Pass4sure 70-534 Dumps

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Architecting Microsoft Azure Solutions
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• Big Data Briefing

• How to implement Big Data on Windows Azure

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Big Data running cheaply and efficiently on
Windows Azure to discover business value from
data you already hold about your business.
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Introduction
Agenda Windows Azure Intro HDInsight
Intro Architecture BI and Visualisations Case
Studies
Who Andy Cross, Director of Microsoft Partner
Elastacloud, Windows Azure MVP, Big Data
specialist and international speaker.
Time until next coffee 5500
30 minutes
30 minutes
30 minutes
15 minutes
15 minutes
Find out more at http//www.Microsoft.com
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Windows Azure

• Introduction to

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Todays Transformation Cloud
Economics ? Agility ? Focus
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IT Continuum
Evolution toward highly-virtual and beyond to
cloud
PaaS
SaaS
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Microsoft On The Internet
1.0
400m active accounts
One of 3rd worlds largest private networks
More than 3 billion queries per month
1.0
1 billion authentications per day
750 million unique visitors at any given time
Global Foundation Services
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Windows Azure
1 million SQLs More Transactions in LIVE than VISA
By the Numbers
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The Microsoft Cloud

• Globally Distributed Data Centers

Quincy, WA
Chicago, IL
San Antonio, TX
Dublin, Ireland
Generation 4 DCs
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Inside a Microsoft Data Center
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Cloud Computing Patterns
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Applicationbuilding blocks
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• Big Data Technologies

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HDInsight Summary

• GA, recent preview of Hadoop 2
• Managed Hadoop on Windows Azure
• Familiar tools such as Hive, Pig, Oozie
• Additional BoB Microsoft ecosystem tooling with
  .net SDK
• Powershell and .net for provision
• Execution with .net and powershell for Hive
• Paired with Hortonworks HDP for on-premises
  Hadoop compatible with all major Hadoop
  implementations
• Combined with Excel and traditional Microsoft BI
  stack for compelling solutions

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Position in Cloud
PaaS
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Centralised Resources
State a Windows Azure SQL DB stores metadata to
allow identical clusters to be spawned
Data all your data resides on Windows Azure
Blob Storage resilient, secure and cost effective
Logs machine state and cluster uptime is stored
in Windows Azure Table Storage
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• Provision hundreds of machines against your data
  gain understanding rapidly

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Speed to understanding
500 servers. 20 minutes.
40,000,000,000 data points
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Drive Investment
Buy the Look
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Exploring Sentiment, Social and Metadata Graphs
Person
Product
Product
Alike
Owns
Owns
Person
Alike?
Social Media
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Microsoft Big Data Solution
FAMILIAR END USER TOOLS
BI PLATFORM
SSAS
SSRS
Microsoft EDW
Connectors
Hadoop On Windows Server
Hadoop On Windows Azure
UNSTRUCTURED STRUCTURED DATA
APPs
LOB
CRM
ERP
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Microsoft Offerings
Hive ODBC Driver Hive Add-in for
Excel Integration with Microsoft PowerPivot
Hadoop based distribution for Windows Server
Azure Strategic Partnership with Hortonworks
JavaScript framework for Hadoop RTM of Hadoop
connectors for SQL Server and PDW
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Hadoop on WindowsInsights to all users by
activating new types of data
Differentiation
Contributions proposed back to community
distribution
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Microsoft Big Data Roadmap
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• Microsofts value adds

• Why Elastacloud recommend Microsofts platform

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Skill reuse
Express elegant solutions in C Familiar Unit
Testing patterns Concise programmatic terseness
Complex logic is best expressed in programmatic
form
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Commoditised query
Value of query
Value
Provision
De-provision
Cost
Time
Execute
Action Cost
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Hybrid Compatibility
Microsoft are the only vendor with enterprise on
premises and cloud big data offerings
HDInsight in Azure
Hadoop On Premises
NameAndy
Pnid123456
123456 4712
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Just as Big Data is more than Hadoop Windows
Azure is more than HDInsight
HDP Spark Storm
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Elastacloud provisioned a bespoke 500 core
virtual cluster on Windows Azure, allowing us to
cut down a compute intensive task from 20 days
over 8 cores to under 12 hours over 500
cores. Jedidiah Francis, Data Scientist, ASOS
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• Architectural Considerations

• Solving Big Data challenges cohesively

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The first challenge you face with Big Data is
somewhat the hardest
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Elastaclouds tooling aims to solve these
challenges
Ingress, Compute, Egress automated allowing
focus on providing value
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• Workflows

Big Data solutions are rarely the result of a
single piece of code running instead jobs
transform data into intermediate domains before
completing an overall piece of work
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The overall architectural challenge of Big Data
is that just as Data can vary, so must
architectures.
Batch
Interactive
Real Time
Hadoop can operate with O(n) over Petabytes of
data
Drill, Stinger and Tez bring must quicker querying
Storm allows enormous scalable throughput
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Batch Process
Batch
Static Data
Precompute
Serving
Operational Data Store
User Query
Speed
Data Stream
Real Time
Increment
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Technologies possible? Any.
Batch Interactive Real Time
Hadoop SQL / MySQL Storm
Spark Hadoop 2 / Tez / Drill Spark
Lucene Mongo
Cassandra
Windows Azure Table Storage
Spark
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Batch
Static Data
HDInsight
Precompute
Serving
User Query
SQL/NoSQL Database
Speed
Data Stream
Increment
Storm
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Blob Persist
Elastacloud Service Bus Spout
Windows Azure Service Bus
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• Moving Mediatonic to Windows Azure

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AWS didnt work

• Mediatonic are a leading UK games company
• They had deployed an analytics platform to AWS
• They required quite a bit of manpower to maintain
  their system operationally
• Their biggest cost was an Amazon Redshift data
  warehouse which was a bottleneck in their design
• Their system was built so that if a server went
  down whilst collecting gaming messages they could
  lose 15 minutes of data
• They found the Big Data part so complex that
  only highly-paid specialists could improve the
  system

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How Windows Azure Helped

• A joint collaboration between Microsoft,
  Elastacloud and Mediatonic migrated their Game
  Fuel platform to Windows Azure
• With the Windows Azure Service Bus we were able
  to ensure that their messaging was continuous and
  not discrete so no messages were ever lost
• With HDInsight we were able to teach their staff
  how to build Big Data applications
• We were able to deliver a system with unique
  components of Windows Azure, removing the
  expensive data warehousing bottleneck but
  delivering the same functionality

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• I cant believe that I could get up and running
  with HDInsight doing real work in 30 minutes. It
  took me days to do the same thing with Elastic
  Map Reduce on Amazon
• Adam Fletcher Gamefuel Project Lead

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Initial State
Buy the Look
Traditional Analytics
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Limited
Traditional Analytics allows for the tracing of
single actions on a website who added a product
to a bag, where did they come from, where did
they go?
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Advancement
Cross Sell
Buy the Look
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Improvements possible
Beyond immediacy is the ongoing workflow of a
system. Who added items to a basket after using
the Buy the Look functionality. However, this
lacks comprehension of customer behaviour.
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Cutting edge
Who bought this?
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Cutting edge understand your customer
January
February
Purchase propensity
Time
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Proving through Big Data technologies that
engaged customers will return through engagement
following life events such as pay-days to
continue the engagement. Building business on
this basis.
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