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.
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
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
9. 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
12. 12
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
Redshift
17. 17
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
18. 18
• Help organizations to democratize data
ü Enable governed self-service analytics
ü Take inventory of all data assets
ü Explore and understand data assets and data beyond data warehouses
• Discover data assets and relationships to make sense of data
ü Technical and business metadata
ü Data lineage, impact analysis
ü Data relationships
• Manage data as a strategic asset
Maximize the Value of Data Assets with a Data Catalog
19. 19
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
20. 20
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
24. 24
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
33. 33
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
AWS Marketplace & Quick StartsReference Architecture GuidesWhitepapers & Workbooks