Gayatri Patel, eBay, presents at the Big Analytics 2012 Roadshow The wonders of what data can do for an organization is measured in the productivity and competitiveness of their team's decisions. Some believe more data is the key. Agreed...but good decisions require more than just deriving intelligence from big data. In this dynamic market, the need to socialize and evolve ideas with other teams, quickly correlate information across sources, and test ideas to fail fast early are strong enablers to gain competitive footing. eBay¹s analytic and technology advancements garners insights and approaches that continue to help our employees tell their "data stories" and make better decisions.

1. Extreme Decision-
Making at eBay
Gayatri Patel

2. We All Make Decisions…

3. Our Decision Makers
“I love to
connect
the dots to
“I love to find unique find out
anomalies that have not what is
been discovered yet!” driving our
growth
and why!”
“I love to
monitor
the health
of our
global
operations
with
confidence
and tell
great
stories to
our BoD”

4. Is Customer Brand
improving with last Business
months’ new Motors Marketing
campaign from our Manager
Motors Mobile
Application?
What is the latest
revenue projection for
our coupon campaigns
targeted to enhance
Fashion Search for
large retailer listings?

5. 5

7. Source: McKinsey Global Institute
“Big data: The next frontier for innovation, competition, and productivity”

8. What Makes it Happen?
Lots & Lots & Lots of Data
at eBay

9. BIG Data VVC
>50 TB/day new data >100k data elements
>100 Trillion pairs of information
>100 PB/day Processed
>50k chains of logic
>7500
business users & analysts
Active/Active
turning over a TB every second
24x7 x365 Millions of queries/day
Always online
99.98+% Availability
Near-Real-time
9

10. Who Makes it Happen with
Extreme Analytics at eBay?

11. Researcher Analyst
“I love to
$ “I love to find unique $$ connect
anomalies that have not the dots
been discovered yet!” to find
out what
PM & BM is driving
our
$$$ “I love to
monitor growth
the health and why!”
of our
global
operations
with
confidence
and tell Management &
great Executives
stories to
$$$$
our BoD”
Decision Makers…

12. Capacity Facilities Customer
Procurement
Planning Support
Fraud
Finance Search
Operations
Strategy
Marketing Corporate
Legal
Shipping Supply Chain
HR
IT
Independent Data Marts = Silo Intelligence…

13. 500+ 150+ 5-10
concurrent users concurrent users concurrent users
Analyze & Report
Discover & Explore
Structured Semi-structured Unstructured
SQL SQL++ JAVA / C
Production Data Warehousing Contextual-Complex Analytics Structure the Unstructured
Large Concurrent User-base Deep, Seasonal, Consumable Data Sets Detect Patterns
Enterprise-class System Low End Enterprise-class System Commodity Hardware System
EDW Singularity Hadoop
6+PB 40+PB 20+PB
Data Storage & Processing Platforms

14. There’s No Technology Silver Bullet

15. What is Why is it How to take
happening?* happening?* action?
Harmony Symphony Melody
Informative Enlightened Actionable Opportunistic
Measurements Reasonings Recommendations Decisions
• Iterate…Test-What If…Collaborate-Share
• Trust • Timely
• Quality • Context
Key Questions to Make Informed Decisions

16. Informative Opportunistic
Measurements Decisions
Harmony-Class
Insights
Harmony Vertical (Customer/Inventory)
Harmony Health – Finance & Marketing
50,000 ft
• Cross-Function Metrics
• Business Performance
Summaries
• Personalize views:
• Dimensions
• Attributes
• Deep Dive to Summarized Explore Cube
Data
Harmony Search & Harmony Trading & Trust
Behavior
Quick…Easy…”Personalizable”…”Business-blessed”

17. Informative Enlightened Opportunistic
Measurements Reasonings Decisions
Harmony Trading Harmony Verticals
Harmony-class
Insights
50,000 ft
Symphony-class Symphony Shipping
Symphony Fashion
Insights
Symphony Enthusiast
10,000 ft Symphony Transaction
• Product Performance
• Drill Downs
• What-If/Ad-Hoc
Explore Cube Explore Cube
Quick…Easy…”Personalizable”…”Product-blessed”

18. Data
Customer Inventory Trading Search Enabling
Services
… …
• Dashboards • Summary Tables
• Reports • Aggregate Tables
• Views • In-Memory Caches
• Metrics • Data Feeds
• Measurements The DataHub Portal • Data Files
• Base Tables
Front End Back End
Analytic Assets Analytic Assets
ODW
EDW Singularity Hadoop
Analytic Assets

19. Health Product Customer Inventory Behavior Search Trading Trust
Product Product Product Product Product Product
Harmony
Front End
(4 only)
Symphony
Front End
(1-3)
Common Dimensional Model
Symphony
Back-End
Insights Products

20. Q1 Q2 Q3 Q4
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Health Harmony Harmony Health v3.2 Harmony Health v3.4 Harmony Health v3.6
Insights Health v3.0 3.0 4.0
Symphony v3.3 Symphony v3.5 Symphony v3.7 Symphony v3.9
Trading Symphony
Symphony v0.11 Symphony v1.3 Symphony v1.5 Symphony v1.13 Symphony v1.17
Insights 1.7
Symphony Symphony
Symphony v1.15
Harmony 1.9 v1.11
Trading 1.0 Harmony Trading v1.2 Harmony Trading v1.4 Harmony Trading v1.6 2.0
v1.0
Trust Insights Symphony v0.9
Symphony v1.3 Symphony v1.5 Symphony v1.7 Symphony v1.9
…
• Extends value over time
• Adapt & make available quickly
• Continuous quality
Product Roadmap

21. Extreme Analytics at eBay
Advanced Analytic Infrastructures

22. Designing for the Unknown
>85% of eBay analytical workload is NEW & Unknown
The metrics you know are cheap
The metrics you don’t know are expensive – but high in
potential ROI
Exploration & Testing are core pillars of an analytics-
driven organization
22
22

23. Hypothesis
Ideas Assumptions
Algorithm
Pattern Guesses
Simulation
Behavioral
More Better Better
Tests Tests Decisions
Ownership & Confidence
Attribution
Machine
Advanced Learning
Experimentation: Build From Idea Up
23

27. Platform Metrics For Sample Queries

28. Business Centric Technology Centric
Executives & Management Executives & Management Executives & Management Analysts Executives & Management
PM & BU Managers * PM & BU Managers PM & BU Managers Scientists & Researchers * PM & BU Managers
Analysts Analysts * Analysts Engineers *
Scientists & Researchers Scientists & Researchers Engineers *
Engineers Engineers
Desktop Self- Rapid-fire BI & Statistical Purpose Built
Enterprise BI
service Exploration Modeling Applications
* Primary authoring group
BI Tools & Platforms

29. Self Service Analytics

30. 30

35. Thank You
Gayatri Patel
gayatripatel@ebay.com