics for PAARL
Philippine Association of Academic/Research Librarians
 
PPTX
Data Science Meets Biomedicine, Does Anything Change
Philip Bourne
 
PPT
data science ppt of emngineering studnets
anughasha
 
PDF
Career in Data Science (July 2017, DTLA)
Thinkful
 
PPTX
Real-time applications of Data Science.pptx
shalini s
 
PPT
Data Science-1 (1).ppt
SanjayAcharaya
 
PPTX
Data_Science_Applications_&_Use_Cases.pptx
wahiba ben abdessalem
 
PPTX
Data_Science_Applications_&_Use_Cases.pptx
ssuser1a4f0f
 
PDF
Getting started in Data Science (April 2017, Los Angeles)
Thinkful
 
PDF
Luciano uvi hackfest.28.10.2020
Joanne Luciano
 
PPTX
Biomedical Data Science: We Are Not Alone
Philip Bourne
 
PDF
The Field Guide to Data Science 2nd Edition Booz Allen Hamilton
samryaiso
 
PDF
AI for Marking Industry application for.pdf
jdcil1975
 
PDF
Data_Science_Applications_&_Use_Cases.pdf
vishal choudhary
 
03-introductiontodatascience-190819220727.pptx
aashammariaziz
 
Data Science.pptx
CarolineRebeccaD
 
Digital project planning and pedagogy
librarianrafia
 
Data Science and AI in Biomedicine: The World has Changed
Philip Bourne
 
Current Disruptions in Media: Earthquakes or New Openings? Stanford as Catalyst
Martha Russell
 
Getting Started in Data Science
Thinkful
 
Data Science Meets Biomedicine, Does Anything Change
Philip Bourne
 
data science ppt of emngineering studnets
anughasha
 
Career in Data Science (July 2017, DTLA)
Thinkful
 
Real-time applications of Data Science.pptx
shalini s
 
Data Science-1 (1).ppt
SanjayAcharaya
 
Data_Science_Applications_&_Use_Cases.pptx
wahiba ben abdessalem
 
Data_Science_Applications_&_Use_Cases.pptx
ssuser1a4f0f
 
Getting started in Data Science (April 2017, Los Angeles)
Thinkful
 
Luciano uvi hackfest.28.10.2020
Joanne Luciano
 
Biomedical Data Science: We Are Not Alone
Philip Bourne
 
The Field Guide to Data Science 2nd Edition Booz Allen Hamilton
samryaiso
 
AI for Marking Industry application for.pdf
jdcil1975
 
Data_Science_Applications_&_Use_Cases.pdf
vishal choudhary
 
Ad

More from Laguna State Polytechnic University (20)

PDF
Number Theory - Lesson 1 - Introduction to Number Theory
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 8 - Predicates and Quantifiers
Laguna State Polytechnic University
 
PDF
Machine Learning Algorithms (Part 1)
Laguna State Polytechnic University
 
PDF
Artificial Intelligence Algorithms
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 7 - Rules of Inference
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 6 - Switching Circuits
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 5 - Logical Equivalence
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 4 - Tautology, Contradiction and Contingency
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 3 - Truth Tables
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 2 - Logical Connectives
Laguna State Polytechnic University
 
PDF
Formal Logic - Lesson 1 - Introduction to Logic
Laguna State Polytechnic University
 
PPTX
Ethical Issues and Relevant Laws on Computing
Laguna State Polytechnic University
 
PPTX
Number Systems Basic Concepts
Laguna State Polytechnic University
 
PDF
Number Systems Basic Concepts
Laguna State Polytechnic University
 
PPTX
Exploring the Difference Between Information Technology and Information System
Laguna State Polytechnic University
 
PPTX
Introduction to Computers
Laguna State Polytechnic University
 
PPTX
Introduction to Computing Logic Formulation
Laguna State Polytechnic University
 
PDF
Oasis of Sparkling and Refreshing Truisms
Laguna State Polytechnic University
 
PDF
My Teacher Got IT v2.0 - Software Installation Track
Laguna State Polytechnic University
 
PPTX
A Case Study on Issues and Violations on Information Technology
Laguna State Polytechnic University
 
Number Theory - Lesson 1 - Introduction to Number Theory
Laguna State Polytechnic University
 
