The document discusses key concepts in master data management including: - Defining systems of record, sources of truth, and canonical data models to manage master data across different systems. - Mapping data entities and attributes stored in different systems like CRM, ERP, and data hubs. - Techniques for matching, merging, and determining the "single source of truth" for master data when conflicts arise from multiple source systems.

1. Prepared and presented by :
• Vinay Sail – Domain Architect, Canon EMEA
MDM & Metadata
Management

2. MASTER DATA MANAGEMENT

3. ❖ Pace-Layered Application Strategy
❖ Master Data Management Definition
❖ System of Record
❖ Systems landscape with Data Entity Mapping
❖ GoldenSingle Source of Truth (SSOT)
❖ The Difference Between System of Record and Source of Truth
❖ Canonical Data Model
❖ Use Case
❖ Hierarchies Management
❖ Data Migration – MDM considerations
❖ Managing Data Conflicts
❖ External data for enrichment
❖ Data Matching Techniques
❖ Data Survivorship Techniques
What You Will Learn Today!

4. System of record
Source: https://www.gartner.com/binaries/content/assets/events/keywords/applications/apn30/pace-layered-applications-research-report.pdf
Pace-Layered Application Strategy
Established packaged applications
or legacy homegrown systems that
support core transaction processing and
manage the organization's critical master
data. The rate of change is low,
because the processes are well-established
and common to most organizations, and
often are subject to regulatory
requirements. Systems of record have the
longest life cycle, at 10 or more years
e.g. ERP – Order Management
System of differentiation
Applications that enable unique company
processes or industry specific
capabilities. They have a medium life
cycle (one to three years), but need to be
reconfigured frequently to
accommodate changing business practices
or customer requirements
e.g. Loan Processing System,
Customer Service
System of innovation
New applications that are built on
an ad hoc basis to address new
business requirements or opportunities.
These are typically short life cycle
projects (zero to 12 months) using
departmental or outside resources and
consumer-grade technologies
e.g. Product Review Service, Mobile
Apps

5. Master Data Management Definition
Master data management (MDM) is a technology-enabled discipline in which business and IT work together
to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability
of the
enterprise’s official shared master data assets.
Master data is the consistent and uniform set of identifiers and extended attributes that
describes the core entities
of the enterprise including customers,
prospects, citizens, suppliers, sites, hierarchies and chart of accounts.
https://www.gartner.com/en/information-technology/glossary/master-data-management-mdm

6. System of Record
System of record
Established packaged applications
or legacy homegrown systems that
support core transaction processing and
manage the organization's critical master
data. The rate of change is low,
because the processes are well-established
and common to most organizations, and
often are subject to regulatory
requirements. Systems of record have the
longest life cycle, at 10 or more years
e.g. ERP – Order Management
Source: https://www.gartner.com/binaries/content/assets/events/keywords/applications/apn30/pace-layered-applications-research-report.pdf
A system of record is the authoritative data source for a given data
element or piece of information

7. Systems landscape with Data Entity Mapping
CRM ERP Product Hub SCMSystem of Record
Attributes
Customer
CompanyName
Phone
Email
Order
Invoice
Order Lines
Product
Name
Type
Supplier
Name
Location
Entity

8. GoldenSingle Source of Truth (SSOT)
The source of truth is a trusted data source that gives a complete picture of the data object as a whole

9. The Difference Between System of Record and Source of Truth
Business Process Design Sales Shipment
Application - System
of Record
Product Data Hub CRM Transport
Management
Attributes Product Name,
Description etc.
Pricing Logistic
System of Record System of Truth
Product Data
Hub
CRM
Transport
Management
Product Master
• Create a SOT by compiling item attributes from the different item SORs.
• This is where a data repository helps us in delivering SOT data to the
business users.
• This could be an operational data store, data warehouse, or data lake.
https://www.linkedin.com/pulse/difference-between-system-record-source-truth-santosh-kudva/

10. Canonical Data Model
System A
System B
System C
System 1
System 2
System 3
System 4
Point to Point Mappings
System A
System B
System C
System 1
System 2
System 3
System 4
Canonical Data
Model
Canonical Mappings
https://www.bmc.com/blogs/canonical-data-model/

