With consumer and business buyer expectations growing exponentially, more businesses are competing on the basis of customer experience. But executing preferred customer experiences requires data about who your customers are today and what will they likely need in the future. Every business can benefit from an AI-powered master data management platform to supply this information to line-of-business owners so they can execute great experiences at scale. This same need is true from an internal business process perspective as well. For example, many businesses require better data management practices to deliver preferred employee experiences. Informatica provides an MDM platform to solve for these examples and more.
2. 2 Š Informatica. Proprietary and Confidential.2
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
3. 3 Š Informatica. Proprietary and Confidential.3
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
4. 4 Š Informatica. Proprietary and Confidential.
The Questions Customer 360 Solves
Compliance / CFO/
Financial Analyst
How do I secure my
data and comply with
regulations?
How do I mitigate risk
and measure risk
concentration?
Sales, Marketing,
Service, eCommerce
How do I improve
customer experience?
How do I accelerate
product introduction?
How can I trust my
supply chain
integrity?
How can I streamline
curation of a trusted
360 view of data?
How confident can I
be in the quality of
the data we use?
Data Steward
How can I find hidden
relationships in data?
How can I spend more
time on analytics?
How can I more easily
ask & answer complex
questions?
Data Scientist
How do I ensure the
data we use is
trusted and relevant?
How can I deploy
software more
quickly?
Developer
5. 5 Š Informatica. Proprietary and Confidential.5
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
6. Š Informatica. Proprietary and Confidential.
⢠An international not-for-profit health system delivering
care from more than 400 hospitals, long-term care
facilities, clinics, and outpatient centers.
⢠Needed to manage increasing volume of patient and
operational data while improving productivity and
delivering the next generation of patient care.
⢠Created enterprise data platform to deliver immediate,
complete patient information to health professionals.
⢠Decreased length of stay and emergency wait times;
saved $500,000 in just two months; delivered a better
quality, more personalized patient experience.
Improving Delivery of Quality Patient Care
8. Š Informatica. Proprietary and Confidential.
⢠A premier global hospitality company.
⢠Compete more effectively in highly competitive
market through exceptionally personalized guest
experiences.
⢠Powers Guest Experience Management system with
360Âş views of guests behaviors and preferences.
⢠Experienced double digit growth from loyalty
customers, 19% y/y revenue increase from
promotional offers, and a 50% reduction in
promotional spend.
Irrational Emotional Bond
9. 9 Š Informatica. Proprietary and Confidential.
The Customer Data Management Solution
Informatica PowerCenter Informatica PowerCenter Real-Time
Offers
Enterprise Data
Warehouse
Predictive
Scoring &
Analytics
All
Channels
All
Channels
All
Channels
List
Pulls
Real Time
Marketing
Customer
Profile
Field
Marketing
Field
Marketing
Field
Marketing
Field
Marketing
Email
Marketing
(Cheetah)
Ids, groupings Metrics
Customer Info
Transactions
Mgmt
Reports
Over 10,000 files received
Customer Info
Transactions
Real-Time
CDI
Transactions
Customer Hub
(INFA MDM)
Campaign
Mgmt
(SAS)Response
Tracking
IDQ
Hyatt.com/Reservations
Property Systems
Property Systems
Digital Marketing
Hyatt.com/Reservations
11. 11
Informatica MDM Center of Excellence
Relationship with Informatica
Peoples and Experience
Solution Development
Domains and Entities
Informatica
MDM CoE
ď§ Top premier Global SI partner since 2005
ď§ Winner of the Best SI Partner for Informatica
for 2012, 2013,2014 ,2015 & 2016
ď§ Global System Integrator of the Year 2015
ď§ Winner of Informatica (Siperian) Gooey
Award (2008)
ď§ Informaticaâs Beta test partner with early
access to Informatica MDM future releases
ď§ Winner of 3 Innovation Awards
ď§ 450 + resources with experience on MDM Hub across North America, UK, Central Europe & India
ď§ 90+ associates certified by Informatica University & 300+ Associates with Cognizant certification
ď§ 80+ implementations with 30 global rollouts and 5 multi entity projects
ď§ âMDM-in-a-Boxâ - a pre-fabricated Cognizant solution for different
business domains like Retail ,Consumer Goods, Life Sciences etc.
ď§ Insurance 360 for Insurance industry
ď§ Clinical MDM for Pharmaceutical companies
ď§ Financial Reference Data Management Solution
ď§ IDMP solution for Life Sciences
ď§ Key Domains: Retail, Consumer Goods, Life Sciences, Technology, Healthcare, Logistics, Banking & Financial Services, Insurance
ď§ Key entities: Customer, Vendor, Product, Policy, Location, Account, Reference Data, etc.
