In fiercely competitive industries, data analytics platforms are implemented to enable the best use of analytics. As the world produces exponentially more data over time, there is an increasing need to acquire the data, organise it, and study it. The basics of obtaining, loading, and efficiently manipulating raw data from diverse sources to achieve business goals will be taught to learners, along with industry best practises for managing various forms of data, proper manipulation, and coding. They will experience first-hand real-world issues with non-trial datasets. The learner will leave this course at MAGES Institute with the abilities and resources needed to approach business data issues programmatically.

1. THE FUTURE STARTS HERE
Different types of Data
Analytics
HARNESS THE POWER OF ANALYTICS
CONVERT RAW DATA INTO ACTIONABLE INSIGHTS
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4. WHY LEARN DATA ANALYTICS?
• As more and more companies move to the cloud, the need for data science
and engineering talent will further increase
• Rapid growth and demand in digital transformation and advanced
analytics have led to a surge in demand for data science professionals in
key technology areas such as artificial intelligence
• Analytics enables data-driven decision-making which is vital for
corporations today.

5. HOW MUCH
DATA IS GENERATED?
Data is being created all the time without us even
noticing it. Much of what we do every day now happens
in the digital realm, leaving an ever-increasing digital
trail that can be measured and analyzed.
Netflix
Subscribers Stream
77,160 Hours of
Video
UBER
Passengers take
694 Rides Facebook
Users Like
4,166,667 Posts
Twitter
Users Send
347,222 Tweets
YouTube
Users Upload
300 Hours of
new video
Instagram
Users Like
1,736,111 Photos
Pinterest
Users Pin
9,722 Images
Apple
Users Download
51,000 Apps
Reddit
Users CAst
18,327 Votes
Amazon
Receives
4,310 Unique
Visitors
Vine
Users Play
1,041,666 Videos
Tinder
Users Swipe
590,278 Times
Snapchat
Users Share
284,722 Snaps
Buzzfeed
Users View
34,150 Videos
Skype
Users Make
110,040 Calls
Every
Minute of
the Day

7. DATA SCIENCE IN VARIOUS INDUSTRIES
Machine Learning
− Data science is leveraged to
disrupt ML based application
Medical
− Disease prediction
− Analyze patient recovery growth
Insurance
− Fraud and risk detection
− Insurance claims prediction
Retail
− Analyze Consumer Behaviors
− Predict Product Pricing
Enterprise
− Capturing data volume, variety
and value
Healthcare
− Detect Causes of disease
− Risk prediction
Digital Marketing
− Detect targeted audience
− Demographic behavior analysis
Funding
− Detect possible fundraisers

8. The scope of Descriptive Analytics is to describe what has
happened and primarily looks at past data to understand
patterns and trends in the data analysed.
It serves as a base point or starting point for an analytics
strategy.
It utilizes techniques such as data mining, summary
statistics, and clustering to provide past trends.
The Four Types :
Descriptive Analytics

9. Why did this thing happen is the question that falls under
the arena of Diagnostic Analytics.
The basic purpose of this analytics is to find out why a
thing has happened or lay the foundation for the reasons
supporting that event. In this type of analysis, we basically
consider the following:
• Why the event has happened
• Rooted in the past and is based on the concept of
probability
This type of analytics involves comparing all the coexisting
trends and the movements by uncovering the correlation
between certain variables. Moreover, it also determines
casual relationships wherever it is possible.
The Four Types :
Diagnostic Analytics
This Photo by Unknown Author is licensed under CC BY-SA-NC

10. This analysis basically looks at the question of What may
happen in future? This type of analytics is basically
centred around:
• What can happen under a certain condition
• This analytics looks into the future and is also based on
probability
It analyses all the historical trends in tandem with the
industry trends to make informed predictions regarding
the future. Here, in this analytics, historical data and other
variables like economic forecast, industry trends and
consumer confidence.
The Four Types :
Predictive Analytics
This Photo by Unknown Author is licensed under CC BY-SA
This Photo by Unknown Author is licensed under CC BY-SA-NC

11. The prescriptive analytics basically revolved around the
question of ‘what would be your next move’ or ‘how to do a
thing’?
It takes into account all the needed variables that you can
logically anticipate. The agenda of this analytics is:
Based on the required outcomes, what type of actions are
required
This analytics looks into the future and is anchored
towards a certain set of rules
It uses the techniques of simulation analysis, artificial
intelligence and neural networks
This analytics is built on the base of predictive analytics
that determines prescribed actions on the basis of desired
outcomes to help achieve business objectives.
The Four Types :
Prescriptive Analytics

12. Write a one-page memo describing your
color and format choices and how you
customized this visualization to fit the
needs of your audience
Written Task
§ To see the status of the project
§ Attempting to see the performance of
the country
§ Attempting to see the performance of
the submitting officer
Objectives
To use color to determine the size of
project
Color Selection
Click on the size of the project will be able to
see the submitting officer and the respective
country involved and size of the total project.
Format Selection
PROBLEM EXAMPLE (USING PYTHON)

14. The. Majority of Top 100 Universities come from USA, who
has about 8x more top 100 universities than the next best
country: the UK. The difference between the number of top
100 universities between the UK, Japan, France, and
Switzerland is less drastic compared to the disparity
between USA and UK.
With only integers, it's difficult to see if USA is the best
place to go for a quality education because we should be
using a percentage figure of: (Number of world rank Top
100 schools / Total Universities in country) *100 to get a
more accurate representation.
Top 5 Countries w Highest numbers of Top
100 Units

15. THE FUTURE STARTS HERE
The Four Types of Data
Analytics
Thank You for taking the First Step.
Convert raw data into actionable information
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