Formal Logic - Lesson 8 - Predicates and Quantifiers
Laguna State Polytechnic University
 
Machine Learning Algorithms (Part 1)
Laguna State Polytechnic University
 
Artificial Intelligence Algorithms
Laguna State Polytechnic University
 
Formal Logic - Lesson 7 - Rules of Inference
Laguna State Polytechnic University
 
Formal Logic - Lesson 6 - Switching Circuits
Laguna State Polytechnic University
 
Formal Logic - Lesson 5 - Logical Equivalence
Laguna State Polytechnic University
 
Formal Logic - Lesson 4 - Tautology, Contradiction and Contingency
Laguna State Polytechnic University
 
Formal Logic - Lesson 3 - Truth Tables
Laguna State Polytechnic University
 
Formal Logic - Lesson 2 - Logical Connectives
Laguna State Polytechnic University
 
Formal Logic - Lesson 1 - Introduction to Logic
Laguna State Polytechnic University
 
Ethical Issues and Relevant Laws on Computing
Laguna State Polytechnic University
 
Number Systems Basic Concepts
Laguna State Polytechnic University
 
Number Systems Basic Concepts
Laguna State Polytechnic University
 
Exploring the Difference Between Information Technology and Information System
Laguna State Polytechnic University
 
Introduction to Computers
Laguna State Polytechnic University
 
Introduction to Computing Logic Formulation
Laguna State Polytechnic University
 
Oasis of Sparkling and Refreshing Truisms
Laguna State Polytechnic University
 
My Teacher Got IT v2.0 - Software Installation Track
Laguna State Polytechnic University
 
A Case Study on Issues and Violations on Information Technology
Laguna State Polytechnic University
 
Ad

Recently uploaded (20)

PDF
SSHS-2025-PKLP_Quarter-1-Dr.-Kerby-Alvarez.pdf
AishahSangcopan1
 
PPTX
SPINA BIFIDA: NURSING MANAGEMENT .pptx
PRADEEP ABOTHU
 
PDF
Reconstruct, Restore, Reimagine: New Perspectives on Stoke Newington’s Histor...
History of Stoke Newington
 
PPTX
ASRB NET 2023 PREVIOUS YEAR QUESTION PAPER GENETICS AND PLANT BREEDING BY SAT...
Krashi Coaching
 
PDF
The dynastic history of the Chahmana.pdf
PrachiSontakke5
 
PDF
LAW OF CONTRACT ( 5 YEAR LLB & UNITARY LLB)- MODULE-3 - LEARN THROUGH PICTURE
APARNA T SHAIL KUMAR
 
PDF
Biological Bilingual Glossary Hindi and English Medium
World of Wisdom
 
PPSX
HEALTH ASSESSMENT (Community Health Nursing) - GNM 1st Year
Priyanshu Anand
 
PDF
People & Earth's Ecosystem -Lesson 2: People & Population
marvinnbustamante1
 
PDF
Isharyanti-2025-Cross Language Communication in Indonesian Language
Neny Isharyanti
 
PPTX
2025 Winter SWAYAM NPTEL & A Student.pptx
Utsav Yagnik
 
PPTX
HYDROCEPHALUS: NURSING MANAGEMENT .pptx
PRADEEP ABOTHU
 
PPTX
Universal immunization Programme (UIP).pptx
Vishal Chanalia
 
PPTX
grade 5 lesson matatag ENGLISH 5_Q1_PPT_WEEK4.pptx
SireQuinn
 
PPT
Talk on Critical Theory, Part One, Philosophy of Social Sciences
Soraj Hongladarom
 
PPTX
Cultivation practice of Litchi in Nepal.pptx
UmeshTimilsina1
 
PDF
CEREBRAL PALSY: NURSING MANAGEMENT .pdf
PRADEEP ABOTHU
 
PDF
Dimensions of Societal Planning in Commonism
StefanMz
 
PDF
The-Ever-Evolving-World-of-Science (1).pdf/7TH CLASS CURIOSITY /1ST CHAPTER/B...
Sandeep Swamy
 
PDF
ARAL-Orientation_Morning-Session_Day-11.pdf
JoelVilloso1
 
SSHS-2025-PKLP_Quarter-1-Dr.-Kerby-Alvarez.pdf
AishahSangcopan1
 
SPINA BIFIDA: NURSING MANAGEMENT .pptx
PRADEEP ABOTHU
 
Reconstruct, Restore, Reimagine: New Perspectives on Stoke Newington’s Histor...
History of Stoke Newington
 