12. Global Roll out of Customer Master
@Global Water Technology Provider
12
Key Highlights
Business Drivers
ď§ There are multiple regions, ERP/siloâd systems, and Languages which add complexity to the Master Data Management paradigm
ď§ Master data is scattered in silos, with scope of improvement in data quality
ď§ No presence of data governance across the globe
ď§ Data discrepancies need to managed and governed properly in order the ensure the success of P2P and O2C process implementation
with Emagia and Catalyst application implementation
Consistent customer
information across
the globe
Integration of MDM
with other
applications (e.g.,
analytics)
Improved data quality
and enrichment by 3rd
parties
Global governance
framework leveraging
people, processes,
standards and MDM/DQ
Solution Highlights
ď§ Global implementation for 2 business partner domains (Supplier & Customer) for 10 + Source systems ( with multiple instances)
with multiple languages in scope
ď§ The phased implementation consisted of a foundation phase for AS IS analysis, Business Requirements & DQ Analysis & Design
and 3 waves for 3 regional rollouts
ď§ The solution involved data quality mgmt., Address Doctor & Multiple third party integration (D&B, Amber Road, Decision Point) in
real time/batch mode for data enrichment for hierarchy, denied party identification etc.
ď§ Data Governance Strategy including a global organization structure, R&R & processes
Business Outcome
ď§ Integration of MDM with Catalyst & Emagia, the primary applications for P2P and O2C Process Mgmt. for managing data
discrepancies like Data duplication, Data redundancy, Exceptions, Data Standardization
ď§ Improved Cross-sell/Up-sell
ď§ Technology Stack: Informatica Multi-domain MDM on AWS Cloud, Power Center, IDQ
13. High Level Solution Architecture â Customer MDM
@Global Water Technology Provider
SFTP
(input)
SFTP
(Golden
Record
output)
Trust Framework
De-Duplication
Survivorship
List Of ValuesAudit Trails
Data Enrichment
Address
Standardization
Name
Standardization
Cleansing and
standardization
Active Directory based Access Control
Informatica
Analyst
Admin
Hub
Console
Provisioning
Tool
Business
Entity UI
Data analysis &
profiling
MDM
Configuration
UI
Configuration
Customer Data Enrichment &
Workflows
User Admin &
Security
Customer
Onboarding Approval
Decision
point
Deniedparty
Hierarchy
OrchestrationLayer
SRC_ID update from ERP
SRC_IDupdatefromERP
Approvals &
Credit
Application
Customer Master
Input
Customer Golden
Master
IDQ & Address Doctor Informatica Customer 360
13
DownstreamSystems
14. Customer MDM Implementation
@Leading Manufacturer of High-performance Paints
14
Key Highlights
Business Drivers
ď§ No single truth of key enterprise entities. It was mastered in Talend earlier and moved to ERP (SAP R/3) .
ď§ Data related to key entities are being authored and manipulated through multiple application/spreadsheets without being governed or
synchronized .
ď§ Data errors were impacting the enterprise flows like order to Cash to Cash & Procure to Pay.
ď§ Operational cost went up due to data corrections .
ď§ S/4 HANA implementation needed governed mastered data.
Enterprise-wide
source for Business
Customer
Customer Workflows
moved to ActiveVOS
from ServiceNow and
other 3rd party apps
Improved data quality
and reliability of key
data elements
Integrated data
synchronization
between MDM and
ERP
Solution Highlights
ď§ Inbound & outbound data integration in Batch & Real Time
ď§ Use of MDM UI as a data authoring source. Uses collaborative method of record creation.
ď§ Optimization of business processes authoring master data based on reference data
ď§ Synching up reference data constraints on MDM with ERP .
ď§ Use of IICS as middleware for integration and data reconciliation.
