Transforming ecommerce Big Data into Big Fast Data

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1 Transforming ecommerce Big Data into Big Fast Data Gagan Mehra, Chief Evangelist, Terracotta, Inc. October 22 nd Terracotta Inc Terracotta Inc. 1

2 WHAT IS BIG DATA? 2013 Terracotta Inc Terracotta Inc. 2

3 What is Big Data? 2013 Terracotta Inc. 3

4 DATA is Expanding Exponentially A confluence of interconnected forces is generating and utilizing VAST AMOUNTS OF DATA 2013 Terracotta Inc. 4

5 Big Data Holds Big Value for Enterprises Making Better Informed Decisions Access Strategies, Recommendations BIG DATA Opportunities Discovering Hidden Insights -- Manage Forensics, Patterns, Trends Automating Business Processes -- Analyze Complex Events, Translation Generate Revenue Act Know What Your Customers Want and When 2013 Terracotta Inc. 5

6 Enterprise Big Data Challenges 2013 Terracotta Inc. 6

7 The Road Ahead Big Data is pervasive But if you can t extract value, Big Data is just a problem to be managed Value relies on Big Data being fast 2013 Terracotta Inc. 7

8 BIG DATA & ecommerce 2013 Terracotta Inc Terracotta Inc. 8

9 ecommerce has been HOT for a long time...and it is still very hot 2013 Terracotta Inc. 9

10 E-Commerce Challenges Can Your Platform Keep Pace? Rapid Revenue Growth 45% 64% increase in online sales by 2016 Shifts in Shopping Behavior smartphone owners shop online Higher Consumer Expectations 72% shoppers abandon slow sites 2013 Terracotta Inc. 10

11 Big Data Use Cases ecommerce Customer Experience Management Personalized or Segmented Supply Chain More features with faster response times Unlimited scalability Dynamic Pricing Fraud Management 2013 Terracotta Inc. 11

12 Many enterprises use caching, NoSQL, etc. to incrementally improve performance An ecommerce system consisting of several applications might use caching, and a combination of relational & NoSQL databases is unable to support all Big Data use cases 2013 Terracotta Inc. 12

13 Evolution of the ecommerce Architecture An architecture designed for real-time Big Data would make it possible for the enterprise to: Intelligently react to hundreds of thousands of events per second Easily handle incremental load without sacrificing performance Rapidly deploy new functionality and associated data sets without worrying about scalability or performance constraints Focus on business growth versus worrying about data 2013 Terracotta Inc. 13

14 A large in-memory store, however, can transform all big data into big FAST data After an in-memory data management solution is introduced in the environment, all applications are able to leverage it, improving overall performance, even under load, and reducing the volume of data that needs to be maintained in databases Terracotta Inc. 14

15 IN-MEMORY TRANSFORMS BIG DATA 2013 Terracotta Inc Terracotta Inc. 15

16 In-Memory in E-Commerce All-Round Better Performance E-commerce application Speed Slash response times with 100x faster data access Scale Keep pace with rapid traffic and transaction growth Stability Decouple from databases to protect performance Cost Efficiency Cut infrastructure and operational expenses Revenue Growth Boost sales with customer satisfaction 2013 Terracotta Inc. 16

17 BigMemory in E-Commerce Proven Track Record BigMemory powers popular global e-commerce sites with: 1,000s of products 100,000s of registered users Millions of daily visitors Billions in annual revenue E-Commerce Use Cases Website performance Web server consolidation Real-time personalization Real-time fraud detection 2013 Terracotta Inc. 17

18 SUCCESS STORY: Getting Global E-commerce on Pace With BigMemory FORTUNE 150 ATHLETIC BRAND What they wanted Continued e-commerce growth for nearly 7,500 products and $340 million in sales Before BigMemory Product catalog and shopping cart data pulled from multiple disk-bound databases Huge spikes in customer traffic (Cyber Monday, Black Friday) jeopardized stability SCALE 2013 Terracotta Inc. 18

19 SUCCESS STORY: Getting Global E-commerce on Pace With BigMemory FORTUNE 150 ATHLETIC BRAND After BigMemory: 90% of product requests served instantly by BigMemory Backend services load slashed by 40% Average page load time reduced by 16% Search time reduced by 30% Improved online shopping experience without big investment in new servers SCALE 2013 Terracotta Inc. 19

20 SUCCESS STORY: Radically Improving Profitability With Better, Faster Fraud Detection FORTUNE 500 ONLINE PAYMENTS PROCESSOR What they wanted Dramatically boost bottom-line profit through faster, more accurate fraud detection Before BigMemory Lost 30 cents on every $100 to fraud With Oracle Exadata, failed to meet 800 ms SLA around 10% of time Limited to 50 rules, even though each new rule generated $12 million in profit SPEED 2013 Terracotta Inc. 20

21 SUCCESS STORY: Radically Improving Profitability With Better, Faster Fraud Detection FORTUNE 500 ONLINE PAYMENTS PROCESSOR After BigMemory: Savings of tens of millions of dollars in reduced costs from missed SLAs and fraudulent charges Meeting stricter 650-millisecond SLA 99% of time Savings of $1 million annually in reduced database licenses Plans to expand from 4TB to 150TB for new applications and to achieve 250 millisecond SLA SPEED 2013 Terracotta Inc. 21

22 SUCCESS STORY: Building a Global Media Distribution Platform With BigMemory GLOBAL ONLINE MOVIE STREAMING SERVICE What they wanted Build a digital media streaming service (Ultraviolet) to compete with the likes of Netflix and Amazon Before BigMemory Strict requirements for streaming movies to mobile devices worldwide Global rollout aspirations VMware GemFire rejected in proof-of-concept for scalability, WAN replication SCALE 2013 Terracotta Inc. 22

23 SUCCESS STORY: Building a Global Media Distribution Platform With BigMemory GLOBAL ONLINE MOVIE STREAMING SERVICE After BigMemory: 6.5 million customers using the service to stream and watch movies on their TVs, tablets, smartphones and other devices Company rolling out service worldwide with new countries every quarter 80GB in-memory store in BigMemory SCALE 2013 Terracotta Inc. 23

24 SUCCESS STORY: Delivering New Revenue by Presenting Relevant Offers in Real Time FORTUNE 100 SHIPPING COMPANY What they wanted Boost revenue with relevant offers and tools while customers are ordering, tracking packages Before BigMemory 32 million tracking requests = opportunities to present offers Performance 4x slower than required by SLA because data resided in multiple disk-bound databases Oracle Coherence rejected for complexity and slowness SCALE 2013 Terracotta Inc. 24

25 SUCCESS STORY: Delivering New Revenue by Presenting Relevant Offers in Real Time FORTUNE 100 SHIPPING COMPANY After BigMemory: Increased revenue by presenting relevant offers 85% faster in just 120 milliseconds Exceeding performance SLAs Adopted BigMemory as company-wide standard for in-memory data management SCALE 2013 Terracotta Inc. 25

26 Questions? 2013 Terracotta Inc Terracotta Inc. 26

27 575 Florida Street, Suite 100 San Francisco, CA TERRA or Terracotta Inc.

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