analytics 101 - getting started

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Analytics : Understanding Patterns Tuesday 10 July 2012

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This deck can be used to conceptualize the concept of analytics and how easy is it to get started on analytics

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Page 1: Analytics 101 - Getting Started

Analytics : Understanding Patterns

Tuesday 10 July 2012

Page 2: Analytics 101 - Getting Started

The Universal Language of Measures

• Time

• Proportions

• Size

• Financials

• Productivity

• Loyalty

Tuesday 10 July 2012

Page 3: Analytics 101 - Getting Started

The Universal Language of Cause & Effect

• Process & Scale

• Habits & Health

• Technology & Efficiency

• Consumer Understanding & Pricing

• Risk & Return

• Action & Outcome

Tuesday 10 July 2012

Page 4: Analytics 101 - Getting Started

Possibilities of no pattern unlikely ........

Cause

Effect

Analytics is finding the relationship/ path of Cause to Effect

Effect = fn ( Data , Math , Common Sense)

Tuesday 10 July 2012

Page 5: Analytics 101 - Getting Started

Sources of Data

• Survey’s

• Transaction Systems

• Free Text

• Digital Images

• Sensors

• Voice

• GPS

• ..... Upto the Imagination

Tuesday 10 July 2012

Page 6: Analytics 101 - Getting Started

Fundamental Concepts

• Exponential Increase in Computing Power

• Explosion of Digitized Data

• Open Source Data Mining & Statistical Software

• Democratization of Multivariate Analytics ( N- Dimensional Plane )

Tuesday 10 July 2012

Page 7: Analytics 101 - Getting Started

Tools For Data Mining & Predictive Modeling

Tuesday 10 July 2012

Page 8: Analytics 101 - Getting Started

Universal Applications

• Direct Marketing

• Scoring Applications

• Forecasting

• Identifying critical influencing drivers

• Marketing

• Customer Service

• HR

• Across all functions....

Regression - Deriving Drivers Cluster - Classifying & Grouping

Tuesday 10 July 2012

Page 9: Analytics 101 - Getting Started

Evolution of Analytics - The Answers

Survey Analytics - Can I ask you?

Transaction Data Analytics -You buy so you are

Social Media Analytics - You are the company you keep

Sentiment Analytics - You are what you feel

Thought Analytics - You are how you think

Pre 80’s

2005

2008

2010

Tuesday 10 July 2012

Page 10: Analytics 101 - Getting Started

Evolution of Analytics - The Data & Techniques

Questionnaire / Cross Tabs /Univariate /Bivariate

Transaction Databases /Multivariate

Web Logs / Text Mining/Multivariate

Text /Voice/Imaging / Artificial Intelligence

Sensors / Artificial Intelligence

Pre 80’s

2005

2008

2010

Tuesday 10 July 2012

Page 11: Analytics 101 - Getting Started

Executing Analytics Projects

CRoss Industry Standard Process for Data Mining (CRISP-DM) for developing and deploying analytics solutions

Problem Objectives

Data Study

Data

Preparation

Analysis & Modeling

Evaluation

Reporting &

Deployment

Determine Problem

objectives

Assess situation

Determine

data mining goals

Produce

project plan

Collect initial data

Describe data

Explore data

Verify data

quality

Select data

Clean data

Construct data

Integrate data

Format data

Select analysis / modeling technique

Generate test

design

Build model

Assess model

Evaluate results

Review process

Determine next steps

Plan deployment

Plan monitoring and maintenance

Produce final

report

Review project

Domain expert finalizes objectives with client

Analysts use data mining software to integrate and understand relevant data

Complex data cleansing algorithms used to collate all relevant data into an analytical data mart.

Statisticians select techniques) based on hypothesis. Business consultants and analysts collaborate to unearth key drivers and forecast key business indicators.

The solutions are evaluated and validated by the business users and practice head.

The solutions are integrated with the relevant business processes.

Tuesday 10 July 2012

Page 12: Analytics 101 - Getting Started

Career Options

Captives Core

3rd Party ITES Boutique

Offshoring Geo Independent

Internal Client

External Client

Products

Analytics Division of Leading Companies

Small Companies Focused on Niche Vertical & Function

BI / Analytics Verticals of most ITES firms

BFSI/ Retail Captives

Product Companies Like SAS/IBM- SPSS/ STATISTICA etc

Tuesday 10 July 2012

Page 13: Analytics 101 - Getting Started

Techniques of Data Mining - 1

Technique Category Description

Summarizing data Data Understanding Frequency counts of categorical variables . Central Tendency Measures for Numeric

Standardizing data Data cleansing / Normalization Format standardization , missing value treatments

Merging / Appending Data Preparation Integrating multiple databases to create single database (datamart buildup )

Variable Creation / Integration Data Preparation Creating Variables which the users understand and derive meaning

Cross Tabulation ReportingHigh level reporting of 2*2 or more variables

Cubes ReportingMulti level and real time drill downs of all relevant variables

Macro’s Automation Automatic generations of all standard reports / cubes.

Tuesday 10 July 2012

Page 14: Analytics 101 - Getting Started

Techniques of Data Mining - 2

Technique Category Description

Measures of Central Tendency Data Understanding Enables identifying the outliers and the central values

Hypothesis Testing / Correlations Analysis

Identification of whether basic assumptions related to the data are valid or not . Used for simple analysis

Regressions/ Factor Analysis /ARIMA Predictive Modeling

Identifying the factors on which the key situation at hand is dependent on. Forecasting Key Indicators

Clustering Models Grouping / SegmentationBucketing records into mutually homogenous & collectively heterogenous groups

Text Algorithms Grouping Preparing unstructured data to be in a form for advanced statistical modeling

Artificial Intelligence/Neural Networks

Inference and Judgement Analytics

Building automated engines which analyze information in a ‘human’ simulated manner

Decision Trees/Chaid /SEM Grouping / Segmentation Root Cause Analysis , Path / Dependency Analysis

Tuesday 10 July 2012

Page 15: Analytics 101 - Getting Started

Thank You

Tuesday 10 July 2012