ď§ Critically placed to improve interface services , lifecycle management services to evolve from coexistence style to transactional style
of implementation
Business Outcome
ď§ Improvement on Time to Market , Order to Cash
ď§ Improved service accuracy through Single Source of Truth
ď§ Mass upload delivered for bulk authoring to improve operations
ď§ Governed ERP master data for CFIN program
ď§ Single Global MDM multi-domain platform for Customer, Supplier, Profit Center and Material master data
ď§ Technology Stack: Informatica Multi-domain MDM on AWS Cloud, Power Center, IDQ, IICS & SAP R/3, S4 HANA
15. Customer MDM Implementation using INFA MDM
@Global provider of water, hygiene and energy technologies and services company
Key Highlights
Business Drivers
ď§ Customer, Product, Field Sales Org and Corporate Account Org hierarchy data not synchronized across systems leading to conflicting
values
ď§ Opportunity to improve understanding of quality of data
ď§ Opportunity to improve visibility of master data across divisions and regions globally
ď§ Unauthorized data changes and lack of country specific validation rules cause data quality issue
ď§ Difficulties in BI and Reporting due to lack of Single Version of TruthEnterprise-wide
source for Business
Customer & Product
Access based task
approval ActiveVOS
implementation on
INFA MDM platform
Improved
sustainability of data
quality and
governance of key
data elements
Improved business
intelligence and
enterprise reporting
Solution Highlights
ď§ Proposed a Global MDM system to the client to make business-critical decisions by selecting, configuring and implementing a single
set of global tools (system and workflow) for the consolidation of data from SAP and non-SAP systems
ď§ Maintaining Customer, Product and Hierarchical data in MDM
ď§ Provided an analytical Customer & Product Master Data solution for reporting purposes
ď§ Implemented SAP PowerExchange with Informatica PowerCenter to extract Customer & Product data from SAP Enterprise
DataWarehouse
ď§ Upgrade from MDM 9.7.1 to MDM 10.2
Business Outcome
ď§ Enabling the objectives of other strategic programs with a strong dependency with Master Data Management and Data
Quality/Governance
ď§ Gained insight into underlying data quality issues and improved data quality, accurateness and uniqueness
ď§ Improved sustainability of data quality and governance for key business data elements and related data
ď§ Improving business intelligence and enterprise reporting for making business-critical decisions
ď§ Consolidation of global management and governance of non-transactional master data across divisions and regions
ď§ Technology Stack: Informatica MDM Advanced Edition, DB2, JBOSS-EAP-6.4.1, Informatica Power Center, Informatica Data
Quality, ActiveVOS, Address Doctor
15
16. 16 Š Informatica. Proprietary and Confidential.
A new breed of customer is changing expectations.
89% of companies plan to compete primarily
on the basis of the customer experience.
17. Š Informatica. Proprietary and Confidential.
What you should know about your customers
⢠Are you a
customer?
â˘Which products
are owned?
â˘Whatâs the next
best offer?
⢠Who is in your
customerâs
circle?
18. Š Informatica. Proprietary and Confidential.18
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
19. Š Informatica. Proprietary and Confidential.
The Information Challenge
Data Governance
?
Marketing OperationsSales Operations Customer Service
Location
Account
Customer
Product
Product
AccountCustomer
LocationAccount
LocationProduct
CustomerProduct
AccountCustomer
Location
No View of Interactions
3
No View of Relationships
2
No Single View
1
LegacyApplicationCloud Computing Unstructured Third Party Data
20. Create an Intelligent 360 View of Data
Contact
Information
Contact
Preferences
Locations
Business
& Consumer
Information
Products
& Services
Business
Relationships
Household
Relationships
Supplier
Relationships
Sales Offers
& Activities
Marketing
Communication
& Responses
Service Issues
& Needs
Billing &
Contract
Activities
Social Media
Channels
IOT & Devices
Chatbots
RelationshipsProfile
Interactions & Transactions
21. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA GOVERNANCE & QUALITY
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
CUSTOMER MASTER
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Customer 360 Data Model
Name
Product Address
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
22. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA GOVERNANCE & QUALITY
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
CUSTOMER MASTER
Customer 360 Data Model
Name
Product Address
23. Š Informatica. Proprietary and Confidential.
Informatica MDM - Customer 360
The data to create a segment of one
Power your customer initiatives
and fulfill customer experience
promises with streamlined
customer onboarding, customer
lifecycle management, and
customer engagement.
Accelerate time-
to-value
Predefined best in
class Customer data
model
Real time web services
Pre-built, configurable
Full MDM capabilities
Designed for
Business Users
Preconfigured
New Task inbox
Role based
Business workflows
Engagement
dashboards
Embedded 360
Apps Access
Expose product
details and
information from
Product 360 and
relationships
Customer
Enrichment
Demographics
3rd Party data
verification and
validation
Preferences
Tags
24. Š Informatica. Proprietary and Confidential.
The Business Model is the tip of the iceberg
Business Model
Metadata Model The metadata model is
generated at design time
The business model is defined
by customer to represent their
master data entities, child
tables, and reference data
25. Š Informatica. Proprietary and Confidential.
Design master data domains as YOU need them
Model the information which matter for your business
The ONLY
True Multi-Domain
140+ domains
Product
Reference Supplier
Infer and suggest the best format for
master data attributes
Flexible, model driven approach for
business users to define master
data domains
Define the relationships between
different domains
Auto generate APIs that allow MDM
to integrate with critical business
systems in real-time
B2C
Customer
B2B
Customer
Location
27. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
CUSTOMER MASTER
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Customer 360 Data Model
Name
Product Address
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
DATA GOVERNANCE & QUALITY
DATAQUALITY
28. Š Informatica. Proprietary and Confidential.
Discover and Understand the Nature of Data
Data discovery and profiling
⢠Identify the untapped sources where master data
exists
⢠Profile the data, understand the quality, identify
variations and trends
⢠Create data quality rules that help fix data issues
on an ongoing basis
⢠Continuously monitor and analyze data issues
⢠Supports Big Data profiling (Data Quality on
Hadoop)
AnalystSteward
29. Š Informatica. Proprietary and Confidential.
