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.
We offer online IT training with placements, project assistance in different platforms with real time industry consultants to provide quality training for all it professionals, corporate clients and students etc. Special features by InformaticaTrainingClasses are Extensive Training will be in both Informatica Online Training and Placement. We help you in resume preparation and conducting Mock Interviews.
Emphasis is given on important topics which are essential and mostly used in real time projects. Informatica training Classes is an Online Training Leader when it comes to high-end effective and efficient I.T Training. We have always been and still are focusing on the key aspects which are providing utmost effective and competent training to both students and professionals who are eager to enrich their technical skills.
Training Features at Informatica training classes:
We believe that online training has to be measured by three major aspects viz., Quality, Content and Relationship with the Trainer and Student. Not only our online training classes are important but apart from that the material which we provide are in tune with the latest IT training standards, so a student has not to worry at all whether the training imparted is outdated or latest.
Course content:
• Basics of data warehousing concepts
• Power center components
• Informatica concepts and overview
• Sources
• Targets
• Transformations
• Advanced Informatica concepts
Please Visit us for the Demo Classes, we have regular batches and weekend batches.
Informatica online training classes
Phone: (404)-900-9988
Email: info@informaticatrainingclasses.com
Web: http://www.informaticatrainingclasses.com
We offer online IT training with placements, project assistance in different platforms with real time industry consultants to provide quality training for all it professionals, corporate clients and students etc. Special features by InformaticaTrainingClasses are Extensive Training will be in both Informatica Online Training and Placement. We help you in resume preparation and conducting Mock Interviews.
Emphasis is given on important topics which are essential and mostly used in real time projects. Informatica training Classes is an Online Training Leader when it comes to high-end effective and efficient I.T Training. We have always been and still are focusing on the key aspects which are providing utmost effective and competent training to both students and professionals who are eager to enrich their technical skills.
Training Features at Informatica training classes:
We believe that online training has to be measured by three major aspects viz., Quality, Content and Relationship with the Trainer and Student. Not only our online training classes are important but apart from that the material which we provide are in tune with the latest IT training standards, so a student has not to worry at all whether the training imparted is outdated or latest.
Course content:
• Basics of data warehousing concepts
• Power center components
• Informatica concepts and overview
• Sources
• Targets
• Transformations
• Advanced Informatica concepts
Please Visit us for the Demo Classes, we have regular batches and weekend batches.
Informatica online training classes
Phone: (404)-900-9988
Email: info@informaticatrainingclasses.com
Web: http://www.informaticatrainingclasses.com
A Brief History of Information Technology
Databases for Decision Support
OLTP vs. OLAP
Why OLAP & OLTP don’t mix (1)
Organizational Data Flow and Data Storage Components
Loading the Data Warehouse
Characteristics of a Data Warehouse
A Data Warehouse is Subject Oriented
For more visit : http://jsbi.blogspot.com
Mdm for materials –positive impact of data quality improvementVerdantis Inc.
Agenda
• Introduction -Positive Impact of Data Quality Improvement
• Customer Case Studies
• Oil & Gas Service Provider –Global MDM Initiative for MRO and ETO
• Global Oil & Gas (E&P) SCM/Procurement Initiative
• Post Merger Material MDM Initiative
• Questions and Answers
Reconciling your Enterprise Data Warehouse to Source SystemsMethod360
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Know different types of tips about Importance of dataware housing, Data Cleansing and Extracting etc . For more details visit: http://www.skylinecollege.com/business-analytics-course
TrustedAgent GRC streamlines the complexity of obtaining security authorization from FedRAMP for cloud IaaS, PaaS, and SaaS services and applications. From tracking evidence and key control implementation to create key deliverables like security plans and managing continuous monitoring for ongoing compliance. TrustedAgent significantly reduces the amount of work to be done manually including managing vulnerabilities from ongoing compliance. Download and contact us to learn more how TrustedAgent GRC can create opportunities for your cloud offerings in the Federal Government.
A Brief History of Information Technology
Databases for Decision Support
OLTP vs. OLAP
Why OLAP & OLTP don’t mix (1)
Organizational Data Flow and Data Storage Components
Loading the Data Warehouse
Characteristics of a Data Warehouse
A Data Warehouse is Subject Oriented
For more visit : http://jsbi.blogspot.com
Mdm for materials –positive impact of data quality improvementVerdantis Inc.
Agenda
• Introduction -Positive Impact of Data Quality Improvement
• Customer Case Studies
• Oil & Gas Service Provider –Global MDM Initiative for MRO and ETO
• Global Oil & Gas (E&P) SCM/Procurement Initiative
• Post Merger Material MDM Initiative
• Questions and Answers
Reconciling your Enterprise Data Warehouse to Source SystemsMethod360
Implementing and an enterprise BI system is a significant organization investment. Too many times the expected benefit of that investment isn’t realized due to inconsistent data between the organization’s operational and BI systems.
