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Introduction to Data Analytics
Course Introduction
What Is Data Analytics?
Data analytics is the science of extracting trends, patterns, and relevant information
from raw data to draw conclusions.
Data Analytics: Benefits
Cost Reduction
Effective decision
making
Improved efficiency
Good resource
utilization
Good market
insights
DATA
ANALYTICS
Data Analytics: Domains
Retail
Industry
Media and
Entertainment
Industry
Education
Industry
Government
Organizations
E-Commerce
Industry
Healthcare
Industry
Data Analytics Domains
Course Outline
Course
Introduction
Evolution
of Data
Analytics
Dealing with Different
Types of Data
Data
Visualization
for Decision
Making
Data Analytics,
Data Science, and
Machine Learning
1
2
3
4
5
6
Data Science
Methodology
7
Data Analytics in
Different Sectors
8
Analytics Framework,
Case Study, and
Upcoming Trends
Learning Outcomes
By the end of this course, you will be able to:
● Analyze the triggers that led to the evolution of
analytics
● Develop an analytical approach to a business problem
● Compare data science, data analytics, and machine
learning and understand their business application
● Explain the significance of data visualization in
analytical modeling to drive meaningful business
decisions
● Identify business use cases that can leverage data
analytics
Course Features
Number of case studies: 11
Number of research studies: 2
Course Features
Few case studies discussed in this course:
Amazon uses data analytics to improve efficiency and reduce cost.
LinkedIn employs data analytics to revamp its job listings, track
user profiles, and posts.
Netflix gathers data from its subscribers to decide on customer
preferences.
Course Features
Research Studies
According to McKinsey, companies that use customer analytics
outsmart their competitors in terms of profit.
According to a survey conducted by the Business Application
Research Center (BARC) on the BI trends, Master Data and Data
Quality Management are the most important trend in 2020.
Happy Learning

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1_Course Introduction Data scince and machine learning

  • 3. What Is Data Analytics? Data analytics is the science of extracting trends, patterns, and relevant information from raw data to draw conclusions.
  • 4. Data Analytics: Benefits Cost Reduction Effective decision making Improved efficiency Good resource utilization Good market insights DATA ANALYTICS
  • 5. Data Analytics: Domains Retail Industry Media and Entertainment Industry Education Industry Government Organizations E-Commerce Industry Healthcare Industry Data Analytics Domains
  • 6. Course Outline Course Introduction Evolution of Data Analytics Dealing with Different Types of Data Data Visualization for Decision Making Data Analytics, Data Science, and Machine Learning 1 2 3 4 5 6 Data Science Methodology 7 Data Analytics in Different Sectors 8 Analytics Framework, Case Study, and Upcoming Trends
  • 7. Learning Outcomes By the end of this course, you will be able to: ● Analyze the triggers that led to the evolution of analytics ● Develop an analytical approach to a business problem ● Compare data science, data analytics, and machine learning and understand their business application ● Explain the significance of data visualization in analytical modeling to drive meaningful business decisions ● Identify business use cases that can leverage data analytics
  • 8. Course Features Number of case studies: 11 Number of research studies: 2
  • 9. Course Features Few case studies discussed in this course: Amazon uses data analytics to improve efficiency and reduce cost. LinkedIn employs data analytics to revamp its job listings, track user profiles, and posts. Netflix gathers data from its subscribers to decide on customer preferences.
  • 10. Course Features Research Studies According to McKinsey, companies that use customer analytics outsmart their competitors in terms of profit. According to a survey conducted by the Business Application Research Center (BARC) on the BI trends, Master Data and Data Quality Management are the most important trend in 2020.