Master data management of customer data is key to strategic business success. Customer MDM provides a 360-degree view of the customer by consolidating, cleansing, standardizing, cross-referencing, governing, and sharing customer data across various business units and systems. Oracle's customer MDM portfolio includes purpose-built MDM applications and a customer hub that serves as the single source of clean customer data for an enterprise. Oracle has over 1,500 MDM customers across diverse industries that are leveraging its customer MDM innovations.
There’s growing recognition in the analyst community that reference data is a form of master data that requires its own governance. Locations, currency codes, financial accounts, and organizational hierarchies are so widely used in an organization that mismatches can result in: reconciliation issues, poor quality analytics or even transactional failures.
While it’s easy to see how poor reference data management (RDM) can cause problems, many companies struggle with determining how to get started. Multiple questions arise: What’s the scope? How should one choose between RDM solutions? How do I compute ROI? To answer these questions and more, Orchestra Networks teamed up with Aaron Zornes, Chief Research Office of the MDM Institute and Godfather of MDM, for: Everything you ever wanted to know about Reference Data (but were afraid to ask).
In this hour long webcast featuring Aaron Zornes (MDM Institute) and Conrad Chuang (Orchestra Networks) you will learn the:
Characteristics of reference data,
Key features of a reference data management (RDM) solution,
Lessons learned RDM implementations,
and more
MDM Institute: Why is Reference data mission critical now?Orchestra Networks
Learn why market-leading enterprises are focusing on RDM in this exclusive webinar from MDM research analyst Aaron Zornes
More than 55% of large enterprises surveyed by the MDM Institute are planning on implementing reference data management (RDM) in the next 18 months.
Why is RDM mission critical today?
How does RDM differ from (how is it similar to) MDM?
What are the top business drivers for RDM?
What are the “top 10” technical evaluation criteria?
Where are most organizations focusing their RDM efforts?
Aaron Zornes, Chief Research Officer of the MDM Institute, answers these questions and more when he reveals findings from the first ever RDM market study based on a 1Q2014 survey of 75+ global 5000 size enterprises.
Raphael Colsent describes National Bank's path to implementing their enterprise-wide MDM. National Bank is mastering data from over 500 domains and supporting their Basel II, CRM, and BI applications with EBX5.
Reference:
Colsenet, Raphael "National Bank MDM Initiative,"
Presentation from 2011 MDM and Data Governance Summit in Toronto, Canada, June 2011.
There’s growing recognition in the analyst community that reference data is a form of master data that requires its own governance. Locations, currency codes, financial accounts, and organizational hierarchies are so widely used in an organization that mismatches can result in: reconciliation issues, poor quality analytics or even transactional failures.
While it’s easy to see how poor reference data management (RDM) can cause problems, many companies struggle with determining how to get started. Multiple questions arise: What’s the scope? How should one choose between RDM solutions? How do I compute ROI? To answer these questions and more, Orchestra Networks teamed up with Aaron Zornes, Chief Research Office of the MDM Institute and Godfather of MDM, for: Everything you ever wanted to know about Reference Data (but were afraid to ask).
In this hour long webcast featuring Aaron Zornes (MDM Institute) and Conrad Chuang (Orchestra Networks) you will learn the:
Characteristics of reference data,
Key features of a reference data management (RDM) solution,
Lessons learned RDM implementations,
and more
MDM Institute: Why is Reference data mission critical now?Orchestra Networks
Learn why market-leading enterprises are focusing on RDM in this exclusive webinar from MDM research analyst Aaron Zornes
More than 55% of large enterprises surveyed by the MDM Institute are planning on implementing reference data management (RDM) in the next 18 months.
Why is RDM mission critical today?
How does RDM differ from (how is it similar to) MDM?
What are the top business drivers for RDM?
What are the “top 10” technical evaluation criteria?
Where are most organizations focusing their RDM efforts?
Aaron Zornes, Chief Research Officer of the MDM Institute, answers these questions and more when he reveals findings from the first ever RDM market study based on a 1Q2014 survey of 75+ global 5000 size enterprises.
Raphael Colsent describes National Bank's path to implementing their enterprise-wide MDM. National Bank is mastering data from over 500 domains and supporting their Basel II, CRM, and BI applications with EBX5.
Reference:
Colsenet, Raphael "National Bank MDM Initiative,"
Presentation from 2011 MDM and Data Governance Summit in Toronto, Canada, June 2011.
