Presentation about Business Analytics and Data Science 101

1. Introduction to Business Analytics and
Data Science
Version 1.0
[Talend Imagine Team] Anthony

2. ABOUT BUSINESS ANALYTICS
. • What is Business Analytics ?
Business analytics is the process of using quantitative methods to
derive meaning from data in order to make informed business
decisions.
There are three primary methods of business analysis:
 Descriptive: Use historical data to identify trends and patterns.
 Predictive: The use of statistics to forecast future outcomes.
 Prescriptive: The application of testing and other techniques to
determine which outcome will yield the best result in a given
scenario.
• What is Benefit with Business Analytics ?
• With business analytics we can give insight based on data and
analysis result for strategic decision.
• Improved operation efficiency. Beyond financial gains, analytics can
be used to fine tune business operations.
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3. VISUAL PERSPECTIVE OF BUSINESS ANALYTICS
.
Modern business analytics can be viewed as an integration of BI/IS, statistics, and modelling and
optimization as illustrated in Figure.
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4. CRISP-DM
.
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CRISP-DM breaks the process
of data mining into six major
phases:
•Business Understanding
•Data Understanding
•Data Preparation
•Modelling
•Evaluation
•Deployment

5. 5
 SQL various databases
 Excel Spreadsheets
 Tableau Software Simple drag and drop tools for visualizing
data from spreadsheets and other databases.
 IBM Cognos Express An integrated business intelligence and
planning solution designed to meet the needs of midsize companies,
provides reporting, analysis, dashboard, scorecard, planning,
budgeting and forecasting capabilities.
 SAS / SPSS / Rapid Miner Predictive modelling and data
mining, visualization, forecasting, optimization and model
management, statistical analysis, text analytics, and more using
visual workflows.
 R / Python Advanced programming-based data preparation,
analytics and visualization.
TOOL & SOFTWARE USED BY BUSINESS ANALYTICS
Database queries
and analysis
Spreadsheets
Data visualization
Dashboards to report key
performance measures
Data and Statistical
methods
Data Mining basics
(predictive models)
Tools Software
Anthony

6. BIG DATA TECHNOLOGY
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Big data refer to massive amounts of business data from a wide variety of sources, much of which is
available in real time, and much of which is uncertain or unpredictable.

7. USE CASE BUSINESS ANALYTICS IN DEALERSHIP
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Use Case : Prediction customer doing service to dealer based on milage and period service
Business Understanding :
(1) Increase customer satisfaction for reminder for service.
(2) Prediction stock spare parts for support service activity
(3) Increase Dealer Revenue
Data Understanding :
(1) Customer Profile & Service History.
(2) Standard Service based on Service Booklet
(3) Telematic Data (ODB2)
Modelling and Prediction :
(1) Prediction next service for vehicle based on
Customer behaviour on use vehicle.
(2) Prediction spare part that need to be replace based on
Customer locations.

8. THANK YOU
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Anthony