[Keynote] Data Driven Organizations with AWS Data - 발표자: Agnes Panosian, Head of APJ Data Sales, WWSO, AWS ::: AWS Data Roadshow 2023

© 2023, Amazon Web Services, Inc. or its affiliates.
Data Driven
Organizations with
AWS for Data

Agenda
2
• What is a data driven organization?
• Partner with AWS to drive cost savings and
innovation
• Driving sustainability with data
• Next steps on your data journey

Gen AI
• Rapid Advancement in Gen AI is driving unparallel business and
social opportunities.
• What has changed?
Autocomplete words to self learning models
Sematic Search and Retrieval Augmented Generation (RAG)
• What do we need?
Compute Capacity to train and process
Data (private / internet) to train and process on
Foundational models
Interfaces to output
3

Evolution of AI
4
AI
Reasoning
Machine Learning
(Supervised, Unsupervised)
Non-Neural
(Big Data)
Neural Networks
Deep Learning
Generative
AI
Predictive AI
Shallow Learning
Regression
SVM etc..

5

© 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon Confidential and Trademark. 6
GenAI Use Case by Vertical
MFG
HCLS
Asset and wealth
management;
Insurance
Vertical Subvertical GenAI Pattern
Selected use cases
Synthesis, analysis
B. Support of life insurance underwriting and pricing through unstructured data
synthesis
FSI Chatbot, analysis
A. Personalized investment portfolio creation through chatbot assistance
B. Scientific literature research through text summary and synthesis
Pharma Data tagging, analysis
A. Personalized HCP engagement plans through automatic data tagging
M&E Publishing Image generation
R&D; Maintenance 3D object design
A. Faster and cheaper part design through generative design
Text synthesis
B. Automation of manual tasks through text summary and synthesis
P&U Energy and plants Text analysis, generation
R/CPG Retail consumer Content generation
A. Improved marketing efforts through enhanced customer segmentation and hyper-
personalized content creation
Analyses, content creation
B. Improve customer journey and product offering through product analyses and
content creation
TTL Shipping Analysis, text synthesis
A. Reduced manual intervention and improved lead time on bill of lading process
through document generation
Text synthesis, chatbot
B. Increased work efficiency and customer satisfaction in disruption handling through
conversational interface
B. A/B testing through rapid generation of headlines and thumbnails
A. Support of text content through image, diagram and visuals generation
Text synthesis
Text generation
A. Acceleration of machine maintenance through semantic search
B. Customer service improvement through text and audio assessment Text/audio synthesis, analysis

© 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved.
GenAI Patterns
Productivity
Text generation
Chat
Virtual assistant
Summarization
Text extraction
Search
Code
generation
Image
generation
Object Creation
Image
classification
Create
music
Generate
videos
7

Data is still the currency for
fundamentals of Gen AI
8

9
The Data-Driven Organization
Set ‘Think Big’ goals Focus on delivering business
priorities fast
Shared leadership
conviction and
Business-IT alignment
on data ownership
Strong collaboration and
agility concerning data
products across data
producers and consumers
Upskilled and
empowered producers
and consumers who
self-serve
Privacy, security, compliance
and federated governance
without impeding innovation
Key Characteristics
“An organization that harnesses data as an asset,
to drive sustained innovation and create
actionable insights to supercharge the experience
for their customers so they demand more.”

Data-driven organizations
are growing an average of
30%+ annually
68% of organizations
reported they’re still unable
to realize value from data
Only 28% of survey
respondents have a data
strategy in place
Accenture, “Closing the Data-value Gap”
https://accntu.re/33V6sU3
Accenture, “Closing the Data-value Gap,”
https://accntu.re/33V6sU3
Forrester, “Insights-Driven Businesses Set
the Pace for Global Growth”
https://bit.ly/3r4uRiL
Data is imperative, but there is a gap

`
Learn from more than 1.5 million AWS customers use database,
analytics, or machine learning services

Partner with AWS to drive cost savings and innovation
Move to
Managed
Services
Modernize
your data
architecture
Adopt
Serverless
Frameworks
BI Tool
Optimization

Self-managed databases can slow your Business
Long release cycles
for new products
and features
Operational
inefficiencies resulting
in overhead costs
Inability to support
changing compliance,
security regulations
Lost revenue due to
missed opportunity,
loss of competitive
edge
Lost productivity or
high costs for
undifferentiated
skills
Non-compliance and
priority disruptions to
resolve compliance or
security issues

Samsung
Challenge
The Oracle database was expensive and difficult to maintain. Simple tasks
required manual maintenance.
Solution
By migrating from Oracle to Amazon Aurora, Samsung achieved cost
savings and decreased operational tasks,
all without service disruption during the migration.
Result
“Our Oracle online migration in EU IDC to Amazon Aurora with
PostgreSQL Compatibility completed in 22 weeks without service
disruption. This success is unprecedented in Korea. The biggest win for us
is cost savings, but we also have decreased our operational tasks, thanks
to Aurora.”
- Go Byeong-ryul, Database Architect, Samsung Electronics
Amazon Aurora with
PostgreSQL compatibility