ASRB NET 2023 PREVIOUS YEAR QUESTION PAPER GENETICS AND PLANT BREEDING BY SAT...
Krashi Coaching
 
The dynastic history of the Chahmana.pdf
PrachiSontakke5
 
LAW OF CONTRACT ( 5 YEAR LLB & UNITARY LLB)- MODULE-3 - LEARN THROUGH PICTURE
APARNA T SHAIL KUMAR
 
Biological Bilingual Glossary Hindi and English Medium
World of Wisdom
 
HEALTH ASSESSMENT (Community Health Nursing) - GNM 1st Year
Priyanshu Anand
 
People & Earth's Ecosystem -Lesson 2: People & Population
marvinnbustamante1
 
Isharyanti-2025-Cross Language Communication in Indonesian Language
Neny Isharyanti
 
2025 Winter SWAYAM NPTEL & A Student.pptx
Utsav Yagnik
 
HYDROCEPHALUS: NURSING MANAGEMENT .pptx
PRADEEP ABOTHU
 
Universal immunization Programme (UIP).pptx
Vishal Chanalia
 
grade 5 lesson matatag ENGLISH 5_Q1_PPT_WEEK4.pptx
SireQuinn
 
Talk on Critical Theory, Part One, Philosophy of Social Sciences
Soraj Hongladarom
 
Cultivation practice of Litchi in Nepal.pptx
UmeshTimilsina1
 
CEREBRAL PALSY: NURSING MANAGEMENT .pdf
PRADEEP ABOTHU
 
Dimensions of Societal Planning in Commonism
StefanMz
 
The-Ever-Evolving-World-of-Science (1).pdf/7TH CLASS CURIOSITY /1ST CHAPTER/B...
Sandeep Swamy
 
