Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Data-driven Innovation
Search
Matt Wood
October 10, 2012
Technology
1
400
Data-driven Innovation
Slides from my session at the #AWS Public Sector Summit, 2012.
Matt Wood
October 10, 2012
Tweet
Share
More Decks by Matt Wood
See All by Matt Wood
Field Notes from Expeditions in the Cloud
mza
2
400
A Platform for Big Data
mza
6
750
The Data Lifecycle
mza
5
510
Provision Throughput Like a Boss
mza
0
440
Impact of Cloud Computing: Life Sciences
mza
2
860
Latency's Worst Nightmare: Performance Tuning Tips and Tricks
mza
4
1.1k
Under the Covers of DynamoDB
mza
4
1.1k
From Analytics to Intelligence: Amazon Redshift
mza
9
1k
Scaling Science
mza
3
500
Other Decks in Technology
See All in Technology
標準技術と独自システムで作る「つらくない」SaaS アカウント管理 / Effortless SaaS Account Management with Standard Technologies & Custom Systems
yuyatakeyama
3
1.2k
フィンテック養成勉強会#54
finengine
0
180
データプラットフォーム技術におけるメダリオンアーキテクチャという考え方/DataPlatformWithMedallionArchitecture
smdmts
5
630
急成長を支える基盤作り〜地道な改善からコツコツと〜 #cre_meetup
stefafafan
0
120
生成AIでwebアプリケーションを作ってみた
tajimon
2
150
AIのAIによるAIのための出力評価と改善
chocoyama
2
550
米国国防総省のDevSecOpsライフサイクルをAWSのセキュリティサービスとOSSで実現
syoshie
2
1.1k
~宇宙最速~2025年AWS Summit レポート
satodesu
1
1.8k
Fabric + Databricks 2025.6 の最新情報ピックアップ
ryomaru0825
1
140
_第3回__AIxIoTビジネス共創ラボ紹介資料_20250617.pdf
iotcomjpadmin
0
150
25分で解説する「最小権限の原則」を実現するための AWS「ポリシー」大全 / 20250625-aws-summit-aws-policy
opelab
9
1.1k
登壇ネタの見つけ方 / How to find talk topics
pinkumohikan
5
440
Featured
See All Featured
The Straight Up "How To Draw Better" Workshop
denniskardys
234
140k
Cheating the UX When There Is Nothing More to Optimize - PixelPioneers
stephaniewalter
281
13k
RailsConf 2023
tenderlove
30
1.1k
Raft: Consensus for Rubyists
vanstee
140
7k
GraphQLの誤解/rethinking-graphql
sonatard
71
11k
Making Projects Easy
brettharned
116
6.3k
Imperfection Machines: The Place of Print at Facebook
scottboms
267
13k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
29
1.8k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
PRO
20
1.3k
The Myth of the Modular Monolith - Day 2 Keynote - Rails World 2024
eileencodes
26
2.9k
Rails Girls Zürich Keynote
gr2m
94
14k
Thoughts on Productivity
jonyablonski
69
4.7k
Transcript
Data-driven innovation
[email protected]
Dr. Matt Wood @mza
Hello
Hello
Data
DNA
Chromosome 11 : ACTN3 : rs1815739
Chromosome X : rs6625163
Chromosome 19 : FUT2 : rs601338
Chromosome 2 : rs10427255
TYPE II Chromosome 10 : rs7903146
+0.25 Chromosome 15 : rs2472297
I know this, because...
None
A T C G G T C C A G
G
A T C G G T C C A G
G A G C C A G G U C C Transcription
A T C G G T C C A G
G A G C C A G G U C C Translation Ser Glu Val Transcription
None
None
Chromosome 11 : ACTN3 : rs1815739
Chromosome X : rs6625163
Chromosome 19 : FUT2 : rs601338
Chromosome 2 : rs10427255
TYPE II Chromosome 10 : rs7903146
+0.25 Chromosome 15 : rs2472297
I know all that, because...
Human Genome Project
40 species ensembl.org
Compare
Change
Less
None
None
Compare
Transformative
None
Data generation costs are falling everywhere
Customer segmentation, financial modeling, system analysis, line of sight, business
intelligence.
