Matt Moore Sr Manager Technology Partnerships Data and AI Category APJ AWS

1. © 2023, Amazon Web Services, Inc. or its affiliates.
© 2023, Amazon Web Services, Inc. or its affiliates.
Matt Moore
Sr Manager Technology Partnerships
Data and AI Category APJ
AWS
Single View of Data
#DataInMotionTour

2. © 2023, Amazon Web Services, Inc. or its affiliates.
© 2023, Amazon Web Services, Inc. or its affiliates.
Agenda
2
❑ Know and Apply your data?
❑ Democratise your data
❑ Challenges
❑ Value outcomes
❑ Where is the leading edge?

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Know and Apply your data?
All Data In A Single Platform
• Complete, accurate and consistent view of all data that a
business collects, stores and processes
• Comprehensive insights to all stakeholders across the
organisation
• Gain understanding of data that may have been missed or
ignored previously
Encapsulate Your Total Environment
• Define data standards
• Integrate data sources
• Clean and transform data
• Enable access
Project Your Outcomes
• Improved decision making
• Increased efficiency
• Enhanced data quality
• Better customer service
3

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Democratise your data
Ethos
• Create a data culture
• Provide training
• Empower users
• Implement data governance
Business outcomes
• Greater business agility
• Improved collaboration
• Increased innovation
• Better decision making
4

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Challenges
Data silos
• Disparate data
Data quality
• Known and unknown
• Don’t apply it everywhere
Resistance to change
• Culture
• People
Security and privacy
• Infrastructure
• People
5

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Value outcomes
• Essential for staying relevant
• Competitive advantage
• Improve cross team functionality
• Faster and better innovation
• Time to value
• Speed of decision making
6

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Where is the leading edge?
=
• Prompt Engineering
(ChatGPT)
• Anthropic AI
• AI Co-pilots
• AI Workflows
• Chatbots
• Take a look at Poe in the
app store on IOS
• With AI, the best idea will
win over market capacity
and $$
• Are we going to run out of
Data?
7
“Data and AI
addressable market
for APJ is $934B”
- Gallop 2023
High quality data will
run out by 2026
- Epoch

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Confluent + AWS: Accelerate Customer Business Outcomes
Topline Impacting New
Experiences
● Event-driven & real-time
● Unify data across org. w/ Kafka
data fabric (Schema Reg,..)
● AWS Analytics, Redshift, ML
connectors
Mitigate Risk
● Higher Service Quality &
Resilience with 99.99% SLA
● Deep Kafka expertise & innovation
● Elastic billing/pricing
Developer Agility
● Focus on innovation (not data
infrastructure)
● Leverage full Kafka OSS
ecosystem + AWS services
Faster Time to Market
● ~50-75% faster time to market*
● Streamline hybrid cloud migration
with no complex lift-n-shift
● Maintain business continuity
Lower Kafka TCO
● ~25-50% lower TCO *
● GBps-scale & fast deployments
for global expansion
● Deploy Kafka at scale in 1 week
Maximize ROI
● ~200% ROI per Forrester study
● Save 10s of $Ms with legacy
offload to AWS with Confluent
Replicator
* For customers that don’t already have Kafka based system in-market
* TCO assessment to be analyzed for specific customer scenarios

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Rich front-end
customer
experiences
Real-time
Event Streams and Analysis
A Sale A shipment
A Trade
A Customer
Experience
Real-time backend
operations
Event streaming with Kafka to set Data in Motion:
Continuously processing evolving streams of data in real time with
Confluent

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Amazon Redshift Warehousing with Confluent Cloud
Serverless with AWS and Confluent Cloud
Real-time Sentiment Analysis with Confluent
Amazon ElastiCache and Confluent Cloud
confluent.awsworkshop.io
Try it out yourself

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Free trial available through the
AWS Marketplace
$400 in free credits to spend
during your first 30 days

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© 2023, Amazon Web Services, Inc. or its affiliates.
Thank you!
Matt Moore
mattym@amazon.com

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© 2023, Amazon Web Services, Inc. or its affiliates.
Appendix
13

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Apache Kafka anatomy 101
kafka
ZooKeeper

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Confluent – AWS Partner
15
AWS SaaS
Rev-Rec Program
Co-sales
80+ ACE co-sell deals / $20M Confluent TCV
40+ MP private offer deals / $12M TCV
450+ co-sell deal registrations in ACE
Confluent launch blog / AWS launch blog
Serverless streaming & Analytics
AWS joint blog
Customer References
58+PB/month
into S3
Top 5 S3 ISV
-not to share with public, for speaker reference only

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Derive insights from data in real-time
Ingest & Process
Capture event streams with a consistent data structure using
Schema Registry, develop real-time ETL pipelines with a lightweight
SQL syntax using ksqlDB & unify real-time streams with batch
processing using +100 Confluent Connectors
Mobile
Web
IoT
Data store
AWS & On-prem
Amazon
S3
S3 Sink
ANALYZE
Amazon
Redshift
AWS Lake
Formation
Amazon
Athena
Redshift Sink
TRANSFORM
Amazon
EMR
AWS Data
Pipeline
AWS
Glue
Source
connectors
Store & Analyze
Stream data with Confluent pre-built Connectors into your
AWS data lake or data warehouse to execute queries on vast
amounts of streaming data for real-time and batch analytics
VISUALIZE
Amazon
Elasticsearch
Schema
Registry
ksqlDB
Events

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Modern data strategy journey
Innovate
by inventing new experiences and
reimagining existing processes
Modernize
data infrastructure to a scalable,
trusted, and secure cloud provider
Unify
data by breaking down silos

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Federated Query
Amazon Redshift Spectrum
query Amazon S3
Data lake export
Operational
databases
Query live data and
maintain materialized views
BI and analytics apps
Connect apps to analyze and visualize your data
Amazon S3 data lake
Keep up to exabytes of data in Amazon S3
SQ
L
Amazon
Redshift ML
Amazon
Redshift
Materialized views
Data sharing
Data marketplaces
for third-party data
ML and
analytics services
Analyze open standards-
based data formats
No
ETL!
No data
movement
Secure and consistent
data sharing
Billions of predictions right
within your data warehouse
No data
duplication
ML in
SQL
Use your favorite
BI tool
1,300+ third-party
datasets, 350+ data providers
Break thru data silos, analyze data across AWS services

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What is a data mesh pattern?
• Decentralized
• Domains ownership
• Data as a product
• Self-service data platform
• Federated governance
AWS Control Tower

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Producer/Consumer Producer/Consumer
Producer/Consumer Producer/Consumer
Data mesh
Lake
Formation
Data
Catalog
AWS Data
Exchange
Data mesh pattern on AWS