ARAL-Orientation_Morning-Session_Day-11.pdf
JoelVilloso1
 

Introduction to Data Science

  • 1. INTRODUCTION TO DATA SCIENCE FOR-IAN V. SANDOVAL Asst. Professor II Laguna State Polytechnic University
  • 2. LEARNING OBJECTIVES • Apprehend the field of Data Science impact and importance in the society • Reflect on its applications, importance and advantages
  • 3. CONTENTS • Why should study Data Science? • How Does Data Science Impact Organizations? • Application and Competitive Advantage of Data Science in Organization • Importance of Data Science to Society • Road to Become a Data Scientist
  • 4. WHY WE ARE TALKING ABOUT DATA SCIENCE? Source: https://bit.ly/31HBHuQ
  • 5. WHAT IS DATA SCIENCE? • “Data Science is a new term. But in the same sense as Columbus was discovered NEW Continent 1000 years ago.” - Hector Garcia-Molina Professor in the Departments of Computer Science and Electrical Engineering of Stanford University
  • 6. WHAT IS DATA SCIENCE? • a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Source: https://bit.ly/30dekJB
  • 7. WHAT IS DATA SCIENCE? • a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. • employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science. Source: https://bit.ly/2YTRQ3w
  • 8. WHAT IS DATA SCIENCE?
  • 9. WHAT IS DATA SCIENCE? Fourth Paradigm of Science • Thousand of years - Empirical • Few hundred of years - Theoretical • Last fifty years - Computational - “Query the world” • Last twenty years - eScience (Data Science) - “Download the world”
  • 10. WHAT IS DATA SCIENCE? Data Science and others • Statistics • Big Data Analytics • Business Analytics • Business Intelligence • Data(base) Management • Visualization • Machine Learning • Data Mining • Artificial Intelligence • Predictive Modelling
  • 11. WHAT IS DATA SCIENCE? Big Data Science Tasks • Facebooks • Amazon • Google • Linkedln • Netflix • Rozetka • Microsoft
  • 12. WHAT IS DATA SCIENCE? Regular Data Science • Data Analysis • Modelling Statistics • Engineering / Prototyping
  • 13. WHAT IS DATA SCIENCE? What do people look for in a data scientist?
  • 14. WHAT IS DATA SCIENCE? What do people look for in a data scientist?
  • 15. WHAT IS DATA SCIENCE? Data Science Roles
  • 16. WHAT IS DATA SCIENCE? Roles Required in Data Science Project Source: https://bit.ly/2z5sYqf
  • 17. WHAT IS DATA SCIENCE? How to become a data scientist? • Data Scientists need to know how to “CODE”
  • 18. WHAT IS DATA SCIENCE? How to become a data scientist? • Other languages, tools, platforms and visualization
  • 19. WHAT IS DATA SCIENCE? Learning Data Science with Python - Libraries
  • 20. WHAT IS DATA SCIENCE? Learning Data Science with Python - Libraries
  • 21. WHAT IS DATA SCIENCE? Learning Data Science with Python - Tools
  • 22. WHAT IS DATA SCIENCE? How to become a data scientist? • Learn to code
  • 23. WHAT IS DATA SCIENCE? Data Scientist need to comfortable with:
  • 24. WHAT IS DATA SCIENCE? Data Scientist need to learning machine learning & software engineering
  • 25. WHAT IS DATA SCIENCE? Who are the Data Scientist?
  • 26. WHAT IS DATA SCIENCE? Who are the Data Scientist?
  • 27. WHAT IS DATA SCIENCE? Who are the Data Scientist?
  • 28. WHAT IS DATA SCIENCE? https://bit.ly/2P4eyl0
  • 29. WHAT IS DATA SCIENCE?
