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Big data using Public Cloud
Big data refers to the large volumes of data that are constantly being generated. This document discusses how big data is being generated from various sources like stock exchanges, aircraft sensors, phone calls, and online banking. It then discusses using public cloud infrastructure and services like Amazon Web Services, Microsoft Azure, and Google Cloud Platform to analyze and manage big data using tools and frameworks like Hadoop. The cloud provides scalable and cost-effective options for organizations to build big data solutions without having to make large up-front investments in hardware.
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Big data using Public Cloud
- 1. Big Data Using PublicCloud Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 18 August 2015
- 2. 2 Internet of ThingsCloudComputing Big Data
- 3. 3 Data created everyminute Source: Trendwise Analytics
- 4. 4 Data! The New YorkStock 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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- 7. 7 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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- 9. 9 “Bัy 2015, 20%of Global 1000 organizations Will have established a strategic focus on information infrastructure ” Gartner
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- 11. 11 Big Data Landscape Source:Big Data in the Enterprise. When to Use What?
- 12. 12 A scalable fault-tolerantdistributed system for data storage and processing Completely written in java Open source & distributed under Apache license What is Hadoop?
- 13. 13 Hadoop Environment Source: Hadoopin Practice; Alex Holmes
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- 15. 15 Big Data FutureArchitecture 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)
- 16. 16 Issue with BigData Infrastructure Large investment Scalabilty ROI Business Cases
- 17. 17 Big Data onCloud Using IaaS to leverage Cloud Vms Using Big Data as a Services
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- 22. 22 Big Data Serviceson Cloud Amazon Elastic Mapreduce Microsoft Azure Hadoop
- 23. 23 Big Data asa Service
- 24. 24 Database as aService Amazon RDS IBM SQL Database for Bluemix Microsoft SQL Database Google CloudSQL
- 25. 25 NoSQL as aService Amazon DynomoDB Google Cloud DataStore Microsoft Azure DocumentDB Cloudant on IBM Bluemix. Mongo DB on Heroku
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- 27. 27 Hadoop as aService 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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- 30. 30 Big Data onAmazon EMR
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- 36. 36 Analytic as aService Google Big Query Amazon Machine Learning Azure Machine Learning BIME: BI as a Service IBM Watson Analytic
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- 40. 40 Big Data onCloud 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
- 41. 41 Sample applications Enterprise applicationsalready 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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