11. Use Case Scenario
Product Data Hub
Enterprise Service
Hub
CRM
ERP
Logistics
Reporting +
Analytics
Third Party
Service

12. Use Case Scenario
Product Data Hub
Enterprise Service
Hub
CRM
ERP
Logistics
Reporting +
Analytics
Third Party
Service
SDM CDM
CDM TDM
CDM TDM
CDM TDM
SDM Source Data Model TDM Target Data Model CDM Canonical Data Model

13. Hierarchies Management
https://help.salesforce.com/articleView?id=account_hierarchy_setup_lex.htm&type=5
• Native or custom build support for hierarchy management
• Visualization of hierarchy
• Access level to view complete hierarchy

14. Data Migration – MDM considerations
• Plan your MDM strategy carefully for interim period of data migration
e.g. Continue using legacy system as system of record until rollout for all countries has been completed for newly
introduced system
• Think about delta data migrationreal time integrations to keep data in sync
• Involve relevant stakeholders to create MDM plan to specific the system of records for specific data sets
e.g. certain objects and fields are master in Salesforce but other objects and it’s fields master in data hub

15. Managing Data Conflicts
• Define primary system that will be used for storing and managing data objects and attributes
• Consult with MDM stakeholders to establish which system acts as the SOR for various data objects and it’s attributes
e.g. few of customer attributes SOR is Salesforce and ERP will be SOR for rest of attributes
• Considering using central data hub e.g. customer andor product data hub
• Define the set of integration to make sure that data flows taking care of updated data available across system landscape
e.g.
PRODUCT
HUB
SUPPLY CHAIN
MANAGEMENT
ORDER
MANAGEMENT

16. External data for enrichment e.g. Account, Address
enrichment
• MDM can leverage external data for data enrichment using third party services
e.g. Customer enrichment using D & B, Address Validation service

17. Define Golden Record – Source of Truth
Matching Policy
Data Survivorship Rules
Deterministic Matching
Probabilistic Matching
• Looking for exact matching between two records/sub section
of data set
• Viable approach only when full data set available for
comparison
• e.g. comparing external id field within Salesforce with primary
key of the record in the ERP system or address comparison
• Weights being used to calculate matching scores
• Based upon score, business can decide rules to define
golden record
• e.g. comparing address fields, tax id field
Most Recent
Most Frequent
Most Complete
• The most recent record can be considered eligible as the survivor
• The Most Frequent approach matches records containing the
same information as an indication of their correctness.
Repeating records indicate that the information is persistent
and therefore reliable
• Most Complete method considers field completeness as its
primary factor of correctness. Records with more values
populated for each available field are considered the most
viable candidates for survivorship.
http://www.dbta.com/Editorial/Think-About-It/For-Data-Quality-Intelligent-Rules-Add-Value-to-the-Golden-Record-92687.aspx

18. Data Survivorship Techniques
http://mdm-socialmedia.blogspot.com/2013/02/
Trust and Decay
Before we start loading data in MDM hub, we should established trust to multiple sources which can
contribute to data in hub. A trust is a factor which determines how much trust we have on data coming
from a particular source. Trust may decrease based on time. This is known as decay. This decay is
usually of two types, SIRL (Slow Initial and Rapid later) and RISL (Rapid initial and Slow later). So, a trust
usually defines at a particular time how much trust we have on a particular source system. During source
system implementation, we should assign some trust level to each source. This trust level is any number
from 0 to 100 in increasing order. 100 means trusted most and 0 means trusted less. This trust must be
enabled on each source and at each cell level. You can assign trust on some of attributes and not
necessary to have it on all.
Validation
Precedence
Once trust has been assigned, we should define some validation rules. A validation rule, determine or helps in
evaluating trust score. A validation rule can only decrease trust score for a particular cell.
For Ex: We can have a validation rule which decrease trust score by 35 for ‘PHONE’ attribute if phone number is
less than 10 digits.
If multiple sources cell value obtained same trust score then which cell survive or win is determined by
precedence rules. Suppose same cell value is coming from four sources then surviving cell source and value
determined by following precedence order.
· Once data gets loaded in hub then its trust score gets evaluated based on trust and decay settings.
· If any validation rule is defined on this cell then trust score again evaluate after applying that validation
rule.
· The source’s cell data which got higher trust score will win and survive/win in best version of truth.
· If multiple source’s cell value got same trust score or trust not enable on this attribute then source which
has latest( most recent) source last update date (SRC_LUD) of xref , will win.
· If still multiple sources has same SRC_LUD then source which has recent last update date in base object
will win.
· If this still same then cell’s record which has higher Rowid_Object( MDM ID) will win.