  • 30. WHAT IS DATA SCIENCE?
  • 32. APPLICATIONS OF DATA SCIENCE • Security
  • 33. APPLICATIONS OF DATA SCIENCE • Sports
  • 34. APPLICATIONS OF DATA SCIENCE • Banking and Finance
  • 35. APPLICATIONS OF DATA SCIENCE • Internet Search
  • 36. APPLICATIONS OF DATA SCIENCE • Digital Advertisements
  • 37. APPLICATIONS OF DATA SCIENCE • Recommender System
  • 38. APPLICATIONS OF DATA SCIENCE • Image Processing
  • 39. APPLICATIONS OF DATA SCIENCE • Speech Recognition
  • 40. APPLICATIONS OF DATA SCIENCE • Gaming
  • 41. APPLICATIONS OF DATA SCIENCE • Price Comparison Websites
  • 42. APPLICATIONS OF DATA SCIENCE • Airline Routing Planning
  • 43. APPLICATIONS OF DATA SCIENCE • Fraud and Risk Detection
  • 44. APPLICATIONS OF DATA SCIENCE • Delivery Logistics
  • 45. APPLICATIONS OF DATA SCIENCE • Internet of Things (IoT)
  • 46. APPLICATIONS OF DATA SCIENCE • Health Care
  • 47. APPLICATIONS OF DATA SCIENCE • Augmented Reality
  • 48. APPLICATIONS OF DATA SCIENCE • Self-Driving Cars
  • 49. APPLICATIONS OF DATA SCIENCE • Robots
  • 50. IMPACT OF DATA SCIENCE ON SOCIETY
  • 51. IMPACT OF DATA SCIENCE ON SOCIETY • Saving Energy
  • 52. IMPACT OF DATA SCIENCE ON SOCIETY • Data-Driven Hospitals
  • 53. IMPACT OF DATA SCIENCE ON SOCIETY • A Cleaner Environment
  • 54. IMPACT OF DATA SCIENCE ON SOCIETY • Volunteer with a socially-oriented data science program/organization
  • 55. IMPACT OF DATA SCIENCE ON SOCIETY • Contribute via competitions
  • 56. IMPACT OF DATA SCIENCE ON SOCIETY • Consider solutions to real-world problems that you encounter
  • 57. IMPACT OF DATA SCIENCE ON SOCIETY • Be thoughtful in professional work
  • 59. IMPORTANCE OF DATA SCIENCE 1. Data science helps brands to understand their customers in a much enhanced and empowered manner. 2. It allows brands to communicate their story in such a engaging and powerful manner. 3. Big Data is a new field that is constantly growing and evolving.
  • 60. IMPORTANCE OF DATA SCIENCE 4. Its findings and results can be applied to almost any sector like travel, healthcare and education among others. 5. Data science is accessible to almost all sectors.
  • 61. Road to become a Data Scientist
  • 62. REFERENCES • https://slideplayer.com/slide/10398517/ • https://www.slideshare.net/ryanorban/how-to-become-a-data-scientist • Dhar, V. (2013). "Data science and prediction". Communications of the ACM. 56 (12): 64–73. doi:10.1145/2500499. • Hayashi, Chikio (1 January 1998). "What is Data Science? Fundamental Concepts and a Heuristic Example". In Hayashi, Chikio; Yajima, Keiji; Bock, Hans-Hermann; Ohsumi, Noboru; Tanaka, Yutaka; Baba, Yasumasa (eds.). Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer Japan. pp. 40–51. doi:10.1007/978-4-431-65950-1_3. ISBN 9784431702085. • Davenport, Thomas H.; Patil, DJ (October 2012), Data Scientist: The Sexiest Job of the 21st Century, Harvard Business Review • Jeff Leek (12 December 2013). "The key word in "Data Science" is not Data, it is Science". Simply Statistics. • https://www.analyticsvidhya.com/blog/2015/09/applications-data-science/ • https://www.edureka.co/blog/data-science-applications/ • https://dutchdatascienceweek.nl/2018/04/05/the-impact-of-data-science-on-society/ • https://www.educba.com/data-science-and-its-growing-importance/

