Presentation for "Cloud Software Development Course" on 18 August 2015

1. Big Data
Using Public Cloud
Assoc. Prof. Dr. Thanachart Numnonda
Executive Director
IMC Institute
18 August 2015

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Internet of ThingsCloud Computing
Big Data

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Data created every minute
Source: Trendwise Analytics

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Data!
The New York Stock Exchange generate about
1TB of new trade data per day.
A commercial aircraft generates 3GB of flight
sensor data in 1 hour.
Vodafone generates 3TB of Call Detail Record
(CRDs) per day.
Between 2009 and 2014, the total number of U.S.
online banking households will increase from 54
million to 66 million.

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Big Data
Source: http://www.datasciencecentral.com/

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Sample Data v.s. Big Data
Can you judge a persons life expectancy?
Given:
– DNA
– Medical records
– Food
– Lifestyle (smoking, drinking, driving, exercise)

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IT Infrastructure
Analytics
Data Sources

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“Bัy 2015, 20% of Global 1000 organizations
Will have established a strategic focus on
information infrastructure ”
Gartner

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Big Data Technology !!

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Big Data Landscape
Source: Big Data in the Enterprise. When to Use What?

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A scalable fault-tolerant distributed system
for data storage and processing
Completely written in java
Open source & distributed under Apache license
What is Hadoop?

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Hadoop Environment
Source: Hadoop in Practice; Alex Holmes

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Hadoop Distribution
Microsoft Azure

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Big Data Future Architecture
Sscial Media Images e-mails Crawlers
ERP CRM LOB APPs
Unstructured and Structured Data
Data Warehouse / NewSQL
Hadoop On
Cloud
Hadoop On
Private
Server
Connectors
S
S
R
S
BI Platform
Familiar End User Tools
Spreadsheet Predictive Analytics
Data Market Place
NoSQL
Petabytes of Data
(Unstructured)
Hundreds of TB of Data
(structured)

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Issue with Big Data Infrastructure
Large investment
Scalabilty
ROI
Business Cases

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Big Data on Cloud
Using IaaS to leverage Cloud Vms
Using Big Data as a Services

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Big Data using IaaS

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Source: http://www.datadansandler.com/

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Big Data Services on Cloud
Amazon
Elastic Mapreduce
Microsoft Azure Hadoop

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Big Data as a Service

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Database as a Service
Amazon RDS
IBM SQL Database for Bluemix
Microsoft SQL Database
Google CloudSQL

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NoSQL as a Service
Amazon DynomoDB
Google Cloud DataStore
Microsoft Azure DocumentDB
Cloudant on IBM Bluemix.
Mongo DB on Heroku

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Amazon DynomoDB

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Hadoop as a Service
Amazon Elastic Map Reduce
Rackspace Cloud Big Data Platform
Qubole
Google Cloud Platform
IBM Bluemix: Analytic on Hadoop
Microsoft Azure HDInsight

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Big Data on Amazon EMR

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Amazon EMR

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Hadoop on Google

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Analytic as a Service
Google Big Query
Amazon Machine Learning
Azure Machine Learning
BIME: BI as a Service
IBM Watson Analytic

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Google BigQuery

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Big Data on Cloud Roadmap
Step 1: Build the business case
Step 2: Assess your Big Data application
workloads
Step 3: Develop a technical approach for
deploying and managing Big Data in the cloud
Step 4: Address governance, security, privacy,
risk,
Step 5: Deploy, integrate, and operationalize
your cloud-based Big Data infrastructure
Source : Deploying Big Data Analytics Applications to the Cloud: Roadmap for Success: CSCS

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Sample applications
Enterprise applications already hosted in the
cloud
High-volume external data sources that
require considerable preprocessing
Tactical applications beyond your on-
premises, Big Data capabilities
Elastic provisioning of very large but short-
lived analytic sandboxes
Source : Deploying Big Data Analytics Applications to the Cloud: Roadmap for Success: CSCS

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www.facebook.com/imcinstitute

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Thank you
thanachart@imcinstitute.com
www.facebook.com/imcinstitute
www.slideshare.net/imcinstitute
www.thanachart.org