Embedded data quality to ensure IT and business collaboration
Ensure High Quality Trustworthy Data
⢠Ensure master data is clean, consistent and
accurate
⢠Data quality capability at the mapping level
⢠Scorecard: Graphical view of point-in-time
view and trends in source data quality
⢠Reuse standardized rules across the data
ecosystem (Build once, deploy anywhere)
⢠Cleanse, standardize, validate â Visual
mappings and no coding
⢠Batch and real time operations
31. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA GOVERNANCE & QUALITY
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Customer 360 Data Model
Name
Product Address
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
CUSTOMER MASTER
Match
32. Š Informatica. Proprietary and Confidential.
Matching Technology
Worldâs best matching engine â used by more than 1400 organizations
Superior data matching leverages best-in-class algorithms
Proven technology with more than 30 years of intelligence
Out-of-the-box rules for global country populations,
language and character sets
Overcomes the error and variations in the data
High performance for extreme data volumes
Also available on Hadoop
Informatica
MDM Match
Engine
Phonetic and
orthographic
errors
Missing, extra
and out-of-order
words
Multi-language
problems
Nicknamed and
abbreviations
Prefix and suffix
variations
Compound and
account name
structures
33. Š Informatica. Proprietary and Confidential.
Error / Variation Example
Sequence Error Mark Douglas - Douglas Mark
Auto-correction Browne - Brown
Concatenation Mary Anne - Maryanne
Nickname Chris - Christine - Tina
Noise Full stops, dashes, titles
Abbreviation Mfg - Manufacturing
Truncation Credit Suisse, First Bost
Prefix / Suffix MacDonald â McDonald
Spelling Potter - P0rter
Typographical Beth - Beht
Error / Variation Example
Transcription Hannah, Hamah
Missing Token Paul W Smith â Paul Smith
Extra Token George Smith - Smith
Romanization ĺąąç°ĺ¤Şé - Taro Yamada
Initials John Alan Smith - J A Smith
Transposition Johnson - Jhonson
Localization Stanislav Milosovich- Stan Milo
Inaccurate Date 12/10/2010â 10/12/2010
Transliteration Kang - Kwang
Phonetic Edinburgh â Edinborough
Informatica Helps You to Get the HARD STUFF Right
We use a combination of methods and
algorithms to compensate for different
classes of error and variation present in
identity data. 30 years, 50+ Populations
35. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA GOVERNANCE & QUALITY
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Customer 360 Data Model
Name
Product Address
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
Dynamic Cell-Level
Survivorship
CUSTOMER MASTER
36. Š Informatica. Proprietary and Confidential.
Merge
Recognize the entity accurately across multiple systems
Mike William
DâAgostini
Michael W DâAgostini
Michael
William
DâAgostini
XREFXREF
Select most
reliable
attributes to
survive, at the
cell level
Reduce
manual effort
by
automatically
merging high
confidence
matches
Efficient
manual reviews
with built in
data steward
screens and
workflows
Complete
history and
lineage of data
changes â
allow you to
easily unmerge
38. Š Informatica. Proprietary and Confidential.
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATAINGESTION
DATA CATALOG
DATA GOVERNANCE & QUALITY
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
DATADELIVERY
Consolidation
Process
Customer 360 Data Model
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
CUSTOMER MASTER
Name
Product Address
39. Š Informatica. Proprietary and Confidential.
Relate
Capture data relationships between people, products and locations
Dr. John T Burch
Dr. Greg Malmquist
Graves Gilbert
Clinic - Russelville
Graves Gilbert
Clinic - Bowling
Western Kentucky
Ortho & Neuro
Seen At
Graves Gilbert
William DâAgostini
DâAgostini Household
Dr. Greg Malmquist
Seen By
Spouse of
Mary DâAgostini
Belongs to
Consolidated
view of all the
relationships
and a single
place to
manage them
Manage master
data and the
relationships in
one single
place
Manage
relationships
from different
applications
and systems
Create and
manage a rich
set of multiple
hierarchies for
different
purposes
Maintain
history and
lineage of
relationship
changes
41. Š Informatica. Proprietary and Confidential.
Customer 360 Reference Architecture
Data WarehouseDocuments
STREAMING
CHANGEDATA
CAPTURE
BATCH
DATA CATALOG
DATA SECURITY
Databases
Application Servers
Mainframe
Machine
Data
Cloud
Mobile
Social
Log
files
Apps
CUSTOMER MASTER
Dynamic Cell-Level
Survivorship
Auto Merge
Match
Manual
Merge
Un-Merge
Consolidation
Process
Customer 360 Data Model
Name
Product Address
Business
Partners
Applications
Data
Warehouse
Machine
Learning
Historical
Analysis
Advanced
Analytics
Real-Time
Visualization
DATA INFRASTRUCTURE
DATAQUALITY
CUSTOMER 360 INSIGHTS
Natural Language Parsing
Contextual Matching
Confidence Scoring
Inferences and Insights
Enrichments
Perspectives
Customer Data Lake
DATA GOVERNANCE & QUALITY
DATAINGESTION
DATADELIVERY
42. Š Informatica. Proprietary and Confidential.