Editor's Notes

  • #10: Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.
  • #13: Data Analysis What percentage of users back to our site? Which products usually bought together? Modelling Statistics How many cars are going to sell next year? Which city is better for opening new office? Engineering / Prototyping Product to use a prediction model Visualization of Analytics
  • #29: In 2012, when Harvard Business Review called it "The Sexiest Job of the 21st Century", the term "data science" became a buzzword.
  • #30: In 2012, when Harvard Business Review called it "The Sexiest Job of the 21st Century", the term "data science" became a buzzword.
  • #31: In 2012, when Harvard Business Review called it "The Sexiest Job of the 21st Century", the term "data science" became a buzzword.
  • #36: Search Engines - Google, Yahoo, Bing, Ask, AOL and Duckduckgo All these search engines (including Google) make use of data science algorithms to deliver the best result for our searched query in fraction of seconds. Considering the fact that, Google processes more than 20 petabytes of data everyday. Had there been no data science, Google wouldn’t have been the ‘Google’ we know today.
  • #37: Starting from the display banners on various websites to the digital bill boards at the airports – almost all of them are decided by using data science algorithms. This is the reason why digital ads have been able to get a lot higher CTR than traditional advertisements. They can be targeted based on user’s past behaviour. This is the reason why I see ads of analytics trainings while my friend sees ad of apparels in the same place at the same time.
  • #38: Internet giants like Amazon, Twitter, Google Play, Netflix, Linkedin, imdb and many more uses this system to improve user experience. The recommendations are made based on previous search results for a user.
  • #39: You upload your image with friends on Facebook and you start getting suggestions to tag your friends. This automatic tag suggestion feature uses face recognition algorithm. Similarly, while using whatsapp web, you scan a barcode in your web browser using your mobile phone. In addition, Google provides you the option to search for images by uploading them. It uses image recognition and provides related search results.
  • #40: Some of the best example of speech recognition products are Google Voice, Siri, Cortana etc. Using speech recognition feature, even if you aren’t in a position to type a message, your life wouldn’t stop. Simply speak out the message and it will be converted to text. However, at times, you would realize, speech recognition doesn’t perform accurately.
  • #41: EA Sports, Zynga, Sony, Nintendo, Activision-Blizzard have led gaming experience to the next level using data science. Games are now designed using machine learning algorithms which improve / upgrade themselves as the player moves up to a higher level. In motion gaming also, your opponent (computer) analyzes your previous moves and accordingly shapes up its game.
  • #42: At a basic level, these websites are being driven by lots and lots of data which is fetched using APIs and RSS Feeds. If you have ever used these websites, you would know, the convenience of comparing the price of a product from multiple vendors at one place. PriceGrabber, PriceRunner, Junglee, Shopzilla, DealTime are some examples of price comparison websites. Now a days, price comparison website can be found in almost every domain such as technology, hospitality, automobiles, durables, apparels etc.
  • #43: Airline Industry across the world is known to bear heavy losses. Except a few airline service providers, companies are struggling to maintain their occupancy ratio and operating profits. With high rise in air fuel prices and need to offer heavy discounts to customers has further made the situation worse. It wasn’t for long when airlines companies started using data science to identify the strategic areas of improvements. Now using data science, the airline companies can: Predict flight delay Decide which class of airplanes to buy Whether to directly land at the destination, or take a halt in between (For example: A flight can have a direct route from New Delhi to New York. Alternatively, it can also choose to halt in any country.) Effectively drive customer loyalty programs Southwest Airlines, Alaska Airlines are among the top companies who’ve embraced data science to bring changes in their way of working.
  • #44: One of the first applications of data science originated from Finance discipline. Companies were fed up of bad debts and losses every year. However, they had a lot of data which use to get collected during the initial paper work while sanctioning loans. They decided to bring in data science practices in order to rescue them out of losses. Over the years, banking companies learned to divide and conquer data via customer profiling, past expenditures and other essential variables to analyze the probabilities of risk and default. Moreover, it also helped them to push their banking products based on customer’s purchasing power.
  • #45: Logistic companies like DHL, FedEx, UPS, Kuhne+Nagel have used data science to improve their operational efficiency. Using data science, these companies have discovered the best routes to ship, the best suited time to deliver, the best mode of transport to choose thus leading to cost efficiency, and many more to mention. Further more, the data that these companies generate using the GPS installed, provides them a lots of possibilities to explore using data science.
  • #47: Medical Image Analysis Genetics and Genomics Drug Development Virtual assistance for patients and customer support
  • #48: Data Science and Virtual Reality do have a relationship, considering a VR headset contains computing knowledge, algorithms and data to provide you with the best viewing experience. A very small step towards this is the high trending game of Pokemon GO. The ability to walk around things and look at Pokemon on walls, streets, things that aren’t really there. The creators of this game used the data from Ingress, the last app from the same company, to choose the locations of the Pokemon and gyms.
  • #50: Imagine a world, where we are surrounded by robots like these. Will they do any good for us? 
  • #52: Data scientists are given the opportunity to develop smart data-driven applications that enable the reduce unnecessary energy use,” says Ronald Root, Senior Data Driven Business Developer & Privacy Officer for Eneco.
  • #54: Data scientists will develop solutions with our open data, in which man and machine can work together to benefit the people
  • #55: a data-science organization that is solely focused on social good and offers various opportunities for volunteering, whether it’s through mentoring or using your data science skills to help solve a social problem
  • #56: A newer, socially-focused competition platform, DrivenData partners with various organizations. These organizations are typically non-profit, focused on difficult social problems with real-world impact.
  • #57: A resourceful data scientist can identify and work to solve social good problems on their own, with the data available to them. A great resource for data is the Gap Minder Foundation which provides statistics to understand global trends. Rather than obscuring statistics with emotions or drama, Gap Minder emphasizes objectivity to promote genuine understanding of our world so that we can work better to make it better.
  • #58: Data science positions exist and continue to emerge across all sectors, from the private to the public and non-profit sectors. There are so many opportunities to make a meaningful social impact in your professional endeavors. Within the private sector, there are certainly companies that develop innovative solutions to greater societal problems. Data science work is also available for organizations that are oriented towards serving the public good. Governments are beginning to recognize the importance of data in understanding their citizenry, particularly its use in implementing effective, evidence-based interventions and policies.
  • #60: Customers are the soul and base of any brand and have a great role to play in their success and failure. With the use of data science, brands can connect with their customers in a personalized manner, thereby ensuring better brand power and engagement. When brands and companies utilize this data in a comprehensive manner, they can share their story with their target audience, thereby creating better brand connect. After all, nothing connects with consumers like an effective and powerful story, that can inculcate all human emotions. With so many tools being developed, almost on a regular basis, big data is helping brands and organisations to solve complex problems in IT, human resource, and resource management in an effective and strategic manner. This means effective use of resources, both material and non-material.
  • #61: 4. Understanding the implications of data science can go a long way in helping sectors to analyze their challenges and address them in an effective fashion. 5. There is a large amount of data available in the world today and utilizing them in an proper manner can spell success and failure for brands and organizations. Utilizing data in a proper manner will hold the key for achieving goals for brands, especially in the coming times.
  • #62: Learning data science can be really hard.