7. Disrupting Retail
Profiles Attributes
Explicit data
500 million individual data points
No two fixes the same
Stores feed real-time behavior to design
Concept-to-shelf: 12 months to 2 weeks
Scarcity as the business model
Unsold inventory <10% (20% is standard)
“What customers buy
and why, and what
they don’t buy and why
not, is very powerful.”
14. -Understanding the skill sets needed today
and tomorrow
-Redefining roles and skill sets to take
advantage of new data available
-Training and retraining employees is a
distinguishing capability to remain relevant
Key Patterns
17. History of the Telephone
Began point-to-point
Provided an apparatus
for transmission
The telephone exchange switchboard
provided a consistent structure and
unified points of access.
18. Spark unifies data, enabling real-time insights
IT Today IT on Spark
complex | disparate | limited flexible | unified | unlimited
19. Spark processes and analyzes data from ANY data source
Business Applications and Business Intelligence
Apache Spark
Spark
SQL
Spark
Streaming
MLlib
(machine
learning)
GraphX
Hadoop Database Mainframe
Data-
warehouse
20. The Big Data Maturity Curve
Big Data Maturity
Value Operations Data
Warehousing
Line of Business
and Analytics
New Business
Imperatives
We are here
Lower the Cost
of Storage
Warehouse
Modernization
• Data lake
• Data offload
• ETL offload
• Queryable archive
and staging
Data-informed
Decision Making
• Full dataset
analysis (no more
sampling)
• Extract value from
non-relational data
• 360 view of all
enterprise data
• Exploratory analysis
and discovery
Business
Transformation
• Create new
business models
• Risk-aware
decision making
• Fight fraud and
counter threats
• Optimize
operations
• Attract, grow,
retain customers