This webcast will explain several options to enable your organization to leverage its investment by providing options to reconcile the data from source operational systems to BI.
Know different types of tips about Importance of dataware housing, Data Cleansing and Extracting etc . For more details visit: http://www.skylinecollege.com/business-analytics-course
TrustedAgent GRC streamlines the complexity of obtaining security authorization from FedRAMP for cloud IaaS, PaaS, and SaaS services and applications. From tracking evidence and key control implementation to create key deliverables like security plans and managing continuous monitoring for ongoing compliance. TrustedAgent significantly reduces the amount of work to be done manually including managing vulnerabilities from ongoing compliance. Download and contact us to learn more how TrustedAgent GRC can create opportunities for your cloud offerings in the Federal Government.
Slides from TFMA conference- April 2016 in Chicago.
Important considerations and metrics to leverage when deciding if you are ready to implement a consumption based model and ITFM process.
Join us as we take a deep dive into the architecture of the Salesforce1 Platform, explain how multitenancy actually works, and how it affects you as a developer. Showing the technology we use and the design principles we adhere to, you'll see how our platform teams manage three major upgrades a year without causing any issues to existing development. We'll cover the performance and security implications around the platform to give you an understanding of how limits have evolved. By the end of the session, you'll have a better grasp of the architecture underpinning Force.com and understand how to get the most out of it.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
Data Mesh is the decentralized architecture where your units of architecture is a domain driven data set that is treated as a product owned by domains or teams that most intimately know that data either creating it or they are consuming it and re-sharing it and allocated specific roles that have the accountability and the responsibility to provide that data as a product abstracting away complexity into infrastructure layer a self-serve infrastructure layer so that create these products more much more easily.
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In his Data Management Workshop at the 8th ETOT Summit in London, October 2016 - DataGenic's CTO Colin Hartley looked at trends and best practice when it comes to commodity data management. As well as sharing the dos and don'ts of forward curve creation and management.
Data Virtualization for Compliance – Creating a Controlled Data EnvironmentDenodo
CIT modernized its data architecture in response to intense regulatory scrutiny. In this presentation, they present how data virtualization is being used to drive standardization, enable cross-company data integration, and serve as a common provisioning point from which to access all authoritative sources of data.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/CCqUeT.
Achieving a Single View of Business – Critical Data with Master Data ManagementDATAVERSITY
Organizations today are critically reliant on data. However, as enterprise applications accumulate—often through digital transformation initiatives, new product launches, or mergers and acquisitions—business-critical data becomes increasingly siloed. As a result, organizations struggle to gain a complete view of customers, products, business partners, or other data domains scattered across legacy systems, cloud, databases, and spreadsheets—typically featuring unique ways of defining, modeling, and recording master data. Working with a network of vendors and suppliers, each with their own array of applications and data systems, only complicates the picture further. All of which inhibits an organization’s ability to realize value from their data. Master Data Management (MDM) allows organizations to consolidate data from multiple sources to create a single source of truth that provides a holistic view of enterprise-wide information. Join this webinar to discover how multi-domain MDM can eliminate the guesswork and uncertainty that results from data gaps and inconsistencies, paving the way for new, powerful insights through cross-domain intelligence.
Topics covered will include:
- Following a proven method to define and execute a data harmonization strategy that’s directly aligned with business objectives and outcomes
- Establishing a ‘contextually relevant’ golden record of consistent, valid, and accurate data across domains, applications, and services
- Creating linked relationships between data domains and surfacing up analytics on different data types to provide context and enable more informed decision-making
- Ensuring that your data governance strategy both complements and supports your data harmonization and consolidation approach
- Managing all administrative, stewardship, and governance functions across domains from a single user interface
- Allowing various user personas to utilize data and collaborate effectively with structured operating models that are ‘fit for purpose’
- Ultimately achieving a single view of critical data and related data elements that is easy to navigate
Understanding the Salesforce Architecture: How We Do the Magic We DoSalesforce Developers
Join us for a deep dive into the architecture of the Salesforce1 Platform. We'll explain how multitenancy actually works and how it affects you as a Salesforce customer. By understanding the technology we use and the design principles we adhere to, you'll see how our platform teams manage three major upgrades a year without causing any issues to existing development. We'll cover the performance and security implications around the platform to give you an understanding of how limits have evolved. By the end of the session, you'll have a better grasp of the architecture underpinning Force.com and understand how to get the most out of it.
Introduction to Data Warehouse. Summarized from the first chapter of 'The Data Warehouse Lifecyle Toolkit : Expert Methods for Designing, Developing, and Deploying Data Warehouses' by Ralph Kimball
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Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
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Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
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• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
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Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
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- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
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UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
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UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
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What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
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Test Automation with generative AI and Open AI.
UiPath integration with generative AI
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GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
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Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
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
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
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!
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/
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