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Level 200 Hands-on Workshop
Visualize your data in Data Lake with
AWS Athena and AWS Quicksight
Jeff Ng, Solutions Architect
eCloudvalley 27 July, 2017
Agenda
 About eCloudvalley
 Overview of Amazon Athena?
 Overview of Amazon QuickSight?
 Athena+QuickSight vs ELK
 Demo
 Lab
About eCloudvalley
Create a New Cloud Standard by
becoming
TRUE CLOUD EXPERT.
10 X All 5-Cert Engineers
90+ AWS Certifications
AWS Authorized Instructor
Microsoft Certified Trainer
100% Focus on the
Largest Cloud- AWS
Born-in-the-cloud
System Integrator
https://aws.amazon.com/partners/premier/
The 1st and the Only Premier Partner in GCR
The 1st and the Only Premier
Partner in GCR
AWS China
Region
Consulting
Partner
AWS Premier
Consulting
Partner
(1st and the Only
Premier Partner in
GCR)
Marketing &
Commerce
Competency
AWS Audited
Managed
Services
Provider
Mobile
Competency
Our Offering
Official
AWS Training
DevOps/
Optimization
Next Generation
Managed Services
Fully Managed
AWS
Migration
DataOps/
Big Data/ BI
Overview of Data Analytics
and Visualize
Athena
AthenaS3 QuickSight
Challenges Customers Faced
Significant amount of work required to analyze data in
Amazon S3
Users often only have access to aggregated data sets
Managing a Hadoop cluster or data warehouse requires
expertise
Introducing Amazon Athena
Amazon Athena is an interactive query service that
makes it easy to analyze data directly from Amazon
S3 using Standard SQL
Athena is Serverless
No Infrastructure or
administration
Zero Spin up time
Transparent upgrades
Amazon Athena is Easy To Use
Log into the Console
Create a table
Type in a Hive DDL Statement
Use the console Add Tablewizard
Start querying
Amazon Athena is Highly Available
You connect to a service endpoint or log into the console
Athena uses warm compute pools across multiple
Availability Zones
Your data is in Amazon S3, which is also highly available
and designed for 99.999999999% durability
Query Data Directly from Amazon S3
No loading of data
Query data in its raw format
Text, CSV, JSON, weblogs, AWS service logs
Convert to an optimized form like ORC or Parquet for the best
performance and lowest cost
No ETL required
Stream data from directly from Amazon S3
Take advantage of Amazon S3 durability and availability
Use ANSI SQL
Start writing ANSI SQL
Support for complex joins, nested
queries & window functions
Support for complex data types
(arrays, structs)
Support for partitioning of data by
any key
(date, time, custom keys)
e.g., Year, Month, Day, Hour or
Customer Key, Date
Familiar Technologies Under the Covers
Used for SQL Queries
In-memory distributed query engine
ANSI-SQL compatible with extensions
Used for DDL functionality
Complex data types
Multitude of formats
Supports data partitioning
Amazon Athena Supports Multiple Data
Formats
Text files, e.g., CSV, raw logs
Apache Web Logs, TSV files
JSON (simple, nested)
Compressed files
Columnar formats such as Apache Parquet &Apache ORC
AVRO support
Amazon Athena is Fast
Tuned for performance
Automatically parallelizes
queries
Results are streamed to console
Results also stored in S3
Improve Query performance
Compress your data
Use columnar formats
Amazon Athena is Cost Effective
Pay per query
$5 per TB scanned from S3
DDL Queries and failed queries are free
Save by using compression, columnar formats, partitions
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
A Sample Pipeline
A Sample Pipeline
Ad-hoc access to raw data usingSQL
A Sample Pipeline
Ad-hoc access to raw data usingSQL Athena can query
aggregated datasets as well
Summary
No ETL required. No loading of data. Query data where it lives
Query data at whatever latitude and longitude you want
No infrastructure to manage
Accessing AmazonAthena
Simple Query
editor with key
bindings
Can also see a detailed view
in the catalog tab
You can also check the
properties. Note the location.
