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© 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Sundar Raghavan, Director, AWS
October 2015
Amazon QuickSight
What to Expect from the Session
• Overview of Big Data & Analytics strategy
• Challenges our customers face in Big Data Analytics
• Amazon innovations
• What’s next?
Many thousands of companies use AWS for Big Data
We start with the customer
We take on the big challenges they have
We innovate
We start with the customer… and innovate
Customers told us… We created…
Managing databases is painful & difficult
SQL DBs do not perform well at scale
Hadoop is difficult to deploy and manage
DWs are complex, costly, and slow
Commercial DBs are punitive & expensive
Streaming data Is difficult to capture & analyze
 Amazon RDS
 Amazon DynamoDB
 Amazon EMR
 Amazon Redshift
 Amazon Aurora
 Amazon Kinesis
AnalyzeStore
Amazon
Glacier
Amazon
S3
Amazon
DynamoDB
Amazon RDS/
Aurora
AWS big data portfolio
AWS Data
Pipeline
Amazon
CloudSearch
Amazon
EMR
Amazon
EC2
Amazon
Redshift
Amazon
Machine
LearningAWS
Import/Export
AWS Direct
Connect
Collect
Amazon Kinesis
AnalyzeStore
Amazon
Glacier
Amazon
S3
Amazon
DynamoDB
Amazon RDS,
Aurora
AWS big data portfolio – new services
AWS Data
Pipeline
Amazon
CloudSearch
Amazon
EMR
Amazon EC2
Amazon
Redshift
Amazon
Machine
Learning
Amazon
Elasticsearch
AWS Database
Migration
New
Amazon
Kinesis
Analytics
New
Amazon
Kinesis
Firehose
New
AWS
Import/Export
AWS Direct
Connect
Collect
Amazon Kinesis Amazon
QuickSight
New
Launched
What are the Big Data challenges
our customers face?
Lots of data
Who are my top customers and what are they buying?
Which devices are showing time for maintenance?
What is my product profitability by region?
Why is my most profitable region not growing?
How much inventory do I have?
Has my fraud account expense increased?
How is my marketing campaign performing?
How is my employee satisfaction trending?
Lots and lots of questions
Few insights
Old-guard BI
Costs Too Much
Pay $ million before seeing first analysis
3 year TCO $150 to $250 per user per month
Takes Too Long
Spend 6 to 12 months of consulting
and SW implementation time
Can’t handle NoSQL, Streaming Data
Time
Cost
Pay $ millions for license and hardware
Requires 6 to 12 months of consulting
Slower performance at scale
Doesn’t deliver fast query performance
Extra $$ For Mobile and Sharing
Extra $$ For IoT Dashboards
Old-guard BI
Freedom to get the real value
out of the data you have
Introducing
Amazon QuickSight
A very fast, cloud-powered, BI service for
1/10th the cost of old-guard BI software
$9
per user per month
With 1 year commitment
Business user
Sign-in
First analysis in about 60 seconds
Register for preview beginning Oct 7 at aws.amazon.com/quicksight
Business User
QuickSight API
Data Prep Metadata SuggestionsConnectors SPICE
Business User
QuickSight UI
Mobile Devices Web Browsers
Partner BI products
Amazon
S3
Amazon
Kinesis
Amazon
DynamoDB
Amazon
EMR
Amazon
Redshift
Amazon RDSFiles Apps
Direct connect
JDBC/ODBC
On premise Data
I have multiple data sets both on premise, and on
AWS, from different sources, and need to make data
available and enable access via QuickSight.
How do I do this?
1. Data made available in “Data Lakes” using Amazon S3 or
Amazon Redshift
2. Data access managed with bucket or schema level policies
3. Data enabled via Amazon QuickSight
Amazon EMR
or Hadoop
Log Files,
Application API
Extracts
On prem data
Amazon
Redshift
DynamoDB or EC2
based MongoDB,
Cassandra
Amazon
S3
Data made
available in
data lakes
QuickSight
Mobile Devices Web Browsers
Bucket or Schema
level permissions
by user cohort and
data access needs
Data access
managed at
the data lake
Data enabled
by user cohort
In data marts
Innovations
• Easy exploration of AWS data
• Fast insights with SPICE
• Intuitive visualizations and transitions (AutoGraph)
• Native mobile experience
• Secure sharing and collaboration (StoryBoard)
How do I SPICE up my data?