⢠Option 1: Pub Sub Integration/Synchronization
⢠Leverage MDM triggering events to publish a message to a
queue
⢠Option 2: Informatica Real-Time Services
⢠Leverage Informatica Services Integration Framework (SIF)
⢠Leverage Business Entity (Composite) Services operate on
Composite Objects and represent a composition of atomic
logic steps
⢠Option 3: Informatica Cloud Real-Time
⢠Real-Time Integration with Web services
⢠Option 4: PowerCenter/PowerExchange Connectors
⢠Leverage out of the box connectors for commons sources
Integrate
43. 43 Š Informatica. Proprietary and Confidential.43
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
44. 44 Š Informatica. Proprietary and Confidential.44
Lab: Hands-On with MDM Microservices Architecture
⢠Lab 1: Review the MDM Hub REST API using Postman
⢠Lab 2: Add an Attribute to the MDM Services using the Provisioning Tool
⢠Lab 3: Review the New Attribute in the REST API
⢠Lab 4: Add a New Attribute to the Stewardship User Interface
⢠Each Participant will access their own Lab Environment using Microsoft Remote Desktop
45. 45 Š Informatica. Proprietary and Confidential.45
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
47. Š Informatica. Proprietary and Confidential.
IDENTIFY BUSINESS GOALS
ESTABLISH METRICS FOR YOUR TRUSTED DATA EFFORTS
GET YOUR BEARINGS: YOUR ROADMAP TO TRUSTED
DATA
PLAN AND CONDUCT STAKEHOLDER INTERVIEWS
ANALYZE YOUR FINDINGS
Route to Trusted Data
PREPARE YOUR BUSINESS CASE
48. Š Informatica. Proprietary and Confidential.
Getting Started
Identify Business Problems, Requirements and Key Stakeholders
⢠Business Challenges
- Revenue is lost by making irrelevant product offers to existing customers.
- Time and money is wasted trying to acquire new customers with poor
segmentation.
- Profits are lost, and customer retention and loyalty suffer because of the inability
to align service levels to customer value.
⢠Root Cause
- Company has no single view of customers, and the products and services that
customers have purchased.
⢠Solution
- Create a single view of customers, products and services accessible to sales,
marketing, and customer service
Cross-Sell Example:
âCross-sell
revenue has
declined 10
percent"
49. 49 Š Informatica. Proprietary and Confidential.
Business drivers fueled by a trusted 360 view of data
Governance and
Compliance
Mergers and
Acquisitions
Operational
Efficiency
Advanced
Analytics
Customer
Experience
Product
Experience
Trusted 360 view of
customers to deliver:
⢠Personalized digital
experiences
⢠Omnichannel
consistency
⢠Better cross-sell / upsell
offers
⢠Targeted marketing
⢠Improved customer
service delivery
⢠Frictionless engagement
⢠Enable customer centric
processes
Increase efficiency &
employee productivity:
⢠Reduce procurement
costs & streamline
processes
⢠Accelerate time to value
by collaborating across
teams & departments
⢠Achieve higher margins
& conversion rates from
e-commerce
Feed actionable data to
Data Lakes & Data
Warehouse for:
⢠Self-service analytics
and reporting
⢠Customer behavior
analysis
⢠Trends & forecasting
⢠Service personalization,
optimization, & targeting
⢠Next best action
recommendations
Comply with internal
policies & regulations:
⢠Secure & protect
sensitive information
about customers
⢠Manage consents
across the customer
base
⢠Gain visibility to product
& supplier details
⢠Avoid regulatory fines
by reporting accurate
data on time
Streamline merger &
acquisition processes &
increase value:
⢠Act as one company to
customers and
employees:
⢠Expedite M&A synergies
⢠Understand risk
concentration of
customers, suppliers,
etc.
⢠Acquire new customers
faster
Improve collaboration &
product information
management:
⢠Simplify complex
product information
management.
⢠Reduce cost of owner-
ship & increase
productivity.
⢠Ensure consistent,
accurate & complete
information across sales
channels.
⢠Accelerate time to
market for new product
introduction.
50. Š Informatica. Proprietary and Confidential.
