In this presentation, we will decode the basic differences between data scientist, data analyst and data engineer, based on the roles and responsibilities, skill sets required, salary and the companies hiring them. Although all these three professions belong to the Data Science industry and deal with data, there are some differences that separate them. Every person who is aspiring to be a data professional needs to understand these three career options to select the right one for themselves. Now, let us get started and demystify the difference between these three professions. We will distinguish these three professions using the parameters mentioned below: 1. Job description 2. Skillset 3. Salary 4. Roles and responsibilities 5. Companies hiring This Master’s Program provides training in the skills required to become a certified data scientist. You’ll learn the most in-demand technologies such as Data Science on R, SAS, Python, Big Data on Hadoop and implement concepts such as data exploration, regression models, hypothesis testing, Hadoop, and Spark. Why be a Data Scientist? Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data scientist you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. Simplilearn's Data Scientist Master’s Program will help you master skills and tools like Statistics, Hypothesis testing, Clustering, Decision trees, Linear and Logistic regression, R Studio, Data Visualization, Regression models, Hadoop, Spark, PROC SQL, SAS Macros, Statistical procedures, tools and analytics, and many more. The courseware also covers a capstone project which encompasses all the key aspects from data extraction, cleaning, visualisation to model building and tuning. These skills will help you prepare for the role of a Data Scientist. Who should take this course? The data science role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Scientist Master’s Program, including: IT professionals Analytics Managers Business Analysts Banking and Finance professionals Marketing Managers Supply Chain Network Managers Those new to the data analytics domain Students in UG/ PG Analytics Programs Learn more at https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training

1. Cover slide?
I have asked Siddam again. Will
update it once I get it.

2. What’s in it for you?
Job Description
Skillset
Salary
Roles and Responsibilities
Companies Hiring

3.  A data scientist is one who
uses advanced level of data
techniques to derive to business
conclusions
 He/she is the senior most in the
team and have an in-depth
knowledge of statistics, data
handling and machine learning
 They take the inputs from Data
Engineers and Analysts and
formulate actionable insights for
the business
Data
Scientist

4.  A data scientist is one who
uses advanced level of data
techniques to derive to business
conclusions
 He/she is the senior most in the
team and have an in-depth
knowledge of statistics, data
handling and machine learning
 They take the inputs from Data
Engineers and Analysts and
formulate actionable insights for
the business
Data
Scientist
 A data analyst is an entry-level
member into the data analytics
team
 He/she needs to be good in
technical skills and know the
basics of data handling,
modeling and reporting
 They can move into the roles of
Data Engineer and Data
Scientist with more experience
Data
Analyst

5.  A data scientist is one who
uses advanced level of data
techniques to derive to business
conclusions
 He/she is the senior most in the
team and have an in-depth
knowledge of statistics, data
handling and machine learning
 They take the inputs from Data
Engineers and Analysts and
formulate actionable insights for
the business
Data
Scientist
 A data analyst is an entry-level
member into the data analytics
team
 He/she needs to be good in
technical skills and know the
basics of data handling,
modeling and reporting
 They can move into the roles of
Data Engineer and Data
Scientist with more experience
Data
Analyst
Data
Engineer
 A data engineer is an
intermediary between the data
analyst and the data scientist
 He/she needs to have expertise
in developing, constructing and
maintaining architectures
 Generally, they work on big data
and submit their reports to the
data scientist to analyze

6. Skillset
Programming Languages
Python, R, SQL, SAS, Java
Frameworks
Pig, Spark, Hadoop
Technologies
Machine Learning, Deep
Learning
Data
Scientist

7. Skillset
Programming Languages
Python, R, SQL, SAS, Java
Frameworks
Pig, Spark, Hadoop
Technologies
Machine Learning, Deep
Learning
Data
Scientist
Programming Languages
Python, R, SQL, SAS,
JavaScript
Tools
SAS Miner, Microsoft Excel,
SSAS, SPSS
Data
Analyst

8. Skillset
Programming Languages
Python, R, SQL, SAS, Java
Frameworks
Pig, Spark, Hadoop
Technologies
Machine Learning, Deep
Learning
Data
Scientist
Programming Languages
Python, R, SQL, SAS,
JavaScript
Tools
SAS Miner, Microsoft Excel,
SSAS, SPSS
Data
Analyst
Programming Languages
Python, R, SQL, SAS, Java
Frameworks
Hadoop, MapReduce, Hive,
Pig, Apache Spark, Data
Streaming, NoSQL
Data
Engineer

9. Data
Scientist
$ 137,000
Salary
Source: Glassdoor

10. Data
Scientist
Data
Analyst
$ 137,000 $ 67,000
Salary
Source: Glassdoor

11. Data
Scientist
Data
Analyst
Data
Engineer
$ 137,000 $ 67,000 $ 116,000
Salary
Source: Glassdoor

12. Roles and Responsibilities
• Mine and clean data and
process unstructured data
• Designing models to work on
big data
• Infer and interpret the
analysis on big data
• Lead the entire data team to
achieve their goals
• Deliver conclusions that have
a direct business impact
Data
Scientist

13. Roles and Responsibilities
• Mine and clean data and
process unstructured data
• Designing models to work on
big data
• Infer and interpret the
analysis on big data
• Lead the entire data team to
achieve their goals
• Deliver conclusions that have
a direct business impact
• Gather information from a
database through querying
• Process data and provide
summary reports
• Use basic algorithms in their
work
• Have core skills in statistics,
data munging, data
visualization and exploratory
data analysis
Data
Scientist
Data
Analyst

14. Roles and Responsibilities
• Mine and clean data and
process unstructured data
• Designing models to work on
big data
• Infer and interpret the
analysis on big data
• Lead the entire data team to
achieve their goals
• Deliver conclusions that have
a direct business impact
• Mine through data for
insights
• Convert erroneous data into
a usable form for further
analysis
• Write queries on data
• Maintain the design and
architecture of data
• Create large data
warehouses using ETL
Data
Scientist
Data
Analyst
Data
Engineer
• Gather information from a
database through querying
• Process data and provide
summary reports
• Use basic algorithms in their
work
• Have core skills in statistics,
data munging, data
visualization and exploratory
data analysis

15. Companies Hiring
Data
Scientist

16. Companies Hiring
Data
Scientist
Data
Analyst

17. Companies Hiring
Data
Scientist
Data
Analyst
Data
Engineer