An introduction to Amazon Redshift for business intelligence applications. Presented at Microstrategy World 2013.

1. introducing
AMAZON REDSHIFT
for
BUSINESS INTELLIGENCE
a presentation at
MICROSTRATEGY WORLD 2013
by
DR. MATT WOOD

2. Hello.

3. Thank you.

4. I
Data, data
everywhere

5. I II
Data, data Collection &
everywhere storage

6. I II III
Data, data Collection & Data
everywhere storage security

7. I II III IV
Data, data Collection & Data Data
everywhere storage security movement

8. I II 0. III IV
Amazon web
Data, data Collectionervices Data
S & Data
everywhere storage security movement

9. Building blocks.

10. Compute, storage & databases.

11. Retail Merchant Web
services services

12. Blinding flash of the obvious.

13. Available.

14. Low cost.

15. Flexible.

16. Every day, AWS adds enough server
capacity to power amazon.com in 2003,
when it was a $5B enterprise

17. I
Data, data everywhere

18. Data for competitive advantage.

19. Customer segmentation,
financial modeling,
system analysis,
line of sight,
business intelligence...

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

21. Cost of data generation is falling.

22. devices
Kindle Fire HD, Kindle Fire, Kindle
Paperwhite and Kindle hold the top four
spots on the Amazon world wide best seller
chart since launch.

23. Amazon Appstore selection tripled in 2012.
apps and games

24. Amazon customers purchased more than
one toy per second on mobile devices.
commerce

25. most gifted
kindle book

26. lower cost,
increased throughput
Generation
Collection & storage
Analytics & computation
Collaboration & sharing

27. Generation
highly
constrained
Collection & storage
Analytics & computation
Collaboration & sharing

28. Gap.

29. Data volume
The Data Analysis Gap
Generated data
Available for analysis
1990 2000 2010 2020
Enterprise Data Data in Warehouse
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

30. Enter AWS.

31. Utility.

32. Remove constraints.

33. Generation
highly
constrained
Collection & storage
Analytics & computation
Collaboration & sharing

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

35. Full value.

36. Close the gap.

37. Reduced time to market.

38. Identify and meet new business
opportunities.

39. Lower costs.

40. II
Collection & Storage

41. One schema to rule them all.

42. One schema to rule them all.

43. Lots of data.
Lots of users.
Lots of uses.
Lots of locations.

44. Cost.

45. Multipliers.

46. Object storage.

47. 99.999999999%
durability

48. Relational databases.

49. NoSQL data stores.

50. HDFS based stores.

51. Undifferentiated heavy lifting.

52. Lower costs. Ease of use.

53. only pay for what you use
no capital investment
Lower costs. Ease of use.
pay as you go
no subscriptions

54. programmable integrate with
existing tools
Lower costs. Ease of use.
easy to
zero admin
configure

55. Data warehousing.

56. Expensive. Complicated.

57. Enterprises average between
3 and 4 DBAs per data
warehouse.
Source: Gartner. Critical factors in calculating the data warehouse TCO, July 2009

58. Source: Oracle technology global price list 11/1/2012

59. Expensive. Complicated.

60. Unobtainable.

61. Amazon Redshift.

62. Fast. Powerful. Petabyte scale.

63. Managed service.

64. Automated deployment
& configuration.

65. SQL access and BI tool integration.

66. Parallel execution.

67. Leader
Node

68. Leader
Node
Compute Compute Compute
Node Node Node

69. Leader
Node
Compute Compute Compute
Node Node Node

70. 10gigE full bisection network.

71. Leader
Node
Compute Compute Compute
Node Node Node

72. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

73. Certified for use with
Microstrategy.

74. Data compression.

75. Automated backup to S3.

76. Data encrypted in transit
& at rest.

77. Streaming recovery.

78. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

79. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

80. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

81. Elastic.

82. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

83. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute Compute Compute
Node Node Node Node Node

84. Common BI Tools
JDBC/ODBC
Leader
Node
Compute Compute Compute
Node Node Node

85. Data warehouse node types.

86. High Storage Extra Large (XL)
15GB RAM
2TB local attached storage
3 drives
2 virtual cores

87. High Storage Extra Large (XL) 8 High Storage Extra Large (8XL)
15GB RAM 120GB RAM
2TB local attached storage 16TB local attached storage
3 drives 24 drives
2 virtual cores 16 virtual cores

88. Pay as you go.

89. Hourly Prices
2 TB nodes 16 TB nodes
On-demand $0.850 $6.80
1 Year
$0.50 $4.00
Reservation
3 Year
$0.228 $1.824
Reservation

90. Hourly Prices
2 TB nodes 16 TB nodes
On-demand $0.850 $6.80
1 Year
$0.50 $4.00
Reservation
3 Year
$0.228 $1.824
Reservation

91. $999 per TB

92. Don’t pay for the leader node.

93. No additional storage charge for
backups of active clusters.

94. VPC ready.

95. Low cost. Easy to use.

96. Focus on analysis.

97. Private beta today.

98. Available early this year.

99. aws.amazon.com/redshift

100. 2 billion row dataset. 6 representative queries.

101. Amazon Redshift: 2 instance cluster
Compared to 32 nodes. 128 CPUs. 4.2 TB RAM. 1.6 PB storage. 2 billion row data set.
12x to 150x faster

102. 29 minutes 58 seconds
down to
12 seconds

103. III
Data security.

104. Security is our number one priority.

105. Shared responsibility.

107. Choose your region.

108. Availability zones.

109. SOC 2 ISAE 3402 FISMA Moderate PCI DSS FIPS 140-2
ISO 27001 ITAR HIPAA MPAA

111. “You basically turn yourself into a
polymorphic surface to which the attack guy
has a much tougher time getting at. That,
ultimately, is the real key advantage to drive
security and make things much better for us
across the board.”
Gus Hunt, CTO
Central Intelligence Agency

112. Virtual Private Cloud.

113. Network isolated environment.

114. Public and private subnets.

115. Redshift, relational databases, Hadoop
can run inside the VPC.

116. Extend your VPN.

117. Identity and access federation.

118. Identity and access management.

119. IV
Data movement.

120. “How do I get my data
into the cloud?”

121. Generated and stored
in the AWS cloud.

122. Inbound transfer if free.

123. Multipart upload.

124. Aspera, IRODS.

125. Physical media.

126. AWS Direct Connect.

127. 1Gbps or 10Gbps

128. Built in AZ replication.

129. Regional replication.

130. “How do I integrate my data?”

131. Amazon S3 Amazon RDS
Amazon DynamoDB Amazon Redshift
HDFS (Amazon EMR) On Premise

132. AWS Data Pipeline

133. Data-intensive orchestration
& automation.

134. Reliable, scheduled
data movement and analytics.

135. aws.amazon.com/datapipeline

136. aws.amazon.com

137. I
Data, data
everywhere

138. I II
Data, data Collection &
everywhere storage

139. I II III
Data, data Collection & Data
everywhere storage security

140. I II III IV
Data, data Collection & Data Data
everywhere storage security movement

141. Thank you.

142. get in touch
introducing
MATTHEW@AMAZON.COM
AMAZON REDSHIFT or
@MZA
for
BUSINESS INTELLIGENCE
AWS.AMAZON.COM