Master data management (mdm) & plm in context of enterprise product managementTata Consultancy Services
The presentation discusses the classical features and advantages of Master Data Management (MDM) system along with appropriate situations to use it. How do companies apply MDM who design, manufacture and sell their products in several geographies facing challenges in making appropriate decisions on their investment in PLM & MDM space?
Another important aspect covers the comparison/relation between a MDM system (or Product Master System) and Enterprise PLM system. How can you maximize your ROI on both PLM and MDM investments? With examples from different industries the key takeaways include whether your organization requires an MDM solution or not.
White Paper - The Business Case For Business IntelligenceDavid Walker
This white paper looks at the business case that should lie behind the decision to build a data warehouse and provide a business intelligence solution.
There are three primary drivers for making the investment in a business intelligence solution
1. Measurement and management of the business process
2. Analysis of why things change in the business in order to react better in the future
3. Providing information for stakeholders
As a consequence of the investment there will also be a number of secondary benefits that will help to justify the investment and these are also discussed. Finally there are a number of ‘anti-drivers’ – reasons for not embarking on a business intelligence programme.
Analyst field reports on top 20 MDM and Data Governance implementation partne...Aaron Zornes
(1) Determining the evaluation criteria for selecting implementation partners for MDM, RDM and Data Governance projects
(2) Identifying which partners are market leaders in your industry & your chosen software technologies
(3) Managing the partner relationship – esp. avoiding “brain drain” & inflationary “blended rates”
Creating an Effective MDM Strategy for SalesforcePerficient, Inc.
As Salesforce has grown from a simple, standalone tool to a platform that touches every customer interaction, the data has grown more complex. This problem happens for many reasons including user error, adding other cloud apps requiring data integration, and business mergers and acquisitions that create multiple instances of Salesforce within an organization.
A master data management (MDM) strategy is critical to helping companies solve challenges like providing enterprise analytics and creating a 360-degree view of the customer. With Informatica Cloud, companies are learning to address the challenges and explore alternatives including a cost-effective cloud MDM versus a full-blown MDM solution.
During this webinar, our experts demonstrated the Informatica cloud MDM solution in action and showed how with an effective strategy, you can:
-Support the business case for MDM consolidation of multiple instances
-Create a customer 360-degree view in the cloud
-Understand the use case, reference architecture, and why companies are choosing cloud-based MDM
Salesforce Master Data Management WebinarRajeev Kumar
Webinar on Salesforce Master Data Management covering the definitions,strategy, tools, architecture for MDM:
- What is Master Data Management (MDM)?
- Why use MDM ?
- Steps for implementing MDM in your organization
- Architecture Models of MDM
- Salesforce Data duplicity/DeDupe issue and ways to mitigate it
- Best Deduplication/ DeDupe tools for Salesforce CRM (Ex: Advitya)
Customer-Centric Data Management for Better Customer ExperiencesInformatica
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.
White Paper - Data Warehouse GovernanceDavid Walker
An organisation that is embarking on a data warehousing project is undertaking a long-term development and maintenance programme of a computer system. This system will be critical to the organisation and cost a significant amount of money, therefore control of the system is vital. Governance defines the model the organisation will use to ensure optimal use and re- use of the data warehouse and enforcement of corporate policies (e.g. business design, technical design and application security) and ultimately derive value for money.
This paper has identified five sources of change to the system and the aspects of the system that these sources of change will influence in order to assist the organisation to develop standards and structures to support the development and maintenance of the solution. These standards and structures must then evolve, as the programme develops to meet its changing needs.
“Documentation is not understanding, process is not discipline, formality is not skill”1
The best governance must only be an aid to the development and not an end in itself. Data Warehouses are successful because of good understanding, discipline and the skill of those involved. On the other hand systems built to a template without understanding, discipline and skill will inevitably deliver a system that fails to meet the users’ needs and sooner rather than later will be left on the shelf, or maintained at a very high cost but with little real use.
Master data management (mdm) & plm in context of enterprise product managementTata Consultancy Services
The presentation discusses the classical features and advantages of Master Data Management (MDM) system along with appropriate situations to use it. How do companies apply MDM who design, manufacture and sell their products in several geographies facing challenges in making appropriate decisions on their investment in PLM & MDM space?