19. • Pace-Layered Application Strategy
• Master Data Management Definition
• System of Record
• Systems landscape with Data Entity Mapping
• GoldenSingle Source of Truth (SSOT)
• The Difference Between System of Record and Source of Truth
• Canonical Data Model
• Use Case
• Hierarchies Management
• Data Migration – MDM considerations
• Managing Data Conflicts
• External data for enrichment
• Data Matching Techniques
• Data Survivorship Techniques
What You Learned so far Today!

20. Account team from Dreamland Ltd. using Salesforce for their Sales Management. Next to it, they also have on premise ERP system for order
Management. Once opportunity close successfully, opportunity and it’s opportunity products must be integrated with ERP instantly.
All opportunity data must be read only in ERP system to avoid modification of opportunity related data in the ERP.
What will be solution considerations to address above requirements?
• For opportunity and opportunity products, system of records will be Salesforce.
• For orders, system of records will be ERP system
• All the opportunity and opportunity fields must be read only in ERP so that no one can modify those fields value
• Establish integration between Salesforce and ERP to send opportunity and opportunity products (e.g. outbound message)
• For integration use enterprise service bus
• Consider using Canonical Data Model
Scenario : 1
Integration CDM SOR

21. Aayu Ltd. is facing issues with duplicate records and discrepancies between Salesforce and multiple on premise systems. How Master Data
Management could help company to resolving issues?
• Advocate Master Management strategy to be in place
• Identify system of record for various data entities
• Find out gold record for data entities, keep in mind that it might exists in multiple systems
• Identify integration points between various systems
• Disable write access for certain fields in the systems where no one should update the records
Integration SOR SOT
Scenario : 2

22. Metadata Management

23. What is Metadata?
Metadata is information that describes various facets of an information asset to improve its
usability throughout its life cycle.
It is metadata that turns information into an asset. Generally speaking, the more valuable the
information asset, the more critical it is to manage the metadata about it, because it is the
metadata definition that provides the understanding that unlocks the value of data.
https://www.gartner.com/en/information-technology/glossary/metadata
In short, It's data about data

24. • Metadata Definition
• Metadata Types
Data Dictionary
Data Taxonomy
Data Lineage
Data Classification
Data Heritage
• Salesforce Features
Event Monitoring
Field History Tracking
Audit Trail
Custom Metadata Types
What You Will Learn Today!

25. Metadata Types
Data Dictionary
Data
Taxonomy
Data Lineage
Data
Classification
Data Heritage

26. Data Dictionary
A data dictionary (aka data glossary) can be said to be a business glossary designed for an organization’s IT staff. It
would show a listing of the key business concepts and their associated technical instantiations in a common
vocabulary
Data Entity Field
Name
Data Type Data
Format
Field Size Description Example
Contact First Name Text 25 First name
of the
contact
Tim
Contact Last Name Text 25 Last name
of the
contact
Jonson
Contact D.O.B. Date DD/MM/YY
YY
10 Date of
birth of
contact
10/12/1996
Contact Phone No. Integer Country
specific
validation
rules may
applied.
15 Phone No.
of contact
454545454
52

27. Data Taxonomy
Taxonomy is a way of classifying the information (or data) in a hierarchical
manner which further helps in finding the related information much more
efficient.
https://myanalyticsworld.in/taxonomy-in-data-governance/
Vehicle
Commercial
Vehicle
Passenger
Vehicle
Plane
Truck
Train
Car
Scooter
Cycle
Account
Suspect
Prospect
Customer