AWS October Webinar Series - Introducing Amazon QuickSight
Easy exploration of AWS data
• Securely discover and connect to AWS data
• Quickly explore AWS data sources
• Relational databases (Amazon RDS, Amazon RDS for Aurora,
Amazon Redshift)
• NoSQL databases (Amazon DynamoDB)
• Amazon EMR, Amazon S3, files (CSV, Excel, TSV, XLF, CLF)
• Streaming data sources (Amazon DynamoDB, Amazon Kinesis)
• Easily import data from any table or file
• Automatic detection of data types
Fast insights with SPICE
• Super-fast, Parallel, In-memory optimized, Calculation Engine
• 2 to 4x compression columnar data
• Compiled queries with machine code generation
• Rich calculations
• SQL-like syntax
• Very fast response time to queries
• Fully managed – No hardware or software to license
Intuitive visualizations with AutoGraph
• Automatic detection of data types
• Optimal query generation
• Appropriate graph type selection
• Ability to customize the graph type
• Very fast response
Native mobile experience
• iOS, Android
• Full experience on tablets
• Consumption experience
on smart phones
• Very fast response
Tell a story with your data
• Capture the critical snapshot of analysis
• Build a sequence of analysis
• Share it securely
• Enable interactive exploration
• Very fast response
DEMO
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
Fast to get started Fast insights with SPICEEasily explore any AWS data
Easy to use and share Effortless scale Low cost
Low cost
Standard Edition
Ad-hoc analysis, data connectors,
sharing, embedding, mobile experience
+ 10 GB of SPICE storage
1/10th the cost of old-guard BI
Enterprise Edition
Standard Edition + Active Directory
integration, user access control, encryption
at rest, 2X throughput
$9
$18
Per user per month
Per user per month
Pricing details
Standard Edition Enterprise Edition
Subscription Annual Monthly Annual Monthly
Price per user per month $9 $12 $18 $24
SPICE Capacity (GB) 10 10 10 10
Additional SPICE
GB-month $0.25 $0.38
Per user SPICE capacity is pooled across all users in an account. As an example, a customer with 100 user
subscription will get 1,000GB SPICE capacity for the account.
Sign up for Preview at ..
http://aws.amazon.com/quicksight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
Spring
Fitness
promotion
did very well
for Yoga
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight
AWS October Webinar Series - Introducing Amazon QuickSight

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AWS October Webinar Series - Introducing Amazon QuickSight

  • 1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Sundar Raghavan, Director, AWS October 2015 Amazon QuickSight
  • 2. What to Expect from the Session • Overview of Big Data & Analytics strategy • Challenges our customers face in Big Data Analytics • Amazon innovations • What’s next?
  • 3. Many thousands of companies use AWS for Big Data
  • 4. We start with the customer We take on the big challenges they have We innovate
  • 5. We start with the customer… and innovate Customers told us… We created… Managing databases is painful & difficult SQL DBs do not perform well at scale Hadoop is difficult to deploy and manage DWs are complex, costly, and slow Commercial DBs are punitive & expensive Streaming data Is difficult to capture & analyze  Amazon RDS  Amazon DynamoDB  Amazon EMR  Amazon Redshift  Amazon Aurora  Amazon Kinesis
  • 6. AnalyzeStore Amazon Glacier Amazon S3 Amazon DynamoDB Amazon RDS/ Aurora AWS big data portfolio AWS Data Pipeline Amazon CloudSearch Amazon EMR Amazon EC2 Amazon Redshift Amazon Machine LearningAWS Import/Export AWS Direct Connect Collect Amazon Kinesis
  • 7. AnalyzeStore Amazon Glacier Amazon S3 Amazon DynamoDB Amazon RDS, Aurora AWS big data portfolio – new services AWS Data Pipeline Amazon CloudSearch Amazon EMR Amazon EC2 Amazon Redshift Amazon Machine Learning Amazon Elasticsearch AWS Database Migration New Amazon Kinesis Analytics New Amazon Kinesis Firehose New AWS Import/Export AWS Direct Connect Collect Amazon Kinesis Amazon QuickSight New Launched
  • 8. What are the Big Data challenges our customers face?
