Big Data and Analytics on Amazon Web Services: Building A Business-Friendly Platform
-
Upload
amazon-web-services -
Category
Technology
-
view
369 -
download
0
Transcript of Big Data and Analytics on Amazon Web Services: Building A Business-Friendly Platform
© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Blair Layton, Business Development, APAC
May 2016
Building a business-friendly platform
Big Data and Analytics on AWS
Content
• Cases in business-led Big Data solutions
• Finding your shortest path to results
Three big indicators of individual behavior
Purchases Movement Influence
A platform to build business outcomes from data
Purchases
Movement
Influence
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
1 40 9
5
Revenue Lift
Market
acquisition
Customer delight
Brand advocacy
Inventory
optimization
Supply chain
efficiency
...
Business case determines platform design
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Answers &
Insights
START HEREWITH A BUSINESS CASE
Modernization Go mobile Data platform Automation Engagement IOT
Excellence in data Excellence in analytics
Six common categories of investments in Big Data
Capture windows of opportunity
A full-service residential real estate brokerage
Redfin manages data on
hundreds of millions
of properties and
millions of customers
The Hot Homes algorithm
automatically calculates
the likelihood by analyzing
more than 500 attributes
of each home
Was fully AWS-native
since day one
https://aws.amazon.com/solutions/case-studies/redfin/
Hot Homes
Modernization Go mobile Data platform Automation Engagement IOT
There's an 80% chance this home will sell in the next 11 days – go tour it soon.
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Amazon S3
Data lakeAmazon EMR
Amazon
Kinesis
Amazon RedShift
Answers &
Insights
Hot HomesUsers
Properties
Agents
User Profile
Recommendation
Hot Homes
Similar Homes
Agent Follow-up
Agent Scorecard
Marketing
A/B Testing
Real Time Data
…
Amazon
DynamoDB
BI / Reporting
Modernize and decouple to innovate
One of Vietnam's largest private sector companies
Leads the market in many
segments of CPG, and
serves retailers nationwide
with a diverse range of
food and beverage
products
Due to the transportation
infrastructure, it must
manage a complex supply
and delivery chain, with
limited downstream
visibility
With visionaries that are
driving the group to new
innovations, they need to
modernize and decouple
legacy technologies
Large Vietnamese Manufacturing Conglomerate
Modernization Go mobile Data platform Automation Engagement IOT
Need to create incentives for motorbike delivery team to fill underserved markets
Created mobile applications that track the delivery performance of the various
contractors and employees, and the consumption of goods at the point of sale.
The mobile apps use behavioral analysis to understand what is impacting
performance and a gamification engine has been introduced.
Large Vietnamese Manufacturing Conglomerate
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Amazon S3
Data lake
Amazon EMR
Amazon RedShift
Answers &
Insights
Mobile usage
Performance by category,
channel, and region
Demand forecast
Incentives to fill
underserved markets
Gamification of channel
sales
Supply chain visibility
…
Transactions
On-premises
Transactional
Database
CRM
On-premises
CRM system
Legacy BI /
Report Users
Large Vietnamese Manufacturing Conglomerate
Media streaming
Free steak campaign
Disaster recovery
Facebook app
Ground campaign
SAP & SharePoint
Marketing web site
Social Media Monitoring
Consumer social app
IT operations
Mars exploration ops
Interactive TV apps
Consumer social app
Securities Trading Data Archiving
Financial markets analytics
Web and mobile apps
Big data analytics
Digital media
Ticket pricing optimization
Streaming webcasts
Mobile analytics
Consumer social app
Core IT and media
Demand forecasting
Operations insights
Content
• Cases in business-led Big Data solutions
• Finding your shortest path to results
Amazon Redshift Amazon Elastic
MapReduce
Data Warehouse Semi-structured
Amazon Glacier
Use an optimal combination of highly interoperable services
Amazon Simple
Storage Service
Data Storage Archive
Amazon
DynamoDB
Amazon Machine
Learning
Amazon Kinesis
NoSQL Predictive Models Other AppsStreaming
Administration
& Security
Access
ControlIdentity
Management
Key Management
& Storage
Monitoring
& Logs
Resource &
Usage Auditing
Platform
Services
Analytics App Services Developer Tools & Operations Mobile Services
Data
Pipelines
Data
Warehouse
Hadoop
Real-time
Streaming Data
Application
Lifecycle
Management
Containers
Deployment
DevOps
Event-driven
Computing
Resource
Templates
Identity
Mobile
Analytics
Push
Notifications
Sync
App
Streaming
Queuing &
Notifications
Search
Transcoding
Workflow
Core
Services
CDNCompute(VMs, Auto-scaling
& Load Balancing)
Databases(Relational,
NoSQL, Caching)
Networking(VPC, DX, DNS)
Storage(Object, Block
and Archival)
Infrastructure
Availability
Zones
Points of
PresenceRegions
Enterprise
Applications
Business
Sharing &
Collaboration
Virtual
Desktop
Technical &
Business Support
Account
Management
Partner
Ecosystem
Professional
Services
Security &
Pricing Reports
Solutions
ArchitectsSupport
Training &
Certification
Experiment and scale based on your business needs
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Answers &
Insights
SHORT LISTBUSINESS CASES
Modernization Automation
Experiment and scale based on your business needs
MATCHAVAILABLE DATA
Metrics and
Monitoring
Workflow
Logs
ERP
Transactions
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Answers &
Insights
Experiment and scale based on your business needs
AWS
Import/ Export
Amazon S3
Amazon
Kinesis
Amazon
EMR
Ingest/
Collect
Consume/
visualizeStore
Process/
analyze
Data
1 40 9
5
Answers &
Insights
Amazon
Redshift
Amazon
QuickSight
Amazon
SQS
CHOOSEBEST FIT
Rethink how to become a data-
driven business• Business outcomes - start with the insights and
actions you want to drive, then work backwards to a
streamlined design
• Experimentation - start small, test many ideas,
keep the good ones and scale those up, paying only
for what you consume
• Agile and timely - deploy data processing
infrastructure in minutes, not months. take
Thank you!