AWS has the right database for the right job
Aurora
RDS
DynamoDB DocumentDB Timestream
Neptune
ElastiCache QLDB Keyspaces
Relational
Referential
integrity, ACID
transactions,
schema-
on-write
Key-value
High
throughput,
Low latency
reads and writes,
endless scale
Document
Store documents
and quickly
access querying
on any attribute
In-memory
Query by key
with
microsecond
latency
Graph Time-series
Collect, store,
and process
data sequenced
by time
Ledger
Scalable, highly
available, and
managed Apache
Cassandra-
compatible service
Quickly and easily
create and
navigate
relationships
between data
Wide Column
Complete,
immutable, and
verifiable history
of all changes to
application data
Lift and shift,
ERP, CRM,
finance
Content
management,
personalization,
mobile
Leaderboards,
real-time
analytics,
caching
Fraud detection,
social
networking,
recommendation
engine
IoT
applications,
event tracking
Systems
of record,
supply chain,
health care,
registrations,
financial
AWS
Service(s)
Common
Use Cases
Build low-latency
applications,
leverage open
source, migrate
Cassandra to the
cloud
Real-time
bidding,
shopping cart,
payments,
product catalog,
customer
preferences

Capital One completed migration from data
centers to AWS in 2020, becoming the first
US bank to go all in on the cloud.
Transformed credit line technology on AWS
leveraging DynamoDB, RDS, Aurora and
other services
• Shifted mindset from designing for the
data center to cloud‐native design
• Upskilled teams to engineer for
resilience and inner-sourcing
• Delivered wins with consistent UX,
faster time to market, and increased
business income
We are able to manage data at a much larger scale
and unlock the power of machine learning to deliver
enhanced customer experiences.
—Chris Sims
Senior VP, Cloud and Productivity Engineering
“ “

Modern Data Architecture
From traditional . . . . . . to microservices, decoupled architectures
Web servers
Presentation layers
Application servers
Business logic
Database servers
Data layer
Events
Queues + Caches + Messages
Events
Presentation
Business
logic
Data

As organizations accelerate delivery of high-quality data applications, many are taking advantage of serverless services to
remove undifferentiated heavy lifting with no infrastructure to manage, scale automatically, and have high availability
Move from idea to
deployment, faster
Eliminate operational overhead
so your teams can release quickly,
get feedback, and iterate to get
to deployment faster
Time to deploy improvements:
89% for new compute,
96% for new storage*
Lower your costs
With a pay-for-value billing
model, resource utilization is
automatically optimized, and you
never pay for over-provisioning
409% 5-year ROI*
Adapt at scale
With technologies that automatically
scale from zero to peak demands,
you can adapt to business and
customer needs faster than ever
71% fewer unplanned outages*
Build better
applications, easier
Serverless applications have
built-in service integrations, so you
can focus on building your
application instead of configuring it
80% more efficient
IT infrastructure teams*
Build and Innovate with Serverless
SERVERLESS DATA SERVICES
Amazon
OpenSearch
Amazon
Athena
Amazon
Redshift
AWS Glue Amazon EMR
Amazon
Kinesis
Amazon MSK
Amazon
Quicksight
Amazon
Aurora
Amazon
DynamoDB
Amazon
Keyspaces
(for Apache
Cassandra)
Amazon
Timestream
Amazon
Neptune

Modernizing leads to maximum innovation velocity and
optimal total cost of ownership
On-premises Lift
and shift
Move to managed
databases
Modernize with
purpose-built
databases
Innovation
velocity
Total
cost of
ownership
(TCO)
Break-free from
legacy databases

A P P S
D E V I C E S
P E O P L E
A P P / L O G S
T H I R D - P A R T Y D A T A
I O T / D E V I C E S
Data sources
Modernize your data architecture
Catalog & govern | AWS Lake Formation, Amazon DataZone
Amazon
Redshift
Amazon
EMR
B U S I N E S S
I N T E L L I G E N C E
Amazon
QuickSight
M A C H I N E
L E A R N I N G
Amazon
SageMaker
A N A L Y T I C S
F O R
A P P L I C A T I O N S
Amazon
Aurora
Amazon Kinesis
& Amazon MSK
F O R A N A L Y T I C S &
M A C H I N E L E A R N I N G
Data Lake
Amazon S3
Amazon Redshift
Data Warehouse
Amazon
DynamoDB
AWS Glue

Amazon S3
data lake storage
LOB 1
Amazon
Redshift
Amazon
EMR
Amazon
Athena
Consumer 1
Amazon S3
data lake storage
LOB N
Amazon
Redshift
Amazon
EMR SageMaker
Consumer N
Amazon S3
data lake storage
LOB 2
BI Reports
Amazon
EMR Notebook
Consumer 2
Data organizations also talk about data mesh
A decentralized, light-weight federated governance across domain-oriented data systems to
drive governed sharing
….
Unified Policy Management
Enhanced
Governance
Federated Governance
Blueprints Resource
Share
Centralized
Data Catalog
Federated Access Control
Organization wide Sharing
Centralized Governance & Audit
….