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Use the JDBC Driver
Using Amazon Athena with Amazon QuickSight
AmazonS3
AmazonRDS
AmazonRedshift
AmazonAthena
QuickSight allows you to connect to data from a wide variety of AWS, third-party, and on-
premises sources including AmazonAthena
Overview of Amazon QiuckSight
What are the big data challenges
our customers face?
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 of data
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 software implementation time
Introducing
Amazon QuickSight
A fast, cloud-powered, BI service for
1/10 the cost of traditional BI software
$9
per user per month
With 1 year commitment
First analysis in about 60 seconds
Sign-in
Business user
QuickSightAPI
Data prep Metadata SuggestionsConnectors SPICE
Business User 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
Athena
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?
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
Amazon EMR
or Apache
Hadoop
Log files,
applicationAPI
extracts
On-premisesdata
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
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
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
Advantage of Amazon QuickSight
Fast to get started Fast insights with SPICEEasily explore any AWS data
Easy to use and share Effortless scale Low cost
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, acustomer
with 100 user subscriptions will get 1,000 GB of SPICE capacity for theaccount.
Intergrate Amazon Athena
and QuickSight
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop
ELK Dashboard Sample
Athena+Quickview vs. ELK stack
60
Athena (Serverless) ELK Stack
Response Time Inter-active partial results Few seconds
Pre-process time Almost 0 Few Seconds to Minutes
Query String SQL Structured queries
Infrastructure No infra Logstash & Kibana :
EC2
ElastiSearch :
Managed Service
Management effort Low Medium
Input Format CSV、JSON、ORC、Apache
Parquet 和 Avro
JSON 或 XML
Price model Charge by Scanned data Charge by
Infrastructure
Index doc
Front-end QuickSight Kibana
Please fill in feedback form to get
AWS credit
Thank you

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Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on Workshop

  • 1. Level 200 Hands-on Workshop Visualize your data in Data Lake with AWS Athena and AWS Quicksight Jeff Ng, Solutions Architect eCloudvalley 27 July, 2017
  • 2. Agenda  About eCloudvalley  Overview of Amazon Athena?  Overview of Amazon QuickSight?  Athena+QuickSight vs ELK  Demo  Lab
  • 4. Create a New Cloud Standard by becoming TRUE CLOUD EXPERT. 10 X All 5-Cert Engineers 90+ AWS Certifications AWS Authorized Instructor Microsoft Certified Trainer 100% Focus on the Largest Cloud- AWS Born-in-the-cloud System Integrator
  • 6. The 1st and the Only Premier Partner in GCR AWS China Region Consulting Partner AWS Premier Consulting Partner (1st and the Only Premier Partner in GCR) Marketing & Commerce Competency AWS Audited Managed Services Provider Mobile Competency
  • 7. Our Offering Official AWS Training DevOps/ Optimization Next Generation Managed Services Fully Managed AWS Migration DataOps/ Big Data/ BI
  • 8. Overview of Data Analytics and Visualize
  • 11. Challenges Customers Faced Significant amount of work required to analyze data in Amazon S3 Users often only have access to aggregated data sets Managing a Hadoop cluster or data warehouse requires expertise
  • 12. Introducing Amazon Athena Amazon Athena is an interactive query service that makes it easy to analyze data directly from Amazon S3 using Standard SQL
  • 13. Athena is Serverless No Infrastructure or administration Zero Spin up time Transparent upgrades
  • 14. Amazon Athena is Easy To Use Log into the Console Create a table Type in a Hive DDL Statement Use the console Add Tablewizard Start querying
  • 15. Amazon Athena is Highly Available You connect to a service endpoint or log into the console Athena uses warm compute pools across multiple Availability Zones Your data is in Amazon S3, which is also highly available and designed for 99.999999999% durability
