Data science explained through the example of baking a cake. Check out the steps, the different aspects and all the best reasons why it's worth it to be databased! Read the complete blog post: https://www.extentia.com/single-post/Lets-Bake-a-Data-Science-Cake

1. LET’S BAKE A DATA
SCIENCE CAKE!

2. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms
and systems to extract knowledge and insights from data in various forms, both structured
and unstructured.*
*source: WikiPedia
Machine
learning
Business
Economics
Programming
Data
science

4. React on existing
demand
Understand the
factors that might
influence your
market demand –
the consumer
preference, the
time of the day,
and more
Let’s take the
example of a bakery
– if there is a
demand for cakes,
factors might be:
• Time (when do
people normally
consume cake)
• Preference (what
type of cake)
• Quantity
Competitor’s
sales data
Market
research
Sales
reports
WHAT? HOW? EXAMPLE

5. A number of
statistical measures
to derive insights
from past instances
Everybody knows a
cake recipe will
require flour,
however, while corn
flour, gram flour, or
any other type can be
used, most customers
prefer cakes made
with white flour
Understand which
ingredients, products,
and methods have been
not only been historically
significant but also
most preferred
WHAT? HOW? EXAMPLE

6. Find the
most optimized
solution through
statistical modeling
or machine learning
techniques
Predict the number
and size of cakes
that need to be
baked
DECISION
Demand
Available
resources
Firm’s
capacity
Consumer
preferences
Build a model that can be
used to predict values
WHAT? HOW? EXAMPLE

7. Not reaching the
planned numbers
can potentially
lead to financial
losses!
People don’t eat
the cake, or leave
some of it,
contributing to a
loss of ingredients,
baking time, and
the cook’s salary
Monitoring the results
closely can help
determine the direction
a business is taking
Modifying strategies if
they threaten the
business with possible
losses
THE IMPORTANCE OF KPIS:
Without understanding WHAT has happened, it is impossible to
determine WHY it happened – and impossible to proceed with
interpreting results and developing our strategies.
WHAT? HOW? EXAMPLE

8. Aim of
diagnostic
analytics
Identify anomalies
Drill into the
analytics
Determine casual
relationships
Search for hidden relationships
that might have led to the
unexpected outcome
Look for patterns outside the
existing data sets
Raise questions that can
not be answered by data,
and need further research
Diagnosing the
problem, that
enables drawing
conclusions

9. FAULT IN ANALYTICS CAN
LEAD TO FINANCIAL LOSSES!
Analyzing possible
faults in production
and detecting
methods to correct
them
Suppose we used
salt instead of
sugar for the cake
– we will have to
throw the cake.
Suggests solutions in
order to find the best
possible course of
action for a given
situation.
WHAT? HOW? EXAMPLE

10. Get all necessary inputs to produce the best product
Get the right quantity of the needed inputs
Minimize the losses from producing goods that won’t be purchased

11. Thank You!
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