Learn more about the tools, techniques and technologies for working productively with data at any scale. This session will introduce the family of data analytics tools on AWS which you can use to collect, compute and collaborate around data, from gigabytes to petabytes. We'll discuss Amazon Elastic MapReduce, Hadoop, structured and unstructured data, and the EC2 instance types which enable high performance analytics.

1. Big Data Analytics
Constantin Gonzalez
Solutions Architect, Amazon Web Services
Berlin

2. 1. Introducing Big Data
2. From data to actionable information
3. Analytics and Cloud Computing
Overview

3. Introducing Big Data
1

4. Generation
Collection & storage
Analytics & computation
Collaboration & sharing

5. The cost of data generation
is falling

6. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
Lower cost,
higher throughput

7. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
Lower cost,
higher throughput
Highly
constrained

8. Generated data
Available for analysis
Data volume
Gartner: User Survey Analysis: Key Trends Shaping the Future of Data Center Infrastructure Through 2011
IDC: Worldwide Business Analytics Software 2012–2016 Forecast and 2011 Vendor Shares

9. Elastic and highly scalable
No upfront capital expense
Only pay for what you use
+
+
Available on-demand
+
=
Remove
constraints

10. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
Lower cost,
higher throughput
Highly
constrained

11. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
Accelerated

12. Technologies and techniques for
working productively with data,
at any scale.
Big Data

13. From data to
actionable information
2

14. “Who buys video games?”

15. 3.5 billion records
13 TB of click stream logs
71 million unique cookies
Per day:

18. 500% return on ad spend
From 2 months procurement time
to a few minutes
Results:

19. “Who is using our service?”

20. Identified early mobile usage
Invested heavily in mobile development
Finding signal in the noise of logs

21. 9,432,061 unique mobile devices
used the Yelp mobile app.
4 million+ calls. 5 million+ directions.
In January 2013

22. Speaking of mobile devices
and social networks…

23. You Are What You Tweet: Analyzing Twitter for Public Health. M. J. Paul and M. Dredze, 2011
Tweets about the Flu

24. Analytics and
Cloud Computing
3

25. Generation
Collection & storage
Analytics & computation
Collaboration & sharing

26. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
S3, Glacier,
Storage Gateway,
DynamoDB,
Redshift, RDS,
HBase

27. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
EC2 &
Elastic MapReduce

28. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
EC2, S3, RDS
CloudFormation,
Elastic MapReduce,
DynamoDB, Redshift

29. Generation
Collection & storage
Analytics & computation
Collaboration & sharing
EC2 &
Elastic MapReduce
S3, Glacier,
Storage Gateway,
DynamoDB,
Redshift, RDS,
HBase
AWS Data Pipeline
EC2, S3, RDS
CloudFormation,
Elastic MapReduce,
DynamoDB, Redshift

30. Elastic MapReduce

31. How does it work?
EMR
EMR ClusterS3
1. Put the data
into S3 (or
HDFS)
1. Put the data
into S3 (or
HDFS)
3. Get the
results
3. Get the
results
2. Launch your cluster.
Choose:
•Hadoop distribution
•How many nodes
•Node type (hi-CPU, hi-
memory, etc.)
•Hadoop apps (Hive,
Pig, HBase)
2. Launch your cluster.
Choose:
•Hadoop distribution
•How many nodes
•Node type (hi-CPU, hi-
memory, etc.)
•Hadoop apps (Hive,
Pig, HBase)

32. EMR
EMR Cluster
How does it work?
S3
You can
easily resize
the cluster
You can
easily resize
the cluster

33. EMR
EMR Cluster
How does it work?
S3
Use Spot
nodes to
save time
and money
Use Spot
nodes to
save time
and money

34. EMR
EMR Cluster
How does it work?
S3
Launch parallel clusters
against the same data
source (tune for the
workload)
Launch parallel clusters
against the same data
source (tune for the
workload)

35. How does it work?
EMR ClusterS3
When the work is complete,
you can terminate the
cluster (and stop paying)
When the work is complete,
you can terminate the
cluster (and stop paying)

36. EMR Cluster
How does it work?
You can store
everything in HDFS
(local disk)
You can store
everything in HDFS
(local disk)
High Storage nodes
= 48 TB/node
High Storage nodes
= 48 TB/node

37. EMR Cluster
How does it work?
Launch in a Virtual
Private Cloud for
extra security
Launch in a Virtual
Private Cloud for
extra security

38. Thousands of Customers, 5+ Million Clusters

39. Give it a try:
aws.amazon.com/elasticmapreduce
Cost to run a 100-node EMR cluster:
EUR 5.75/hour
($7.50/h)

40. Photos: renee_mcgurk https://www.flickr.com/photos/51018933@N08/5355664961/in/photostream/
Calgary Reviews https://www.flickr.com/photos/calgaryreviews/6328302248/in/photostream/
+

41. AWS Data Pipeline
Data-intensive orchestration and automation
Reliable and scheduled
Easy to use, drag and drop
Execution and retry logic
Map data dependencies
Create and manage temporary compute
resources

42. Anatomy of a pipeline

43. Additional checks and notifications

44. Arbitrarily complex pipelines

45. Thanks.
glez@amazon.de
@zalez
Learn More: aws.amazon.com/big-
data

46. Alan Priestley
Strategic Marketing Director
Intel Corporation

47. Analysis of Data Can Transform Society
Create new business
models and improve
organizational
processes.
Enhance scientific
understanding, drive
innovation, and
accelerate medical
cures.
Increase public safety
and improve
energy efficiency with
smart grids.

48. Democratizing Analytics gets Value out of Big Data
Unlock Value in
Silicon
Support Open
Platforms
Deliver Software Value

49. Intel at the Intersection of Big Data
Enabling exascale
computing on
massive data sets
Helping
enterprises build
open
interoperable
clouds
Contributing code
and fostering
ecosystem
HPC Cloud Open
Source

50. Intel at the Heart of the Cloud
Server
Storage
Network

51. Scale-Out Platform Optimizations for Big Data
Cost-effective performance
•Intel® Advanced Vector Extension
Technology
•Intel® Turbo Boost Technology 2.0
•Intel® Advanced Encryption Standard
New Instructions Technology

52. 52
Intel® Advanced Vector Extensions Technology
• Newest in a long line of
processor instruction
innovations
• Increases floating
point operations per
clock up to 2X1
performance
1 : Performance comparison using Linpack benchmark. See backup for configuration details.
For more legal information on performance forecasts go to http://www.intel.com/performance
Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are
measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other
information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products.

53. Intel® Turbo Boost Technology 2.0
More
Performance
Higher turbo speeds
maximize performance for
single and
multi-threaded applications

54. Intel® Advanced Encryption
Standard New Instructions
•Processor assistance for
performing AES encryption
7 new instructions
•Makes enabled encryption
software faster and stronger

55. Power of the Platform built by Intel
Richer
user
experiences
4HRS
50%
Reduction
10MIN
80%
Reduction 50%
Reduction 40%
Reduction
TeraSort
for 1TB
sort
Intel®
Xeon®
Process
or E5
2600
Solid-State
Drive 10G
Ethernet Intel®
Apache
Hadoop
Previous
Intel®
Xeon®
Process
or

56. Cloud
Intelligent
Systems
Clients
Virtuous Cycle of Data-Driven Experience

57. Get 600 Hours of free supercomputing time!
www.powerof60.com

58. Thank you!