Introduction: The New World of Enterprise Analytics
increase in data
need to differentiate products
tenfold increase from 90 to 2010 (linkedin)
10x from 2005 to 2012 "analytics"
the rise of big data
IIA and the Research for this Book
International Institute for Analytics: IIA
3-5 page topics
write-ups of meetings
general enterprise topics
Part I: Overview of Analytics and Their Value
1. What Do We Talk About When We Talk About Analytics?
terms for decision-making from data
70s: decision support systems
80s: executive information systems
80s: online analytical processing (olap)
90s: business intelligence
statistical and quantitative analysis
explanatory and predictive models
Why We Needed a New Term: Issues with Traditional Business Intelligence
too much verbiage
with more quantitative slant
Three Types of Analytics
ad hoc reports
how many, how often?
what exactly is problem
what actions needed
what happened in past
why is it happening
what will happen
use models to predict future from past
what if we try this
what's the best that can happen
tell you what to do
Where Does Data Mining Fit In?
discovery of trends and patterns
AI, ML, statistics, database
Business Analytics Versus Other Types
health care analytics
clinical decision support
too many different sources
2. The Return on Investments in Analytics
Traditional ROI Analysis
roi = ( total value / benefits - total investment ) / total investment
selecting high-potential customers for direct-mail campaign
mine CRM data
send mail to customers who meet a criteria
investment cost: 50 K
expected benefit: 75 K
roi = ( 75 - 50 ) / 50 = 50%
cash flow and roi
assumption: costs and benefits occur at the same time
based on credible business case
The Teradata Method for Evaluating Analytics Investments
• Phase 1: Validate business goals and document best-practice usage.
• Phase 2: Envision new capabilities.
• Phase 3: Determine ROI and present findings.
• Phase 4: Communicate.
Phase 1: Validate business goals and document best-practice usage.
strategic business initiatives
documenting best practices
reviewing reports, plans, ...
Part II: Application of Analytics
3 Leveraging Proprietary Data for Analytical Advantage
4. Analytics on Web Data: The Original Big Data
5. The Analytics of Online Engagement