These Data Challenges Impact Every Aspect of Your
Business
Existing Data Challenges and Root Causes
Too many duplicate
sources of similar data
Fragmented views
of information
Limited insights into
relationships between and
across entities
Lack of access
to required data
⢠Higher customer
acquisition costs
⢠Lower sales conversion rates
⢠Higher customer
servicing costs
⢠Unable to grow wallet share
⢠Inaccurate customer
profitability measurements
⢠Delays new client onboarding
processes
⢠Errors in regulatory reporting
⢠Duplicative and overstated
risk measurements
⢠Increased risk of
regulatory fines
⢠Unable to identify and
measure overall risk exposure
⢠Failure to comply with OFAC,
CDD, KYC requirements
⢠Increase risk of failed trade
executions
⢠Incorrect and/or delayed
settlement processes
⢠Higher reconciliation costs
⢠Treated as a stranger vs. a
valued customer
⢠Offered the wrong products
and/or services
⢠Poor customer experience
across touchpoints
Sales and Marketing Risk and Compliance CustomersOperations
51. Š Informatica. Proprietary and Confidential.
How MDM Can Help the Business
Creating the business case
⢠Improve productivity and profitability
⢠Drive revenue with more effective cross-sell and up-sell offers
⢠Boost customer loyalty and retention by reducing response times
⢠Reduce customer service costs by aligning service to customer value
⢠Increase operational efficiency and cash flow
⢠Streamline supply chain efficiency
52. Š Informatica. Proprietary and Confidential.
ThinkBig, Start Small, Grow Fast
MDM Applications
CUSTOMER
360
orCUSTOMER
360
PRODUCT
360
RELATE
360
CUSTOMER
360
PRODUCT
360
SUPPLIER
360
Domain
Single Multiple
Records
Attach
Enterprise
Data Catalog
Axon
Data
Integration
Data as a
Service
Big
Data
Data
Quality
MDM
and
Implementation Style
Batch /
Analytical
Operational Registry Consolidation Co-Existence Centralized
Usage
Localized
Implementation
Global
Expansion
Line of
Business
M&AFunctional
Areas
53. Š Informatica. Proprietary and Confidential.
Keys to Success
⢠Crawl â Walk â Run
⢠Keep scope as small as possible to meet objectives of each of the phases
⢠Evolve what is there (additional attributes) and expand the base (include more businesses
and new domains)
⢠Start the MDM program by looking the consumption side to understand consumers
and business objectives and then work backwards
⢠Find a vocal champion at the executive level â both Business and IT
⢠Architect for the future but design for today
⢠Perfection is the enemy of the good
⢠IT needs to be flexible and have a plan for changes that will occur
54. 54 Š Informatica. Proprietary and Confidential.54
Agenda
Introduction
The Need for Mastering Data
Key Concepts for Mastering Data
1
2
3
Hands-On Lab4
Engaging Your Business Counterparts5
Final Q & A, Wrap-up6
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
And with INFA EDG Application, we now have a complete set of capabilities, that meets every data governance stakeholder, business or technical, where they are, and allows them to be productive, regardless of their skillset or the current maturity of the data governance program.
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
CHRISTUS Health is a global, not-for-profit Catholic health system delivering care from more than 60 hospitals and long-term care facilities, 350 clinics and outpatient centers, and dozens of other health ministries and ventures. Based in Irving, Texas, the organization employs 30,000 people, including 9,500 physicians. Itâs vision: to be a leader, a partner, and an advocate in the creation of innovative health and wellness solutions that improve the lives of individuals and communities
CHRISTUS Health has grown significantly in recent years. That growth placed an increasing burden on the organization to more effectively manage the resulting volume of patient and operational data â everything from billing and registration information to clinical data. Information was spread across a number of siloed applications and EMRs, making it hard to aggregate, govern, and validate.
CHRISTUS Health set out to not only better manage the growing volume of data, but to leverage that data to increase the effectiveness and quality of the services it delivers to patients. To do this, the organization needed to integrate and organize data across the enterprise, with common tools, classifications, and standards. Ultimately, data needed to reach the right people at the right time to deliver the expected levels of service. In addition, patients needed to be able to trust the care they were receiving: it was important that medical staff understood their health histories and requirements.
Using Informatica, the needs of provider and patient were met. Enterprise-wide data is now captured, normalized, and interrogated into a single, easily accessible platform. CHRISTUS care providers can now use complete, clean patient data to make informed decisions and deliver a more personalized experience. Additionally, the adoption of evidence-based computerized physician order entry has resulted in decreased length of stay and lower emergency department wait times. This resulted in $500,000 in savings within a few months of the system going live. For example, a discrepancy in a vendor agreement was spotted, saving CHRISTUS Health $250,000.