Drive data governance with Amazon DataZone
U N L O C K T H E P O W E R O F A L L D A T A F O R A L L U S E R S W I T H T R U S T E D A U T O N O M Y
23
Team who runs the
data marketplace
Teams who want to share data Teams who want to use data
Amazon DataZone
Data producers Data consumers

Amazon DataZone pillars
D I S C O V E R , S H A R E , A N D G O V E R N D A T A A T S C A L E A C R O S S O R G A N I Z A T I O N A L B O U N D A R I E S
Governed data sharing
Automate workflows to facilitate
sharing of data more securely
between producers and consumers
to make sure that the right data is
accessed by the right users
for the right purpose
Efficiently audit who is using
which datasets for what business
use case, and monitor usage and
costs across projects and lines of
business (LOBs).
Simplified access to
analytics
Create business use case–based
data projects to group teams,
tools, and data
Work with the tool of your
choice seamlessly without the
undifferentiated heavy lifting
needed when switching
between services
Self-service portal
Experience an integrated data
environment to promote
exploration and
drive innovation with a
personalized homepage
Facilitate streamlined cross-
functional collaboration while
working with data and tools in a
self-service fashion
Enterprise-wide
business data catalog
Make data visible with context
for all your users to find and
understand data quickly and
more easily
Catalog any data type across the
organization, in the cloud,
on premises, or in SaaS
applications with rich metadata
and business context

Optimize your BI / reporting solution
Legacy
Reports
PRODUCT A
• Unified serverless BI at hyperscale
• Unparalleled ease of use – no technical training required
• Same UI, new features every 2-4 weeks
• Eliminate costly licenses, pay-as-you-go
• Silos of BI environments
• Specialized training, staff for each
• Different UI for each platform
• Separate costly licenses and maintenance
Dashboards
PRODUCT B PRODUCT C
Embedded
Analytics
NLQ
PRODUCT D
Natural
Language
Queries
Dashboards Reports Embedded
Analytics

Sustainability drives business growth
Tomorrow’s strongest-performing businesses are likely
to be the “Twin Transformers”—companies that find
new value at the intersection of digital technologies
and sustainability.
Powered by these twin engines of growth, they’re
2.5x more likely to outperform their peers.
-Accenture, April 2021

© 2021, Amazon Web Services, Inc. or its Affiliates.
ENGIE builds the Common Data
Hub on AWS, accelerates
zero-carbon transition
Challenge
ENGIE’s decentralized global customer base had accumulated lots of data,
and it required a smarter, unique approach and solution to align its initiatives
and to efficiently provide data across its global business units.
Solution
ENGIE built its Common Data Hub data lake on AWS, enabling the company’s
business units to collect and analyze data to support a data-driven strategy
and to lead the zero-carbon transition.
Result
• Collected 95 TB of data across 351 projects
• Automated energy predictions
• Maximized wind farm energy production
Benefits
Since implementing the CDH, ENGIE’s renewable fleet of wind farms, solar
farms and hydroelectric dams is significantly more efficient. If you improve
the availability and performance of an asset that's worth $100 million or
$500 million by just 1% because you tap into the right data— well, I’ll let
you do the math.
Yves Le Gélard CDO and CIO.
Amazon Redshift
Amazon Kinesis Data Streams Amazon S3 Amazon SageMaker
AWS Glue Amazon Athena

© 2023, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential. |
Need peer-level
guidance?
✓ Discuss mental models and strategies
based on experience and learnings
working with AWS customers
✓ Get peer-level sounding board
Jumpstart the development
of your modern data strategy
Need a strategy and
help executing it?
✓ Align business and technical leaders
on data related use cases and
initiatives to support business goals
✓ Align on priorities and where to start
activating the modern data strategy
✓ Leave with an actionable delivery
plan and architecture to activate an
initial business driven use case in 90
days
Come with an idea,
leave with a modern data
strategy and a solution
Need to align executive
stakeholders?
✓ Begin to align on what a modern
data strategy is and why it’s
important
✓ Dive deeper into the non-technical
and technical concerns of a modern
data strategy
Inspire and accelerate your
data driven transformation
Next steps on your data journey

[Keynote] Data Driven Organizations with AWS Data - 발표자: Agnes Panosian, Head of APJ Data Sales, WWSO, AWS ::: AWS Data Roadshow 2023

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[Keynote] Data Driven Organizations with AWS Data - 발표자: Agnes Panosian, Head of APJ Data Sales, WWSO, AWS ::: AWS Data Roadshow 2023