A Empresa na Era da Informação Extrema

José Papo

Amazon Evangelist

@josepapo

josepapo@amazon.com @josepapo

“Algorithms have already written symphonies as moving as those

composed by Beethoven,

picked through legalese with the

deftness of a senior law partner, diagnosed patients

with more accuracy than a

doctor, written news articles

like a seasoned reporter,

and driven vehicles on urban highways with better control

than a human driver.”

A Nuvem é o alavancador das novas tendências tecnológicas

○○○○

We are sincerely eager to

hear your feedback on this

presentation and on re:Invent.

Please fill out an evaluation

form when you have a

chance.

We are constantly producing more data

We are sincerely eager to

hear your feedback on this

presentation and on re:Invent.

Please fill out an evaluation

form when you have a

chance.

From all types of industries

“Todos os mercados estão sendo transformados pela nova onda digital”

http://www.amazon.com.br/Digital-Disruption-Unleashing-Innovation-ebook/dp/B009L7QD1S/

3Vs

27 TB per day Large Hadron Collider – CERN

The Role of Data

is Changing

We are sincerely eager to

hear your feedback on this

presentation and on re:Invent.

Please fill out an evaluation

form when you have a

chance.

Until now, Questions you ask drove Data model

New model is collect as much data as possible – “Data-First Philosophy”

We are sincerely eager to

hear your feedback on this

presentation and on re:Invent.

Please fill out an evaluation

form when you have a

chance.

Data is the new raw material for

any business on par with

capital, people, labor

Data is the new raw material for business on par with capital

& labor

Data

Actionable Information

Generated

data

Available for analysis

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

Data Strategist

lunch hours last year?

select productId, count(*) from page_hits where hour in (12,13) group by productId order by count(*) desc

cat *-(12|13) | cut –f3 | sort | uniq -c > out

Hit <enter>?

1PB = 10^15 (1,000,000,000,000,000) bytes

1 PB = 231 days at 50MB/s

Solution: Massively Parallel Processing

○○○○

HDFS Reliable storage

MapReduce Data analysis

Very large log

(e.g TBs)

Very large log

(e.g TBs)

Lots of actions

by John

Very large log

(e.g TBs) Split into

small

pieces

Lots of actions

by John

Very large log

(e.g TBs)

Process in a

hadoop cluster

Split into

small

pieces

Lots of actions

by John

Very large log

(e.g TBs)

John’s history

Process in a

hadoop cluster

Aggregate

the results Split into

small

pieces

Lots of actions

by John

map Input

file reduce Output

file

Worker node

map Input

file reduce Output

file

map Input

file reduce Output

file

map Input

file reduce Output

file

Worker node

Worker node

Worker node

#3 ♥

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We are sincerely eager to

hear your feedback on this

presentation and on re:Invent.

Please fill out an evaluation

form when you have a

chance.

Elastic On Demand

Pay as you go

Focus on

YOUR

business

November

Provisioned capacity

November

76%

24%

Provisioned capacity

November

November

0

1.000.000

2.000.000

3.000.000

4.000.000

5.000.000

6.000.000

“What kind of movies do people like ?”

More than 25 Million Streaming Members

50 Billion Events Per Day

30 Million plays every day

2 billion hours of video in 3

months

4 million ratings per day

3 million searches

Device location , time ,

day, week etc.

Social data

10 TB of streaming data per day

~1 PB of data stored in Amazon S3

S3

Wide range of processing languages used

EMR

Prod Cluster (EMR)S3

Data consumed in multiple ways

S3

EMR

Prod Cluster (EMR)

Recommendation

Engine

Ad-hoc

Analysis Personalization

EMR

S3EMR

EMR

Prod Cluster (EMR)

Query Cluster (EMR)

EMR

EMR

Foursquare…

33 million users 1.3 million businesses

…generates a lot of Data 3.5 billion check-ins 15M+ venues, Terabytes of log data

Uses EMR for Evaluation of new features

Machine learning

Exploratory analysis

Daily customer usage reporting

Long-term trend analysis

Source: IDC Whitepaper, sponsored by Amazon, “The Business Value of Amazon Web Services Accelerates Over Time.” July 2012

70% lower 5 year TCO per app

AWS

On-premises

$3.01M

$0.90M

50% reduction in analytics costs

0

0,1

0,2

0,3

0,4

0,5

0,6

Female Male

Gender

0 10 20 30 40 50 60 70 80

Age

Gorilla Coffee

Gray's Papaya

Amorino

Thursday Friday Saturday Sunday

Log files

250 EMR clusters spun up

and down every week

Challenge: Large amounts of computing resources needed for short periods of time; significant data storage costs

Solution: Clusters of 100s of nodes on EMR running 4-5 hours at a time Leverages 1000 genomes Public Data Set on AWS —free access to ~200 TB of genomes for over 2,600 people from 26 populations around the world.

Challenge: Volatile weather is deadly to crops like grapes

Solution: Built a predictive model based on freely available data— 60 years of crop data, 14 TBs of soil data, and 1M government Doppler radar points 50 EMR clusters process new data as it comes into S3 each day, continuously updating the model.

OBRIGADO!

http://awshub.com.br

slideshare.net/AmazonWebServicesLATAM

José Papo

Amazon Evangelist

@josepapo

josepapo@amazon.com