Retail banks are moving beyond the data warehouse and data lake and are now implementing data fabric architectures to address data discovery and integration challenges. These are the slides from our webinar "Modern Data Discovery and Integration in Retail Banking" in which we explore the role of the data discovery and integration layer in a data fabric with special focus on evolution from data warehouse to data fabric, semantics and graph data models in data fabric and example use cases in retail banks and B2C financial services.

1. Modern Data Discovery and
Integration in Retail Banking
BARBARA PETROCELLI, VP STRATEGY
GREG WEST, SENIOR PRE SALES ENGINEER

2. • Data Fabric Defined
• Modern Data Discover and Integration
• Intro to Anzo
• Integration View of Auto Loan Customer
• Getting Started
Agenda

3. ©2018 Cambridge Semantics Inc. All rights reserved.
FASTER TIME
TO ANSWER
LOWER DATA
DELIVER COSTS
AGILE SCALEABLE
DATA PROVISIONING
What’s a data fabric (and why do I want one)?
Modern enterprise data management architecture and
technology stack for data preparation and provisioning.
To makes much more enterprise data available to the
business faster and in various formats to fuel analytics and
meet the demands of digital transformation

4. RDBMS/OLTP Big Data / Hadoop Document Repositories
Traditional BI Cloud
ACCOUNT
TRADE
ASSET
CUSTOMER
The Financial Data Fabric

5. ©2018 Cambridge Semantics Inc. All rights reserved.
Data Discovery and Integration in Data Fabric Catalogs,
Connects, Enriches, Blends, and Exposes Enterprise Data
Accounts
CRM
Loan
Marketing
AML
Fraud Detection
Personalization
Recommendation
KYC/Customer 360
Regulatory Reporting
Data Discovery
and Integration
LINE OF BUSINESS
ANALYTIC USE CASES
ENTERPRISE
DATA LANDSCAPE
3rd party
Investment
Digital Assistants
Digital Risk/Underwriting

6. A modern data discovery and integration platform
for your enterprise data fabric.
Anzo lets business users find, connect, and blend
enterprise data into analytic ready datasets.
Map and Explore
Enterprise Data
Build Blended
Analytic-Ready
Datasets
Apply Enterprise-Ready
Data Management

7. 4 Step User Experience
Catalog and map your
existing data assets –
structured or unstructured.
Translate dataset into graph
models. Add business
definitions, object types, and
relationships with semantics.
Create blended analytic
ready datasets. Connect
graph models. Transform
data. Harmonize into
canonical models.
Analyze data using semantic
and graph models. Export
data for use with BI,
analytics, and machine
learning tools.
ON-BOARD MODEL BLEND ACCESS

8. Automated Deployment and Operations
Storage and Compute Integration
MODEL
Graph Data Model
• Lift Data into
Data Fabric
• Design Ontologies
• Connect Data
Models
ON-BOARD
Ingest & Map
• Automated ETL
• Collaborative
Mapping
• Metadata
Capture
Enterprise
Data Sources
Machine
Learning and AI
Enterprise
Search
“Last Mile”
Analytics Tools
Metadata Catalog
Semantic-based Metadata Management, Governance and Lineage
Cloud or On-Prem Data Storage Infrastructure
Data Storage Layer
Ingest
BLEND
GraphMarts
• Combine and Align
Related Data Sets
• In-memory MPP
Query Engine
• Data Layers
ACCESS
Hi-Res Analytics
• Analyze All
Data Together
• Fast, Iterative Queries
Ad Hoc, What if
• Code Free or API
Graphical Application Interface

9. Anzo Difference:
Graph Data Models & Semantics
Simplifies access to complex data to address unanticipated questions
Quickly profiles, connects and harmonizes data from multiple
sources, including unstructured
Presents tailored views and experiences to different personas
with conceptual models
Flexibly accommodates new data sources and use cases on the fly,
with minimal impact
Scales horizontally to accommodate enterprise data fabric scale

10. ©2018 Cambridge Semantics Inc. All rights
DEMO
Key Concepts:
● Onboarded and modeled data
for an automobile manufacturer
and financer
● Shows blended entities from 3
different source systems
● Allows business users to access
their data and ask unanticipated
questions
Finance Dept
Manufacturing
Dept
Sales Dept

11. Begin your journey.
Identify your
initial use case
Define the
IT/business
partnership
Quick start
deployment
4 - 8 weeks
Leverage
CSI technical
expertise /staff

12. ©2018 Cambridge Semantics Inc. All rights reserved.
THANK YOU
barbara.petrocelli@cambridgesemantics.com – 516-313-0263
greg@cambridgesemantics.com – 330-707-0107
Watch the Webinar On-demand