"Driving the On-Demand Economy with Predictive Analytics" by CEO Eric Frenkiel at the Orange County Real-Time Roadshow on March 17, 2017.

1. Driving the On-Demand Economy with
Predictive Analytics
Eric Frenkiel, CEO

2. DATA CORPUS

3. DATA CORPUS
ACTORS
Applications

4. DATA CORPUS
ACTORS
Applications
OPERATORS
Data Science

5. DATA CORPUS
ACTORS
Applications
OPERATORS
Data Science
ACTORS + OPERATORS
Real-Time
Machine Learning

6. ACTORS
Applications
OPERATORS
Data Science
ACTORS + OPERATORS
Real-Time
Machine Learning
FEEDBACK LOOP

7. PRECISION

8. TUNING

9. DISCOVERY

10. Today’s Talk
▪ The On-Demand Economy
▪ Introduction to MemSQL
▪ Customer Use Cases
▪ Demo

11. The on-demand
economy is here.

12. Consumers
are now
conditioned
to instant
services

14. Data
scientists
need to carry
the world
forward

15. Too often
stuck with
batch
processing
and slow ETL

16. Slow Loading
Slow Queries
No Concurrency
On-going Data Processing Barriers

17. A shift is
underway…
the move to
real time

18. The Real-Time Data Warehouse
for the Frontline of Your Business

19. Real-Time Scalable Multi-Cloud
• Fast Ingest, Low Latency
Queries, High Concurrency
• Operational and Ad-Hoc
Analytics
• Powerful applications
• Petabyte scale
• Elastic
• Commodity hardware
• Low TCO
• Cloud Managed Service
• On-premises
• Multi-cloud deployments
• Enterprise-grade Security
A Modern Data Warehouse for the Enterprise Frontlines

20. Real-Time Data
Messaging and
Transforms
Historical Data
Bare Metal, Virtual Machines, Containers On-Premises, Cloud, As a Service
Business
Intelligence
Dashboards
Real-Time
Application
AnalyticsReal-Time Data
Warehouse
Live Data
Memory Optimized
Tables
Historical Data
Disk Optimized
Tables
Streaming Ingest
Real-Time
Data Pipelines

21. How Did We Get Here

23. Trying to build
scale-out for
a traditional
product

25. Scale-out

26. ▪ Every piece of technology is scalable
▪ Analyzing data from hundreds of thousands of
machines
▪ Delivering immense value in real-time
• Real-time code deployment
• Detecting anomalies
• A/B testing results
▪ Fundamentally making the business faster by providing
data at your fingertips
An Insider’s View at Facebook

27. Imagine scaling a
database on industry
standard hardware.
Need 2x the
performance?
Add 2x the nodes.

28. MemSQL Confidential28
Product or Services Scores
for Operational Data
Warehouse
Critical Capabilities for Data
Warehouse and Data
Management Solutions for
Analytics
Gartner, July 2016

29. A few thoughts
on the Cloud

30. Aim for Dual-Cloud Equilibrium
7
Core Business
Data

31. Gartner Hybrid DBMS Cloud Scenarios
31
Dev Test
Disaster
recovery
Architecture Spanning Use Case Specific Multicloud
Prod
Source: Gartner (April 2016)

32.  Fully managed database service
for real-time analytics
 Fast data ingest from Amazon S3,
Kinesis, or Apache Kafka
 Lift and Shift to the Cloud
REAL-TIME ANALYTICS
AT YOUR SERVICE
7

33. A Comprehensive Hybrid Cloud Approach
▪On-Premises deployments
•Any hardware, NUMA optimizations, vectorized processing
•Any Linux, VMs, Containers
•Robust security including Role-based Access Control (RBAC)
•Perfect for retiring legacy appliances
▪Any Cloud
•Any cloud service IaaS
•Simple `replicate database` command

34. Strategic Approach to Global Analytics
▪ Develop a center of excellence for real-time
infrastructure
• Include both real-time AND historical data
▪ Identify complements and replacements for traditional
technologies
• Data warehouse appliances, rigid systems
▪ Choose a straightforward path
• Faster historical insights, real-time data, predictive analytics

35. Customer Use Cases

36. Real-time analytics transformed profitability analysis of customer logistics
from weekly to daily, and reduced latency from days to minutes
+
36

37. 37
BUSINESS BENEFITS
▪ New increased profitability customer logistics analysis
from weekly to daily
▪ Reduce Latency from days to minutes
TECHNICAL BENEFITS
▪ Reduced 22 hour ETL to minutes
▪ Increased query response time by 80x

38. THE KELLOGG’S REAL-TIME ARCHITECTURE
38
22 hours to minutes
80x faster

39. Reducing delay in “freshness of data” from two hours to 10 minutes
+

40. BUSINESS BENEFITS
▪ Reach over 1.5 billion users across 100s of thousands of mobile apps
▪ Real-time optimization of advertising campaigns with improved post-install
engagements
▪ Net new personalized campaign performance reports for greater visibility
TECHNICAL BENEFITS
▪ 10x faster data refresh, from hours to minutes
▪ Ad-hoc queries on raw log-level data in seconds
▪ Real-time deduplication
▪ 1 TB/day ingest

41. THE MANAGE REAL-TIME ARCHITECTURE
41
REAL-TIME
ANALYTICSReal-Time
inputs
http://www.enterprisetech.com/2016/12/09/managing-30b-bid-requests/

42. DellEMC Adopts MemSQL for Customer Acquisition
Lifecycle Management
+

43. 43
BUSINESS BENEFITS
• Deliver real-time customer updates to DellEMC Sales Department
• Scale customer analytics to increase sales productivity
• Execute joins across multiple distributed data set
• Drive real-time personalization for operational efficiency
TECHNICAL BENEFITS
• Data loading
• Concurrency
• Sub-second response
• Distributed joins

44. DELLEMC REAL-TIME ARCHITECTURE
REAL-TIME
ANALYTICS

45. SECURE DATA LAKE ARCHITECTURE
45 http://itblog.emc.com/2016/05/03/simplifying-lives-emc-myservice360/

46. 46
The global leader in Content Delivery Network services, has deployed MemSQL
to enhance billing speed and efficiency for thousands of customers around the world
+

47. 47
BUSINESS BENEFITS
▪ Analyze Historical Against Live Data
▪ 30% Increased Forecast Accuracy
▪ Tighter Financial Reporting to Street
TECHNICAL BENEFITS
▪ Analyze Millions of rows / second
▪ Massive Concurrency
▪ 8 Million UPSERTS per second
▪ Process 1PB Data Per Day

48. THE AKAMAI REAL-TIME ARCHITECTURE
48
REAL-TIME
ANALYTICSCustomer
traffic
statistics

49. Demo

50. Front OfficeBack Office

51. Real-TimeBatch

52. Predictive InsightHindsight

53. Q&A

54. www.memsql.com
Thank You