SlideShare une entreprise Scribd logo
1  sur  15
Télécharger pour lire hors ligne
Data Scientist“ to be the
sexiest career of the 21st
century.
R A J E E V R A N J A N   D W I V E D I
I N T E G R A T E D M . S C . S T A T I S T I C S
C E N T R A L U N I V E R S I T Y O F R A J A S T H A N
DATA SCIENCE
Data science, also known as data-
driven science, is an interdisciplinary
field of scientific methods,
processes, and systems to extract
knowledge or insights from data in
various forms, either structured or
unstructured, similar to data mining.
Data science is the study of where
information comes from, what it
represents and how it can be turned
into a valuable resource in the creation
of business and IT strategies. Mining
large amounts of structured and
unstructured data to identify patterns
can help an organization rein in costs, 
recognize new market opportunities and
increase the organization's competitive
advantage.
N O W A F T E R K N O W I N G A B O U T
D A T A S C I E N C E , L E T ' S T R Y T O
K N O W W H A T A DATA
SCIENTIST I S ?
A H Y B R I D O F D A T A H A C K E R ,
A N A L Y S T , C O M M U N I C A T O R ,
A N D T R U S T E D A D V I S E R .
DATA SCIENTIST
A PERSON EMPLOYED TO ANALYSE AND INTERPRET COMPLEX DIGITAL DATA,
SUCH AS THE USAGE STATISTICS OF A WEBSITE, ESPECIALLY IN ORDER TO
ASSIST A BUSINESS IN ITS DECISION-MAKING.
WHAT DOES
A 
DATA
SCIENTIST
DO?
> Conduct un-directed research and frame
open-ended industry questions
> Extract huge volumes of data from multiple
internal and external sources
> Employ sophisticated analytics programs,
machine learning and statistical methods to
prepare data for use in predictive and
prescriptive modelling
> Thoroughly clean and prune data to discard
irrelevant information
> Invent new algorithms to solve problems and
build new tools to automate work
> Recommend cost-effective changes to existing
procedures and strategies
> And many more...
Data visualization: the presentation of data
in a pictorial or graphical format so it can be
easily analyzed.
Machine learning: a branch of artificial
intelligence based on mathematical
algorithms and automation.
Deep learning: an area of machine learning
research that uses data to model complex
abstractions.
Pattern recognition: technology that
recognizes patterns in data (often used
interchangeably with machine learning).
Data preparation: the process of converting
raw data into another format so it can be
more easily consumed.
DATA SCIENTIST’S
TOOLBOX
“THE SEXY JOB IN THE
NEXT 10 YEARS WILL BE
STATISTICIANS. PEOPLE
THINK I’M JOKING, BUT
WHO WOULD’VE
GUESSED THAT
COMPUTER ENGINEERS
WOULD’VE BEEN THE
SEXY JOB OF THE
1990S?”
HAL R. VARIAN
DEMAND OF DATA
SCIENTIST
0
10
20
30
40
50
Item 1 Item 2 Item 3 Item 4 Item 5
IS INCREASING AT EXPONENTIAL RATE.
SCOPE
GOOGLE INTUTI LINKED IN
ZYNGA
AND MANY MORE...
 A  DATA  SCIENTIST  BRINGS
THE WORK OF THE MANAGER IS
TO LEARN HOW TO IDENTIFY
THE TALENT, ATTRACT IT TO
AN ENTERPRISE, AND MAKE IT
PRODUCTIVE.
Thank You

Contenu connexe

Tendances

The best stats you've ever seen
The best stats you've ever seenThe best stats you've ever seen
The best stats you've ever seenParul Verma
 
yijiang-liu-resume_DA
yijiang-liu-resume_DAyijiang-liu-resume_DA
yijiang-liu-resume_DAYijiang Liu
 
Jiaxin-resume
Jiaxin-resumeJiaxin-resume
Jiaxin-resumeJiaxin Xu
 
It future direction 2013 and beyond
It future direction   2013 and beyondIt future direction   2013 and beyond
It future direction 2013 and beyondsubhaprasad79
 
Data Science and Data Visualization (All about Data Analysis) by Pooja Ajmera
Data Science and Data Visualization (All about Data Analysis) by Pooja AjmeraData Science and Data Visualization (All about Data Analysis) by Pooja Ajmera
Data Science and Data Visualization (All about Data Analysis) by Pooja AjmeraPooja Ajmera
 
Data Science Model Curricilum
Data Science Model CurricilumData Science Model Curricilum
Data Science Model CurricilumNazar Burban
 

Tendances (8)

The best stats you've ever seen
The best stats you've ever seenThe best stats you've ever seen
The best stats you've ever seen
 
yijiang-liu-resume_DA
yijiang-liu-resume_DAyijiang-liu-resume_DA
yijiang-liu-resume_DA
 
