Andrew McIntyre, Director of Strategic ISV Alliances, ‎Informatica Modernizing your analytics capabilities to deliver rapid new insights is critical to successfully drive data-driven digital transformation. Many organizations find it challenging to connect, understand and deliver the right data to generate new insights. Learn about the latest patterns, solutions and benefits of Informatica's next-generation Enterprise Data Management platform to unleash the power of your data through the modern cloud data infrastructure of AWS. See how you can accelerate AI-driven next-generation analytics by cataloging and integrating structured and unstructured data from hundreds of data sources from multiple on-premises and cloud data sources.

1. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Andrew McIntyre
Director of Strategic Alliances, Informatica
Accelerate Digital Transformation
through AI-powered Cloud Analytics
Modernization with Informatica

2. New
technology architecture
New users
and influencers
New
consumption
models
New ecosystems
Four
Challenges

3. 3
Data explosion beyond data warehouse
No clear view of data relationships and semantic meaning of data
The Challenges with Changing Data Landscape….
Organizations are unable to maximize business
value from their data assets
Growing number of users using self-service analytics

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58% of companies have a hybrid strategy with
footprints on both cloud and on-premises
Sources: Rightscale Cloud Computing Trends: 2018 State of the
Cloud Survey – February 2018, BetterCloud Monitor: The 2017 State
of the SaaS-Powered Workplace Report
Companies use 16 SaaS apps on average today

5. Informatica
Accelerates Your
Data-driven Digital
Transformation

6. Enterprise
Cloud Data
Management
1#

7. These graphics were published by Gartner, Inc. as part of larger research documents and should be evaluated in the context of the entire document. The Gartner documents are available upon request from Informatica.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner
research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research,
including any warranties of merchantability or fitness for a particular purpose.
Gartner MQ for
Enterprise iPaaS
March 2017
Gartner MQ for
MDM Solutions
Oct 2017
Gartner MQ for
Data Quality Tools
Oct 2017
Gartner MQ for Metadata
Management Solutions
Aug 2017
Gartner MQ for Data
Integration Tools
Aug 2017
The Leader in Five Gartner Magic Quadrants

8. Informatica Intelligent Cloud Services
Connecting 100,000 applications,
databases and other end points
2 Trillion
Transactions a month
>300%
Growth of
API volume
3M+
Integrations/day
200%+ growth YoY
8,000+
Customers
150+
iPaaS Connectors
>50%
Annual revenue
growth
Volumes of data
2x
Every 6 months

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A future-proof data foundation for your enterprise
Any Integration Pattern
Data, Steaming,
Applications, APIs, &
Processes
Any User
For IT & Business Users
Any Data
Cloud, On-premises, IoT, Big
Data
Enterprise Unified Metadata Intelligence
A Single, Modular , Hybrid, Secure and Trusted, Platform

10. Cloud/Hybrid
360
Engagement
Data
Governance
Next Generation
Analytics
One Data Management Partner
Many Journeys

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Cloud Apps (SaaS)Data Stores
DBs, DWs, Big Data, Cloud
Enterprise Systems B2B
Middleware and Tech
Analytics
Social Apps
Any Data - Broadest connectivity across cloud and on-
premises

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Informatica Support Key AWS Services
DynamoDB S3Aurora RedshiftEMR Kinesis QuickSight

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Informatica for AWS
Migration

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Typical use cases on cloud journey
Cloud Data
Warehousing
AWS
Redshift
1 Cloud Application
Integration
2 Self-Service
Analytics
Amazon Web
Services QuickSight
3
Cloud Data
Lake
AWS
EC2 & EMR
Amazon Web
Services S3
4 Hybrid Data
Management
5 Cloud
Migration
SaaS PaaS IaaS
All ecosystem vendors across Cloud DW, Cloud Application Integration,
Cloud Data Lake/Big Data use cases
6

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Four Most Common Cloud Journey Types
RE-HOST
RE-PLATFORM
RE-ARCHITECT
RE-BUY

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Key Challenge – What Data to Modernize First?
Typical Large Enterprise
10000 – 50000 Database Schemas
1000 – 5000 Applications
10M – 100M Columns
1 – 5 Hadoop Data Lakes
Multi-vendor IT
Exponentially expanding data
volumes

17. 17
• Help organizations to democratize data
 Enable governed self-service analytics
 Take inventory of all data assets
 Explore and understand data assets and data beyond data warehouses
• Discover data assets and relationships to make sense of data
 Technical and business metadata
 Data lineage, impact analysis
 Data relationships
• Manage data as a strategic asset
Maximize the Value of Data Assets with a Data Catalog

18. 18
Enterprise Data Catalog
Powered by CLAIRE engine
• Easily find and discover trusted data
• Explore holistic data relationships
• End-to-End data lineage & impact analysis
• Automatically catalog and classify data assets
• Curate data assets – governed or crowdsourced
data assets
• Machine-learning-based
semantic inference and recommendations
• Enhance Classification with entity recognition
• Broad Connectivity, Big Data Scale
Artificial-Intelligence based data discovery and visibility
to all data assets across the enterprise