  • 16. Query Data Directly from Amazon S3 No loading of data Query data in its raw format Text, CSV, JSON, weblogs, AWS service logs Convert to an optimized form like ORC or Parquet for the best performance and lowest cost No ETL required Stream data from directly from Amazon S3 Take advantage of Amazon S3 durability and availability
  • 17. Use ANSI SQL Start writing ANSI SQL Support for complex joins, nested queries & window functions Support for complex data types (arrays, structs) Support for partitioning of data by any key (date, time, custom keys) e.g., Year, Month, Day, Hour or Customer Key, Date
  • 18. Familiar Technologies Under the Covers Used for SQL Queries In-memory distributed query engine ANSI-SQL compatible with extensions Used for DDL functionality Complex data types Multitude of formats Supports data partitioning
  • 19. Amazon Athena Supports Multiple Data Formats Text files, e.g., CSV, raw logs Apache Web Logs, TSV files JSON (simple, nested) Compressed files Columnar formats such as Apache Parquet &Apache ORC AVRO support
  • 20. Amazon Athena is Fast Tuned for performance Automatically parallelizes queries Results are streamed to console Results also stored in S3 Improve Query performance Compress your data Use columnar formats
  • 21. Amazon Athena is Cost Effective Pay per query $5 per TB scanned from S3 DDL Queries and failed queries are free Save by using compression, columnar formats, partitions
  • 24. A Sample Pipeline Ad-hoc access to raw data usingSQL
  • 25. A Sample Pipeline Ad-hoc access to raw data usingSQL Athena can query aggregated datasets as well
  • 26. Summary No ETL required. No loading of data. Query data where it lives Query data at whatever latitude and longitude you want No infrastructure to manage
  • 28. Simple Query editor with key bindings
  • 29. Can also see a detailed view in the catalog tab
  • 30. You can also check the properties. Note the location.
  • 32. Use the JDBC Driver
  • 33. Using Amazon Athena with Amazon QuickSight AmazonS3 AmazonRDS AmazonRedshift AmazonAthena QuickSight allows you to connect to data from a wide variety of AWS, third-party, and on- premises sources including AmazonAthena
  • 34. Overview of Amazon QiuckSight
  • 35. What are the big data challenges our customers face?
  • 36. 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 of data Lots and lots of questions Few insights
  • 37. 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
  • 39. A fast, cloud-powered, BI service for 1/10 the cost of traditional BI software
  • 40. $9 per user per month With 1 year commitment
  • 41. First analysis in about 60 seconds Sign-in Business user
  • 42. QuickSightAPI Data prep Metadata SuggestionsConnectors SPICE Business User 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 Athena
  • 43. 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?
  • 44. 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
  • 45. Amazon EMR or Apache Hadoop Log files, applicationAPI extracts On-premisesdata 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
  • 46. 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
  • 47. 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
  • 48. Native mobile experience • iOS,Android • Full experience on tablets • Consumption experience on smart phones • Very fast response
  • 49. 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
  • 50. Advantage of Amazon QuickSight Fast to get started Fast insights with SPICEEasily explore any AWS data Easy to use and share Effortless scale Low cost
  • 51. 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, acustomer with 100 user subscriptions will get 1,000 GB of SPICE capacity for theaccount.
  • 60. Athena+Quickview vs. ELK stack 60 Athena (Serverless) ELK Stack Response Time Inter-active partial results Few seconds Pre-process time Almost 0 Few Seconds to Minutes Query String SQL Structured queries Infrastructure No infra Logstash & Kibana : EC2 ElastiSearch : Managed Service Management effort Low Medium Input Format CSV、JSON、ORC、Apache Parquet 和 Avro JSON 或 XML Price model Charge by Scanned data Charge by Infrastructure Index doc Front-end QuickSight Kibana
  • 61. Please fill in feedback form to get AWS credit