Opportunity
Transformation
Innovation
Generation Collection & storage Analytics & computation Collaboration & sharing
Generation Collection & storage Analytics & computation Collaboration & sharing
lower cost, increased throughput
Generation Collection & storage Analytics & computation Collaboration & sharing
lower cost, increased throughput highly constrained
Barrier
Data generation challenge X
Analytics challenge
Accessibility challenge
Enter the AWS Cloud
Utility
Remove constraints
Data-driven innovation
Distributed
2
2 Software for distributed storage & analysis
2 Software for distributed storage & analysis Infrastructure for distributed
storage & analysis
Software Frameworks for data-intensive work loads. Distributed by design.
Infrastructure Platform for data-intensive work loads. Distributed by design.
Support the data timeline
Generation Collection & storage Analytics & computation Collaboration & sharing
highly constrained
Generation Collection & storage Analytics & computation Collaboration & sharing
Lower the barrier to entry
Agility
Responsive
Generation Collection & storage Analytics & computation Collaboration & sharing
Generation DynamoDB Analytics & computation Collaboration & sharing
Generation DynamoDB EC2, Elastic MapReduce Collaboration & sharing
Generation DynamoDB EC2, Elastic MapReduce S3, Public Datasets
Tools and techniques for working productively with data
Scale
Secure
2 Software for distributed storage & analysis Infrastructure for distributed
storage & analysis
Amazon EC2
Scale out systems Embarrassingly parallel Queue based distribution Small, medium
and high scale
High performance
High performance Compute performance
Cluster Compute Intel Xeon E5-2670 10 gigabit, non-blocking network 60.5
Gb Placement groupings
Cluster Compute Intel Xeon E5-2670 10 gigabit, non-blocking network 60.5
Gb Placement groupings +GPU
240 TFLOPS
High performance Compute performance IO performance
Unstructured
Variable
Amazon DynamoDB Predictable, consistent performance Unlimited storage Single digit millisecond
latencies No schema. Zero admin.
...and SSDs for all
hi1.4xlarge 2 x 1Tb SSD storage 10 gigabit networking HVM:
90k IOPS read, 9k to 75k write PV: 120k IOPS read, 10k to 85k write
Netflix “The hi1.4xlarge configuration is about half the system cost
for the same throughput.” http://techblog.netflix.com/2012/07/benchmarking-high-performance-io-with.html
Provisioned IOPS Provision required IO performance EBS optimized instances
Cost optimization
Reserved capacity
Reserved capacity On-demand
Reserved capacity On-demand
Spot instances
None
$0.2530 vs $2.40
2 Software for distributed storage & analysis Infrastructure for distributed
storage & analysis
map/reduce
Map. Reduce.
Write functions. Scale up.
Hadoop
Undi erentiated heavy lifting
Amazon Elastic MapReduce Managed Hadoop Clusters Easy to provision and
monitor Write two functions. Scale up. Choice of Hadoop flavors
Amazon Elastic MapReduce Integrates with S3 Analytics for DynamoDB Perfect
for Spot pricing
Input data S3
Elastic MapReduce Code Input data S3
Elastic MapReduce Code Name node Input data S3
Elastic MapReduce Code Name node Input data S3 Elastic cluster
Elastic MapReduce Code Name node Input data S3 Elastic cluster
HDFS
Elastic MapReduce Code Name node Input data S3 Elastic cluster
HDFS Queries + BI Via JDBC, Pig, Hive
Elastic MapReduce Code Name node Output S3 + SimpleDB Input
data S3 Elastic cluster HDFS Queries + BI Via JDBC, Pig, Hive
Output S3 + SimpleDB Input data S3
CDC Centers for Disease Control and Prevention
“BioSense 2.0 protects the health of the American people by
providing timely insight into the health of communities, regions, and the nation by o ering a variety of features to improve data collection, standardization, storage, analysis, and collaboration”
Health data Collection & storage Analytics & computation Collaboration &
sharing
Health data Collection & storage Analytics & computation Collaboration &
sharing highly constrained
HIPAA, HITECH, FISMA Moderate
GovCloud
Beyond a definition of Big Data
Chromosome 11 : ACTN3 : rs1815739
Chromosome X : rs6625163
Chromosome 19 : FUT2 : rs601338
Chromosome 2 : rs10427255
TYPE II Chromosome 10 : rs7903146
+0.25 Chromosome 15 : rs2472297
Thank you aws.amazon.com @mza
[email protected]