28. Data Lineage
Data lineage represents information about everything that has
“happened” to the data within an organization’s environment. Whether
the data was moved from one system to another, transformed,
aggregated, etc., ETL (extraction, transformation, and load) tools can
capture this metadata electronically.
• Data lineage is a representation of the path along which data flows from the point of its origin to the point of its usage.
• Data lineage is used to design and describe processes of data transformation and processing.
• Data lineage is recorded by representing a set of linked components such as data (elements), business processes, IT systems and
applications, data controls. These components could be presented on different level of abstraction and detail. Usually, such a lineage is
called a ‘horizontal’ data lineage.
https://www.ewsolutions.com/the-basics-of-data-lineage/
Business
Process
Business
Process
Business
Process
Data DataDataCRM ERP
Marketing
Reporting

29. Data Heritage
Data heritage represents the metadata about the original source of the data.
https://www.ewsolutions.com/metadata-management-fundamentals/

30. Data Classification
Restricted
Sensitive
Non-sensitive
Public
Data classification is the process of analyzing structured or unstructured data and organizing it into categories
based on the file type and contents.

31. Metadata Management : Salesforce features

32. Event Monitoring
❖ Logins
❖ Logouts
❖ URI (web clicks in Salesforce Classic)
❖ Lightning (web clicks, performance, and errors in Lightning Experience and the Salesforce mobile app)
❖ Visualforce page loads
❖ API calls
❖ Apex executions
❖ Report exports
All these events are stored in event log files. An event log file is generated when an event occurs in your organization
and is available to view and download after 24 hours. The event types you can access and how long the files remain
available depends on your edition.
https://trailhead.salesforce.com/en/content/learn/modules/event_monitoring/event_monitoring_intro
https://salesforce-elf.herokuapp.com/To view log files:

33. Field History Tracking
You can track the field history of custom objects and the following standard objects.
❖ Accounts
❖ Articles
❖ Assets
❖ Campaigns
❖ Cases
❖ Contacts
❖ Contracts
❖ Contract line items
❖ Entitlements
❖ Leads
❖ Opportunities
❖ Orders
❖ Order Products
❖ Products
❖ Price Book Entries
❖ Service Contracts
❖ Solutions
https://help.salesforce.com/articleView?id=tracking_field_history.htm&type=5

34. Audit Trail
The setup audit trail history helps you track the recent setup changes that you and other
administrators have made to your organization. This can be especially useful in
organizations with multiple administrators.
Gives information about who is creating, changing, or deleting certain fields in the past.

35. Custom Metadata Types
https://trailhead.salesforce.com/en/content/learn/modules/custom_metadata_types_dec/cmt_create
You can create your own declarative developer frameworks for internal teams, partners, and customers. Rather than building
apps from data, you can build apps that are defined and driven by their own types of metadata. Metadata is the information that
describes the configuration of each customer’s organization. Custom metadata records are deployable using packages.
Mappings: You can use custom metadata types to create associations between different objects. For example, you can create a custom
metadata type that assigns cities, states, or provinces to particular regions in a country.
Business rules: Salesforce has lots of ways to define business rules. One way is to combine configuration records with custom functionality.
For example, you can use custom metadata types along with some Apex code to route payments to the correct endpoint.
Master data: Say that your org uses a standard accounting app. You can create a custom metadata type that defines custom charges,
like duties and VAT rates. If you include this type as part of an extension package, subscriber orgs can reference this master data.

36. What You Learned so far Today!
• Metadata Definition
• Metadata Types
Data Dictionary
Data Taxonomy
Data Lineage
Data Classification
Data Heritage
• Salesforce Features
Event Monitoring
Field History Tracking
Audit Trail
Custom Metadata Types

37. Consideration of documenting metadata types with respect data architecture while working on Salesforce projects
• Standard Objects
• Custom Fields on the standard objects
• Custom Objects
• Custom Fields on the Custom objects
• Record Types
• Master Detail RelationshipsLookups
Scenario : 1

38. Mention the responsibility of the data stewardship manager while implementing Salesforce for their SalesService organization?
• Align with stakeholders to define SOR and SOT
• Create metadata repository as part of data architecture reference
• Run key reports to determine fields requires for business processes, e.g. check lead object’s fields so conclude lead scoring
• Review metadata xml files to remove any unnecessary fields and consolidate if possible e.g. account, contact object
• Review security model to due to impact on duplicate records if any e.g. Delete access for case merge
Scenario : 2

39. Thank You