Pareto
ParetoPareto
Pareto
 
Jiaxin-resume
Jiaxin-resumeJiaxin-resume
Jiaxin-resume
 
It future direction 2013 and beyond
It future direction   2013 and beyondIt future direction   2013 and beyond
It future direction 2013 and beyond
 
Data Science and Data Visualization (All about Data Analysis) by Pooja Ajmera
Data Science and Data Visualization (All about Data Analysis) by Pooja AjmeraData Science and Data Visualization (All about Data Analysis) by Pooja Ajmera
Data Science and Data Visualization (All about Data Analysis) by Pooja Ajmera
 
Introduction
IntroductionIntroduction
Introduction
 
Data Science Model Curricilum
Data Science Model CurricilumData Science Model Curricilum
Data Science Model Curricilum
 

Similaire à Data scientist

ds.pptx
ds.pptxds.pptx
ds.pptxElves3
 
OVERVIEW OF DATA SCIENCE (3).pdf
OVERVIEW OF DATA SCIENCE (3).pdfOVERVIEW OF DATA SCIENCE (3).pdf
OVERVIEW OF DATA SCIENCE (3).pdfcareer tech
 
Data Analytics Training Course in Noida.pptx
Data Analytics Training Course in Noida.pptxData Analytics Training Course in Noida.pptx
Data Analytics Training Course in Noida.pptxAPTRON Solutions Noida
 
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptx
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptxUnlocking Insights_ The Power of Data Analytics in the Modern World.pptx
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptxAPTRON Solutions Noida
 
_What Is Data Science.pdf
_What Is Data Science.pdf_What Is Data Science.pdf
_What Is Data Science.pdfFlyWly
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data ScienceSwapnilSaurav10
 
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptx
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptxINTRODUCTION TO DATA SCIENCE -CONCEPTS.pptx
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptxMadhumitha N
 
DATA SCIENCE PPT1.pptx
DATA SCIENCE PPT1.pptxDATA SCIENCE PPT1.pptx
DATA SCIENCE PPT1.pptxDMKurnool
 
DATA SCIENCE PPT.pptx
DATA SCIENCE PPT.pptxDATA SCIENCE PPT.pptx
DATA SCIENCE PPT.pptxDMKurnool
 
Digicrome Student Hand Book
Digicrome Student Hand BookDigicrome Student Hand Book
Digicrome Student Hand BookAayushdigichrome
 
Basic analtyics & advanced analtyics
Basic analtyics & advanced analtyicsBasic analtyics & advanced analtyics
Basic analtyics & advanced analtyicsDEEPIKA T
 
Data fluency for the 21st century
Data fluency for the 21st centuryData fluency for the 21st century
Data fluency for the 21st centuryMartinFrigaard
 
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGarg
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGargColloquium(7)_DataScience:ShivShaktiGhosh&MohitGarg
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGargShiv Shakti Ghosh
 

Similaire à Data scientist (20)

data science
data sciencedata science
data science
 
Untitled document.pdf
Untitled document.pdfUntitled document.pdf
Untitled document.pdf
 
ds.pptx
ds.pptxds.pptx
ds.pptx
 
Information & data science (1) converted
Information & data science (1) convertedInformation & data science (1) converted
Information & data science (1) converted
 
Data science
Data scienceData science
Data science
 
Data Analytics Course in Noida. pptx
Data Analytics  Course in Noida.     pptxData Analytics  Course in Noida.     pptx
Data Analytics Course in Noida. pptx
 
OVERVIEW OF DATA SCIENCE (3).pdf
OVERVIEW OF DATA SCIENCE (3).pdfOVERVIEW OF DATA SCIENCE (3).pdf
OVERVIEW OF DATA SCIENCE (3).pdf
 
Data Analytics Training Course in Noida.pptx
Data Analytics Training Course in Noida.pptxData Analytics Training Course in Noida.pptx
Data Analytics Training Course in Noida.pptx
 
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptx
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptxUnlocking Insights_ The Power of Data Analytics in the Modern World.pptx
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptx
 
_What Is Data Science.pdf
_What Is Data Science.pdf_What Is Data Science.pdf
_What Is Data Science.pdf
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptx
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptxINTRODUCTION TO DATA SCIENCE -CONCEPTS.pptx
INTRODUCTION TO DATA SCIENCE -CONCEPTS.pptx
 
Difference b/w DataScience, Data Analyst
Difference b/w DataScience, Data AnalystDifference b/w DataScience, Data Analyst
Difference b/w DataScience, Data Analyst
 
DATA SCIENCE PPT1.pptx
DATA SCIENCE PPT1.pptxDATA SCIENCE PPT1.pptx
DATA SCIENCE PPT1.pptx
 
DATA SCIENCE PPT.pptx
DATA SCIENCE PPT.pptxDATA SCIENCE PPT.pptx
DATA SCIENCE PPT.pptx
 
