Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce you to SPICE -  a Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
April 19, 2016
Getting Started with
Amazon QuickSight
Greg Khairallah, Business Development Manager
Wangechi Doble, Solutions Architect

2. What to expect from the session
• Overview of big data and 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 and difficult
SQL databases do not perform well at scale
Hadoop is difficult to deploy and manage
Data warehouses are complex, costly, and slow
Commercial DBs are punitive and expensive
Streaming data is difficult to capture and analyze
 Amazon RDS
 Amazon DynamoDB
 Amazon EMR
 Amazon Redshift
 Amazon Aurora
 Amazon Kinesis

6. AnalyzeStore
Amazon
Glacier
Amazon
S3
Amazon
DynamoDB
Amazon RDS/
Amazon 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
AWS Data
Pipeline
Amazon
CloudSearch
Amazon
EMR
Amazon
EC2
Amazon
Redshift
Amazon
Machine
LearningAWS
Import/Export
AWS Direct
Connect
Collect
Amazon Kinesis
AWS Database
Migration
New
Amazon
Kinesis
Firehose
New
Amazon
Elasticsearch
Amazon
Kinesis
Analytics
New
Amazon
QuickSight
New
New

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 software 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

13. Introducing
Amazon QuickSight

14. A fast, cloud-powered, BI service for
1/10 the cost of traditional BI software

15. $9
per user per month
With 1 year commitment

16. Business user
Sign-in
First analysis in about 60 seconds

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-premises data

18. I have multiple datasets both on-premises and on
AWS from different sources, and I need to make
data available and enable access by using
Amazon 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 by using Amazon QuickSight

20. Amazon EMR
or Apache
Hadoop
Log files,
application API
extracts
On-premises data
Amazon
Redshift
Amazon
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 and data
access needs
Data access
managed at
the data lake
Data enabled
by user
in data marts

21. Innovations
• Easy exploration of AWS data
• Fast insights with SPICE (Super-fast, Parallel, In-memory Calculation Engine)
• Intuitive visualizations and transitions with AutoGraph
• Native mobile experience
• Secure sharing and collaboration through StoryBoards

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
• NoSQL databases
• Amazon EMR, Amazon S3, files
• Streaming data sources
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
• 2x 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

30. Demo Overview
Stocks/Tweets DB
Amazon Redshift
Dense Compute Node
Cluster
AmazonKinesis
Firehose
StockMarket
FinancialData
Tweets
CustomScripts
AmazonEC2
CustomApp
AmazonEC2
Stocks CSV files
Amazon S3
Visualization with
Amazon QuickSight
Tweets JSON files
Amazon S3

31. Embeddable

32. Fast to get started Fast insights with SPICEEasily explore any AWS data
Easy to use and share Effortless scale Low cost

33. Amazon QuickSight pricing
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 subscriptions will get 1,000 GB of SPICE capacity for the account.

34. Sign-in
Register for the preview @ aws.amazon.com/quicksight

35. Thank You!
http://aws.amazon.com/quicksight