The dynamic engine powering contemporary decision-making is data analytics. Data is produced at a never-before-seen rate in today's fast-paced world across a variety of industries, including business, healthcare, finance, and more. It is critical to be able to use, analyze, and draw conclusions from this abundance of data that can be put to use.

1. Introduction to Data Analytics
Presented by:
Nikhil Kumar Tripathy
Department of Electronics and Communications Engineering
Roland Institute of Technology
Berhampur, Odisha
Email I’d- nikhilkumartripathy@gmail.com

2. Agenda
Why Data
Analytics
Conclusion
What is
Analytics
What is data
What is Data
Analytics
Activities of
Data Analytics
Skills for Data
Analytics
Careers in Data
Analytics

3. Data
• The term "data" refers to information that transformed
into a format for processing.
• For example prices, weights, addresses, ages, names,
temperatures, dates, or distances etc.

4. Analytics
• Analytics- discovery and communication of meaningful patterns in data.
• It helps segment audiences by analyze attitudes and trends, producing more specific,
accurate and actionable snapshots of public opinion.
• It includes different tools, technologies and processes find trends and solve problems by
using data.

5. Data analytics

6. Types of Data analytics..
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
Prescriptive
Analytics
Deals with what happened
in the past
Deals with why did it
happened in the past
Deals with what will
happen in future
How can we make it
happen

7. Why data
analytics?

8. Reasons
• Data analyst are in demand.
• The salary and progression are excellent.
• Anyone can get started easily.
• You'll become a quick decision maker.
• Lots of opportunities for growth.

9. Activities in data analytics
Data extraction - Fetch data from database
Data Analysis - Observe the data
Data manipulation - Manipulate the data
Data modelling - Fit a model to the data
Data visualization - Visualize the data

10. What are the
skills required to
become a data
analyst?

13. Career in Data Analytics
Data engineer(Designing, building, and maintaining the infrastructure supports data storage, processing.)
Data analyst(Transforming raw data to useful insights, delivering important knowledge to enhance decision-making.)
Data modeler(Design critical data models helps the organization's decision-making and customer experience.)
Full stack analyst(Includes collecting and integrating, cleaning and analyzing data and presenting insights through visualization.)