Digicrome Student Hand Book
Digicrome Student Hand BookDigicrome Student Hand Book
Digicrome Student Hand Book
 
Basic analtyics & advanced analtyics
Basic analtyics & advanced analtyicsBasic analtyics & advanced analtyics
Basic analtyics & advanced analtyics
 
Data fluency for the 21st century
Data fluency for the 21st centuryData fluency for the 21st century
Data fluency for the 21st century
 
What is business analytics
What is business analyticsWhat is business analytics
What is business analytics
 
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGarg
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGargColloquium(7)_DataScience:ShivShaktiGhosh&MohitGarg
Colloquium(7)_DataScience:ShivShaktiGhosh&MohitGarg
 

Plus de Rajeev Ranjan Dwivedi

Plus de Rajeev Ranjan Dwivedi (6)

Data communication
Data communicationData communication
Data communication
 
David McCandless: The Beauty of Data Visualization
David McCandless: The Beauty of Data VisualizationDavid McCandless: The Beauty of Data Visualization
David McCandless: The Beauty of Data Visualization
 
What do we do with all this big
What do we do with all this big What do we do with all this big
What do we do with all this big
 
Are You Data-Driven?
Are You Data-Driven? Are You Data-Driven?
Are You Data-Driven?
 
Make data more human by jer thorp
Make data more human by jer thorpMake data more human by jer thorp
Make data more human by jer thorp
 
HOW TO THINK LIKE A DATA SCIENTIST
HOW TO THINK LIKE A DATA SCIENTISTHOW TO THINK LIKE A DATA SCIENTIST
HOW TO THINK LIKE A DATA SCIENTIST
 

Dernier

Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfchloefrazer622
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfJayanti Pande
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introductionMaksud Ahmed
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024Janet Corral
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxVishalSingh1417
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 

Dernier (20)

Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdf
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 

Data scientist

  • 1. Data Scientist“ to be the sexiest career of the 21st century.
  • 2. R A J E E V R A N J A N   D W I V E D I I N T E G R A T E D M . S C . S T A T I S T I C S C E N T R A L U N I V E R S I T Y O F R A J A S T H A N
  • 3. DATA SCIENCE Data science, also known as data- driven science, is an interdisciplinary field of scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs,  recognize new market opportunities and increase the organization's competitive advantage.
  • 4. N O W A F T E R K N O W I N G A B O U T D A T A S C I E N C E , L E T ' S T R Y T O K N O W W H A T A DATA SCIENTIST I S ?
  • 5. A H Y B R I D O F D A T A H A C K E R , A N A L Y S T , C O M M U N I C A T O R , A N D T R U S T E D A D V I S E R .
  • 6. DATA SCIENTIST A PERSON EMPLOYED TO ANALYSE AND INTERPRET COMPLEX DIGITAL DATA, SUCH AS THE USAGE STATISTICS OF A WEBSITE, ESPECIALLY IN ORDER TO ASSIST A BUSINESS IN ITS DECISION-MAKING.
  • 7. WHAT DOES A  DATA SCIENTIST DO? > Conduct un-directed research and frame open-ended industry questions > Extract huge volumes of data from multiple internal and external sources > Employ sophisticated analytics programs, machine learning and statistical methods to prepare data for use in predictive and prescriptive modelling > Thoroughly clean and prune data to discard irrelevant information > Invent new algorithms to solve problems and build new tools to automate work > Recommend cost-effective changes to existing procedures and strategies > And many more...
  • 8. Data visualization: the presentation of data in a pictorial or graphical format so it can be easily analyzed. Machine learning: a branch of artificial intelligence based on mathematical algorithms and automation. Deep learning: an area of machine learning research that uses data to model complex abstractions. Pattern recognition: technology that recognizes patterns in data (often used interchangeably with machine learning). Data preparation: the process of converting raw data into another format so it can be more easily consumed. DATA SCIENTIST’S TOOLBOX
  • 9. “THE SEXY JOB IN THE NEXT 10 YEARS WILL BE STATISTICIANS. PEOPLE THINK I’M JOKING, BUT WHO WOULD’VE GUESSED THAT COMPUTER ENGINEERS WOULD’VE BEEN THE SEXY JOB OF THE 1990S?” HAL R. VARIAN
  • 10. DEMAND OF DATA SCIENTIST 0 10 20 30 40 50 Item 1 Item 2 Item 3 Item 4 Item 5 IS INCREASING AT EXPONENTIAL RATE.
  • 11. SCOPE GOOGLE INTUTI LINKED IN ZYNGA AND MANY MORE...
  • 12.
  • 14. THE WORK OF THE MANAGER IS TO LEARN HOW TO IDENTIFY THE TALENT, ATTRACT IT TO AN ENTERPRISE, AND MAKE IT PRODUCTIVE.