Slide 1: Big Data on AWS
Big Data on AWS Big Data Agility and Performance Delivered in the Cloud © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Slide 2: Managed Services for Analytics
Managed Services for Analytics Retrospective Here-and-now Predictions analysis and real-time processing to enable smart reporting and dashboards applications
Slide 3: The Cloud removes constraints
Elastic and highly scalable + No upfront capital expense + Only pay for what you use + Available on-demand = the Cloud removes constraints
Slide 4: The Cloud Was Built for Big Data
The Cloud Was Built for Big Data
Slide 5: Common Big Data Flow
Common Big Data Flow Collect, Generate Analyze Orchestrate, Store Lower Cost Traditionally - Highly constrained Increased Velocity
Slide 6: AWS Big Data Platform
AWS Big Data Platform Collect Orchestrate Store Analyze
Slide 7: No one tool rules them all
No one tool rules them all
Slide 8: The AWS Approach
The AWS Approach • Flexible - Use the best tool for the job • Data structure, latency, throughput, access patterns • Low Cost - Big data ≠ big cost • Scalable – Data should be immutable (append-only) • Batch/speed/serving layer • Minimize Admin Overhead - Leverage AWS managed services • No or very l
Slide 9: Building a Data Lake on AWS
Building a Data Lake on AWS Catalog & Search Access & User Interface Access and search metadata Give your users easy and secure access Waterline Data. RReltio é3 oF alik@ APIGateway —_ Identity & Access Cognito | It Management | MicroStrategy Hyetableau Data Ingestion Processing & Analytics Use of p
Slide 10: A Sample Batch Analytics Pipeline
A Sample Batch Analytics Pipeline Snowflake Athena can query Ad-hoc access to data using Athena aggregated datasets as well
Slide 11: On-demand Big Data Analytics
On-demand Big Data Analytics Snowflake
Slide 12: Data Warehousing
Data Warehousing Data Sources $3 EMR $3 Snowflake QuickSight Upload data Use Amazon EMR Load formatted Analyze and visualize from multiple to transform and and cleansed \ data with Amazon sources into S3 cleanse the data data into S3 Quicksight (ETL) webservices
Slide 13: Summary
Summary • Build sophisticated Big Data applications cost-effectively and support retrospective, real-time and predictive analysis • You can build incrementally, scale automatically and add use cases as you go • AWS delivers added benefits of security and auditing features to enable you to meet your
Slide 14: Getting Started: Tutorials & Blog
Getting Started: Tutorials & Blog Subscribe to the AWS Big Data Blog: http://blogs.aws.amazon.com/bigdata/