Inside the Solution
Informatica PowerExchange
Informatica PowerCenter
Informatica MDM
Informatica B2B Data Exchange
Informatica Data Archive
Informatica Data Quality
Informatica Address Verification
Informatica Professional Services
Read the Story and Watch the Video: https://www.informatica.com/about-us/customers/customer-success-stories/christus-health.html#fbid=m7IHYmPcRGW
CHRISTUS Health is a global, not-for-profit Catholic health system delivering care from more than 60 hospitals and long-term care facilities, 350 clinics and outpatient centers, and dozens of other health ministries and ventures. Based in Irving, Texas, the organization employs 30,000 people, including 9,500 physicians. Itâs vision: to be a leader, a partner, and an advocate in the creation of innovative health and wellness solutions that improve the lives of individuals and communities
CHRISTUS Health has grown significantly in recent years. That growth placed an increasing burden on the organization to more effectively manage the resulting volume of patient and operational data â everything from billing and registration information to clinical data. Information was spread across a number of siloed applications and EMRs, making it hard to aggregate, govern, and validate.
CHRISTUS Health set out to not only better manage the growing volume of data, but to leverage that data to increase the effectiveness and quality of the services it delivers to patients. To do this, the organization needed to integrate and organize data across the enterprise, with common tools, classifications, and standards. Ultimately, data needed to reach the right people at the right time to deliver the expected levels of service. In addition, patients needed to be able to trust the care they were receiving: it was important that medical staff understood their health histories and requirements.
Using Informatica, the needs of provider and patient were met. Enterprise-wide data is now captured, normalized, and interrogated into a single, easily accessible platform. CHRISTUS care providers can now use complete, clean patient data to make informed decisions and deliver a more personalized experience. Additionally, the adoption of evidence-based computerized physician order entry has resulted in decreased length of stay and lower emergency department wait times. This resulted in $500,000 in savings within a few months of the system going live. For example, a discrepancy in a vendor agreement was spotted, saving CHRISTUS Health $250,000.
Inside the Solution
Informatica PowerExchange
Informatica PowerCenter
Informatica MDM
Informatica B2B Data Exchange
Informatica Data Archive
Informatica Data Quality
Informatica Address Verification
Informatica Professional Services
Read the Story and Watch the Video: https://www.informatica.com/about-us/customers/customer-success-stories/christus-health.html#fbid=m7IHYmPcRGW
Hyatt Hotels Corporation, headquartered in Chicago, is a leading global hospitality company with 12 premiere, luxury, and resort brands and 667 properties in 54 countries (as of June 2016).
Hyatt is in a highly competitive market and is small relative to companies such as Hilton (4,200 properties), Marriott (3,900 properties), and Starwood (1,200 properties). This is a challenge because loyalty programs reward customers for staying at a brandâs properties. With fewer properties itâs harder for customers to earn and take advantage of points. So Hyatt has to differentiate on something other than size, scale, and price. The company differentiates itself by having a laser-like focus on customers, and using data effectively is key to the success of this approach. By doing so, Hyatt is able to fulfill its purpose: to care for people so they can be their best.
Hyatt strives to deliver outstanding and memorable customer experiences that guests want to have every time they travel, thus building fierce brand loyalty. To consistently deliver unmatched customer experiences at any Hyatt property, Hyatt needed a way to capture and understand customer behaviors, preferences, and influences, and share them across properties. For example:
Customer preferences captured at a hotel in Singapore could be readily viewed by hotel staff in Dallas, which could then immediately deliver on those preferences.
Perhaps a frequent business traveler always requests a particular type of pillow or orders a particular drink or item on the dinner menu â next time the traveler arrives, at any property, the hotel can meet those needs before they are even requested, creating the feeling that Hyatt truly cares about the customerâs needs.
To do this, the company needed to:
Empower associates to consistently deliver great guest experiences at every stage of their journey, at any property.
Bridge data silos so customer information can be shared with any of the 600 hotel properties and functions around the world.
Consolidate large amounts of data from a multitude of sources across brands, properties, regions, and functions to execute this end-to-end Guest Experience Management (GEM) vision, while boosting sales and marketing effectiveness and improving business decisions.
Unify and automate distributed marketing efforts and target campaign development around actionable customer data.
Today, Hyatt knows more about its customers, leaving the guess work out of all interactions. Although still in their infancy, results include:
Increased guest engagement metrics substantially and tracked preferences through NPS.
Hyatt Hotels & Resortsâ up-sell/cross sell program in the Americas increased revenue by double digits (60%) year-over-year.
Globally, Hyatt increased revenue from loyalty members by 19.6%.
Improved marketing campaign effectiveness by better segmenting customers based on richer customer profiles for more personalized offers.
Reduced loyalty program costs by targeting the right guests with the right information.
Enabled management to make better business decisions based on great data.
Created a springboard for new analytical applications with its customer data hub; helped segment customers based on different needs or location to build predictive models.
Inside the Solution
Informatica Master Data Management
AddressDoctor
Informatica Data Quality
Informatica PowerCenter
Slide #8: The Customer Data Management Solution
Monica:
SirHari, how did you overcome this customer data management challenge? [speak to the data flows and:
What source and target systems are you using?
Which domains are you mastering?
How many customer records are you mastering?
How long did it take you to implement the solution?
Tom, what operational systems now have great customer data and give me an example of how it helps your team?