19. 19
Machine Curated Catalog
Auto-Scan
Source Metadata
Profiling and Domain DiscoveryMachine Learning
Curated Catalog
Business Glossary AssociationsCrowd Sourced AnnotationsGoverned Curation
Enterprise Data Catalog
Applications &
Databases
Internet of Things
3rd Party Data
Data Modeling
Tools
BI Tools CustomCloud
Enterprise Data Catalog
Data
Relationships
Data
Profile
Data
Lineage
Data
Classification
Data
Discovery

20. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Informatica for AWS
Data Warehouse Modernization

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Cloud Data Warehouse / Analytics
Modernization
Migrate Extend Born in the Cloud
• Agile self-service analytics
• Highly scalable & elastic
• Quickly scale
• Variety & volumes
of data for analysis
• Improve performance
• Reduce costs

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Informatica for Redshift Data Warehouse
Modernization
Data
Quality
Master Data Management

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Fast Data Ingestion into Amazon Redshift
Amazon
Redshift
Batch Read Source Data
Number of Local
Staging Files =
multiple of RedShift
Slices
Files
encrypted
compressed
S3 VPC Endpoint
for performance
Parallel or
Multipart Upload
S3
Bucket
Key Range Partition
Source Key = Distribution Key
No of partitions = no of Redshift
slices
Optimized Copy
Command
Redshift Slices

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Informatica for AWS
Next-Generation Data Lakes on AWS

25. 27 © Informatica. Proprietary and Confidential.
Data Lake on AWS
• Immediate Availability. Deploy instantly. No hardware to procure, no
infrastructure to maintain & scale
• Broad & Deep Capabilities. Over 70 services and 100s of features to support
virtually any big data application & workload
• Trusted & Secure. Designed to meet the strictest requirements. Continuously
audited, including certifications such as ISO 27001, FedRAMP, DoD CSM, and
PCI DSS.
• Hundreds of Partners & Solutions. Get help from a consulting partner or
choose from hundreds of tools and applications across the entire data
management stack.

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Building a Data Lake on AWS

27. 29 © Informatica. Proprietary and Confidential.
Building a Data Lake on AWS with Informatica

28. 30 © Informatica. Proprietary and Confidential.
AIntelligent Data
Lake Management
STREAM
INTEGRAT
E
ENRICH PREPARE CATALOG RELATE PROTECT DELIVERINGEST DEFINE
Orchestrate
data flows
and provision
data to the
enterprise
Prepare data
for analytics
& collaborate
on projects
Streaming
analytics &
event
processing
Integrate all
types of data
of any volume
at scale
Cleanse and
enrich trusted
data
Define and
verify data
governance
policies
Discover,
catalog,and
curate all
enterprise data
Match
and relate
identities
& entities
at scale
Data security
intelligence to
Detect &
protect
sensitive data
Multi-latency
data ingestion
& edge
computing
CATALOG SEARCH LINEAGE RECOMMENDATIONSPARSE MATCH
Informatica’s Enterprise-Class Cloud Data Management Solution for Big Data
Amazon
S3
Amazon
Redshift
Amazon
EMR

29. 31 © Informatica. Proprietary and Confidential.
Informatica Big Data Management Reference
Architecture for Amazon Data Lakes
Ingest
3rd Party Data
On-Prem
Data Center
Database &
Application Servers
Social & Web Logs
Landing
Zone
Raw Data
Amazon S3
Buckets
Data Curation
Amazon EMR
Compute
Cluster
Temporary S3 Storage
Enterprise
Zone
Hive on S3
Buckets
Discovery
Zone
Hive on S3
Buckets
Delivery
Amazon
Redshift
Amazon
RDS
Amazon
DynamoDB
On-Premises
Data Warehouse or
Master Data Management Hub
VPN
Gateway
customer
gateway
VPN
connection
VPN
Gateway
customer
gateway
VPN
connection
Analytic/BI
Tools

30. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Informatica for AWS
Getting Started

31. 33 © Informatica. Proprietary and Confidential.
Informatica Data Lake Solution for AWS Quick
Start
Find out more:
https://www.informatica.com/solutions/explore-
ecosystems/aws/aws-data-lakes
High-performance codeless
integration of multiple hybrid
clouds, on-premises systems
and AWS
Accelerate enterprise data lake
management deployment to
power next generation analytics
Catalog, understand and
manage data assets across
hybrid clouds and on-premises
systems
Rapid Deployment with
AWS Quick Start

32. 34
Learn more
Learn & Prepare
• Data Lake Management on
AWS
• Cloud Analytics with
Informatica Intelligent Cloud
Services & Amazon Redshift
• PowerCenter on AWS
Deep Dive Get Started
www.informatica.com/AWS
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