  • 9. Lots of data Who are my top customers and what are they buying? Which devices are showing time for maintenance? What is my product profitability by region? Why is my most profitable region not growing? How much inventory do I have? Has my fraud account expense increased? How is my marketing campaign performing? How is my employee satisfaction trending? Lots and lots of questions Few insights
  • 10. Old-guard BI Costs Too Much Pay $ million before seeing first analysis 3 year TCO $150 to $250 per user per month Takes Too Long Spend 6 to 12 months of consulting and SW implementation time
  • 11. Can’t handle NoSQL, Streaming Data Time Cost Pay $ millions for license and hardware Requires 6 to 12 months of consulting Slower performance at scale Doesn’t deliver fast query performance Extra $$ For Mobile and Sharing Extra $$ For IoT Dashboards Old-guard BI
  • 12. Freedom to get the real value out of the data you have
  • 14. A very fast, cloud-powered, BI service for 1/10th the cost of old-guard BI software
  • 15. $9 per user per month With 1 year commitment
  • 16. Business user Sign-in First analysis in about 60 seconds Register for preview beginning Oct 7 at aws.amazon.com/quicksight
  • 17. Business User QuickSight API Data Prep Metadata SuggestionsConnectors SPICE Business User QuickSight UI Mobile Devices Web Browsers Partner BI products Amazon S3 Amazon Kinesis Amazon DynamoDB Amazon EMR Amazon Redshift Amazon RDSFiles Apps Direct connect JDBC/ODBC On premise Data
  • 18. I have multiple data sets both on premise, and on AWS, from different sources, and need to make data available and enable access via QuickSight. How do I do this?
  • 19. 1. Data made available in “Data Lakes” using Amazon S3 or Amazon Redshift 2. Data access managed with bucket or schema level policies 3. Data enabled via Amazon QuickSight
  • 20. Amazon EMR or Hadoop Log Files, Application API Extracts On prem data Amazon Redshift DynamoDB or EC2 based MongoDB, Cassandra Amazon S3 Data made available in data lakes QuickSight Mobile Devices Web Browsers Bucket or Schema level permissions by user cohort and data access needs Data access managed at the data lake Data enabled by user cohort In data marts
  • 21. Innovations • Easy exploration of AWS data • Fast insights with SPICE • Intuitive visualizations and transitions (AutoGraph) • Native mobile experience • Secure sharing and collaboration (StoryBoard)
  • 22. How do I SPICE up my data?
  • 24. Easy exploration of AWS data • Securely discover and connect to AWS data • Quickly explore AWS data sources • Relational databases (Amazon RDS, Amazon RDS for Aurora, Amazon Redshift) • NoSQL databases (Amazon DynamoDB) • Amazon EMR, Amazon S3, files (CSV, Excel, TSV, XLF, CLF) • Streaming data sources (Amazon DynamoDB, Amazon Kinesis) • Easily import data from any table or file • Automatic detection of data types
  • 25. Fast insights with SPICE • Super-fast, Parallel, In-memory optimized, Calculation Engine • 2 to 4x compression columnar data • Compiled queries with machine code generation • Rich calculations • SQL-like syntax • Very fast response time to queries • Fully managed – No hardware or software to license
  • 26. Intuitive visualizations with AutoGraph • Automatic detection of data types • Optimal query generation • Appropriate graph type selection • Ability to customize the graph type • Very fast response
  • 27. Native mobile experience • iOS, Android • Full experience on tablets • Consumption experience on smart phones • Very fast response
  • 28. Tell a story with your data • Capture the critical snapshot of analysis • Build a sequence of analysis • Share it securely • Enable interactive exploration • Very fast response
  • 29. DEMO
  • 32. Fast to get started Fast insights with SPICEEasily explore any AWS data Easy to use and share Effortless scale Low cost
  • 33. Low cost Standard Edition Ad-hoc analysis, data connectors, sharing, embedding, mobile experience + 10 GB of SPICE storage 1/10th the cost of old-guard BI Enterprise Edition Standard Edition + Active Directory integration, user access control, encryption at rest, 2X throughput $9 $18 Per user per month Per user per month
  • 34. Pricing details Standard Edition Enterprise Edition Subscription Annual Monthly Annual Monthly Price per user per month $9 $12 $18 $24 SPICE Capacity (GB) 10 10 10 10 Additional SPICE GB-month $0.25 $0.38 Per user SPICE capacity is pooled across all users in an account. As an example, a customer with 100 user subscription will get 1,000GB SPICE capacity for the account.
  • 35. Sign up for Preview at .. http://aws.amazon.com/quicksight