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ANALYTICS SOLUTIONS
Power Business Growth With Data-Driven
Decision-Making
Q. Analytics & data science…is there a difference?
● Yes. Although we use the terms interchangeably, there is a
difference. While data science deals with questions that should be
asked, analytics focuses more on answering these questions.
Q. So, how does data science help me?
● With data science, you can solve the most challenging business
questions, extract actionable insights from data, and power
business growth with data-driven decision-making.
Q. Okay, so how do we, at Grazitti, help businesses make data-driven
decisions?
● The complexity of the questions that you’re able to answer
depends on the level of analytics maturity you’re at. Let’s find out
how we help businesses through these levels of maturity to drive
growth.
Questions You May Have
● Descriptive
● Predictive
● Prescriptive
Level of Analytics Maturity
● Understand past and
current events better by
describing or summarizing
existing data.
● Solutions:
▪ Data Mining
▪ ETL
▪ Data Warehousing
▪ Data Visualization
Descriptive Analytics
● Transform raw data into
actionable information.
● Example: Exploring large
databases and improving
market segmentation to
launch highly-
personalized campaigns.
Data Mining
● Extract, Transform, and Load the data you require, from multiple sources.
ETL
● Build a central repository of integrated data
● Example: Building a data warehouse with
customer information from a company’s point-of-
sale systems, website, mailing lists, and
comment cards
Data Warehousing
● View important data in a visually appealing format.
Data Visualization
Descriptive Analytics Tools
● Predict possible outcomes
and discover trends.
● Solutions:
▪ Statistical Analysis
▪ Extrapolation Forecasting
▪ Predictive Modeling
Predictive Analytics
Statistical Analysis
● Learn what could happen in
the future
● Example: Summarizing data,
such as by making a pie chart
Extrapolation Forecasting
● Learn what could happen if current trends continue
Image Source: https://xkcd.com/605/
Predictive Modeling
● Learn what will happen if you were to change factor X, Y, or Z
Predictive Analytics Tools
● Prescribe the best achievable
outcome
● Solutions:
▪ Optimization Analysis
▪ Machine Learning
Prescriptive Analytics
Optimization Analysis
● Learn more about the best
course of action you can take
● Example: Find out how many
products of each type you
need to manufacture from the
number of parts you have, in
order to maximize profits and
make effective use of your
inventory
Machine Learning
● Learn from this outcome and
find out how to address it.
Examples:
● Virtual Personal Assistants
such as Siri, Alexa, Google Now
● GPS Traffic Predictions
● Video Surveillance
Prescriptive Analytics
Thank You
To learn more, please visit : https://www.grazitti.com/services/data-science/

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ANALYTICS SOLUTIONS

  • 1. ANALYTICS SOLUTIONS Power Business Growth With Data-Driven Decision-Making
  • 2. Q. Analytics & data science…is there a difference? ● Yes. Although we use the terms interchangeably, there is a difference. While data science deals with questions that should be asked, analytics focuses more on answering these questions. Q. So, how does data science help me? ● With data science, you can solve the most challenging business questions, extract actionable insights from data, and power business growth with data-driven decision-making. Q. Okay, so how do we, at Grazitti, help businesses make data-driven decisions? ● The complexity of the questions that you’re able to answer depends on the level of analytics maturity you’re at. Let’s find out how we help businesses through these levels of maturity to drive growth. Questions You May Have
  • 3. ● Descriptive ● Predictive ● Prescriptive Level of Analytics Maturity
  • 4. ● Understand past and current events better by describing or summarizing existing data. ● Solutions: ▪ Data Mining ▪ ETL ▪ Data Warehousing ▪ Data Visualization Descriptive Analytics
  • 5. ● Transform raw data into actionable information. ● Example: Exploring large databases and improving market segmentation to launch highly- personalized campaigns. Data Mining
  • 6. ● Extract, Transform, and Load the data you require, from multiple sources. ETL
  • 7. ● Build a central repository of integrated data ● Example: Building a data warehouse with customer information from a company’s point-of- sale systems, website, mailing lists, and comment cards Data Warehousing
  • 8. ● View important data in a visually appealing format. Data Visualization
  • 10. ● Predict possible outcomes and discover trends. ● Solutions: ▪ Statistical Analysis ▪ Extrapolation Forecasting ▪ Predictive Modeling Predictive Analytics
  • 11. Statistical Analysis ● Learn what could happen in the future ● Example: Summarizing data, such as by making a pie chart
  • 12. Extrapolation Forecasting ● Learn what could happen if current trends continue Image Source: https://xkcd.com/605/
  • 13. Predictive Modeling ● Learn what will happen if you were to change factor X, Y, or Z
  • 15. ● Prescribe the best achievable outcome ● Solutions: ▪ Optimization Analysis ▪ Machine Learning Prescriptive Analytics
  • 16. Optimization Analysis ● Learn more about the best course of action you can take ● Example: Find out how many products of each type you need to manufacture from the number of parts you have, in order to maximize profits and make effective use of your inventory
  • 17. Machine Learning ● Learn from this outcome and find out how to address it. Examples: ● Virtual Personal Assistants such as Siri, Alexa, Google Now ● GPS Traffic Predictions ● Video Surveillance
  • 19. Thank You To learn more, please visit : https://www.grazitti.com/services/data-science/