[SPEAKER NOTES]
89% of companies plan to compete primarily on the basis of the customer experience. Why? Because customers have changed.
Todayâs customers are social, mobile, connectedâŚand spoilt for choice. They want what they want, when they want it. They live for convenience, and if you fail to provide it, theyâll find someone who can. No company is immune to thisâ whether B2B, B2C or B2B2C.
What should you know about your customers?
You need to be able to quickly and easily answer the following questions:
Which customers is it?
What have they purchased?
Whatâs the next best offer?
Is this a good time to make the offer?
If the data thatâs feeding operational and analytical systems isnât clean, consistent and connected, how are people getting the information they need to answer these questions today?
More detailed questions:
Which customer is it?
Is it an account or a contact?
Whatâs their correct contact information for marketing, shipping and billing?
Have they joined our loyalty program or a branded cardholder?
For business customers, are they a stand-alone or subsidiary of a larger company?
What have they purchased?
What products do they have across product lines and channels?
Whatâs theyâre buying and renewals history?
Which channels do they prefer?
Which employee or partner manages this customer relationship?
What opportunities do we have?
What products would be of interest?
Who influences this buyer?
Are there members of the household we should be targeting with relevant offers?
Is this a good time to make the offer?
Are they paying their bills on time?
Have they opted in to receive marketing offers?
Whatâs their level of satisfaction? Any open service issues?
Are they talking about us in social media channels?
Are they an advocate for our brand?
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
Manouj:
Multi-domain and multiple domains
Analytical and operational use cases
Batch, real time and near real time integration options
Business users and data stewards
Discover master data and measure data quality
USP â Award. What is unique that no one has? (Ex: Industry best Matching
Proven technology with more than 30 years of intelligence. All this implemenation knowledge is turned into out-of-the-box rules for global country populations, language and character sets
Here listed are the top 20 common types of errors and variations in names.
To match intelligently, you have to be able reduce false positives to avoid over matching but you also have to be able to find as many potential matches as possible to avoid under matching.
Informatica has a core match engine that has been tuned over 30 years and in use by hundreds of customers in many different industries to handle these sorts of variations
Key Points:
IIR Matching uses a combination of methods and algorithms to compensate for different classes of error and variation in identity data..
Example Text
The Matching algorithms constitute a hybrid approach, since no one approach is enough to compensate for all types of error and variation.
The Linguistic components refer to those parts of Matching that are defined per country or language and relate also to the Phonetic components and some of the Deterministic rules
The Phonetic components refer to the Word Stabilization routines that are provide per country / language
The Empirical components refer to the 20+ years of testing and tuning on real customer data for multiple countries and languages
Deterministic refers to the development of extensive match logic and rules that direct the match process for known classes of variation in a predictable manner. It also includes the ability to combine Match comparisons of different fields together using Boolean logic (e.g. only match these two names if the SSNâs match).
Heuristic refers to the additional Match options and logic that cause the process to try many different approaches to achieve the highest possible score
The Probabilistic contribution to Matching actually comes from the keys and search strategies (which ultimately determine what records are passed to matching). The keys and search strategies, by their inclusion of name frequency into the algorithms, allows common name searches to produce more refined candidate lists than uncommon name searchesâŚ.thus, for example, the probability of mis-matching a âJohn Smithâ is reduced since the number of variations of John Smith that are allowed through is also reduced.
Transition:
The fuzzy matching capabilities of IIR are not just limited to names and addresses, but span the full spectrum of identification data.
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â
PRASH
â
6 primary use cases / initiatives
Maps to sub-journeys, e.g. data governance and compliance maps to .. , M&A maps to âŚâŚ
CX: Deliver frictionless, consistent customer experiences, improve customer engagement, and transition to customer centric organization.
PRASH
â
6 primary use cases / initiatives
Maps to sub-journeys, e.g. data governance and compliance maps to .. , M&A maps to âŚâŚ
CX: Deliver frictionless, consistent customer experiences, improve customer engagement, and transition to customer centric organization.
This is not only a text box. You can also place a table, chart or smart art graphic within a content box. You can only place one or the other.
For each of our MDM solutions, we have the capability to use different levers to control the price. This is effectively done through discounting. For exampleâŚ. [click through each to build and explain].
So at the end of the day, we can usually craft a solution that meets the clientâs budget. It wonât be an unrestricted, unlimited enterprise license (although thatâs certainly an option if they have the budget for it!), but it will meet the project deliverables.
But we still are not likely to be the CHEAPEST solution in the market. How do we justify what we charge? OK, here comes the really cool partâŚ
A bit about the history of MDM (analytics Ă operational; some examples of how customers are using MDM in mission critical applications)
A bit about continuous innovation, architecture, and on-premises and cloud availability
MDM at scale (large volumes of data, MDM in Big Data)
Competitive differentiation
What is next gen MDM
Core strategy
Â