Another important aspect covers the comparison/relation between a MDM system (or Product Master System) and Enterprise PLM system. How can you maximize your ROI on both PLM and MDM investments? With examples from different industries the key takeaways include whether your organization requires an MDM solution or not.
White Paper - The Business Case For Business IntelligenceDavid Walker
This white paper looks at the business case that should lie behind the decision to build a data warehouse and provide a business intelligence solution.
There are three primary drivers for making the investment in a business intelligence solution
1. Measurement and management of the business process
2. Analysis of why things change in the business in order to react better in the future
3. Providing information for stakeholders
As a consequence of the investment there will also be a number of secondary benefits that will help to justify the investment and these are also discussed. Finally there are a number of ‘anti-drivers’ – reasons for not embarking on a business intelligence programme.
Analyst field reports on top 20 MDM and Data Governance implementation partne...Aaron Zornes
(1) Determining the evaluation criteria for selecting implementation partners for MDM, RDM and Data Governance projects
(2) Identifying which partners are market leaders in your industry & your chosen software technologies
(3) Managing the partner relationship – esp. avoiding “brain drain” & inflationary “blended rates”
Creating an Effective MDM Strategy for SalesforcePerficient, Inc.
As Salesforce has grown from a simple, standalone tool to a platform that touches every customer interaction, the data has grown more complex. This problem happens for many reasons including user error, adding other cloud apps requiring data integration, and business mergers and acquisitions that create multiple instances of Salesforce within an organization.
A master data management (MDM) strategy is critical to helping companies solve challenges like providing enterprise analytics and creating a 360-degree view of the customer. With Informatica Cloud, companies are learning to address the challenges and explore alternatives including a cost-effective cloud MDM versus a full-blown MDM solution.
During this webinar, our experts demonstrated the Informatica cloud MDM solution in action and showed how with an effective strategy, you can:
-Support the business case for MDM consolidation of multiple instances
-Create a customer 360-degree view in the cloud
-Understand the use case, reference architecture, and why companies are choosing cloud-based MDM
Salesforce Master Data Management WebinarRajeev Kumar
Webinar on Salesforce Master Data Management covering the definitions,strategy, tools, architecture for MDM:
- What is Master Data Management (MDM)?
- Why use MDM ?
- Steps for implementing MDM in your organization
- Architecture Models of MDM
- Salesforce Data duplicity/DeDupe issue and ways to mitigate it
- Best Deduplication/ DeDupe tools for Salesforce CRM (Ex: Advitya)
Customer-Centric Data Management for Better Customer ExperiencesInformatica
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.
White Paper - Data Warehouse GovernanceDavid Walker
An organisation that is embarking on a data warehousing project is undertaking a long-term development and maintenance programme of a computer system. This system will be critical to the organisation and cost a significant amount of money, therefore control of the system is vital. Governance defines the model the organisation will use to ensure optimal use and re- use of the data warehouse and enforcement of corporate policies (e.g. business design, technical design and application security) and ultimately derive value for money.
This paper has identified five sources of change to the system and the aspects of the system that these sources of change will influence in order to assist the organisation to develop standards and structures to support the development and maintenance of the solution. These standards and structures must then evolve, as the programme develops to meet its changing needs.
“Documentation is not understanding, process is not discipline, formality is not skill”1
The best governance must only be an aid to the development and not an end in itself. Data Warehouses are successful because of good understanding, discipline and the skill of those involved. On the other hand systems built to a template without understanding, discipline and skill will inevitably deliver a system that fails to meet the users’ needs and sooner rather than later will be left on the shelf, or maintained at a very high cost but with little real use.
This presentation will cover the definition of Master Data Management, describe potential MDM hub architectures, outline 5 essential elements of MDM, and describe 11 real-world best practices for MDM and data governance, based on years of experience in the field.
Software Outsourcing: Pitfalls and Best PracticesSitrusLLC
When to outsource (and when not to)
Typical projects
Key issues with outsourcing
Most common reasons projects fail
Best practices
Questions to ask your potential partner
Presentation of use cases of Master Data Management for product Data. It presents the five facets of MDM for product Data (MDM for Material, MDM for Lean Managed Services, MDM for Regulated Products, Product Information Management, MDM for “Anything”) and how Talend platform for MDM can adress them
resentation of use cases of Master Data Management for Customer Data. It presents the business drivers and how Talend platform for MDM can adress them.
Business Integration for the 21st Century Bob Rhubart
Service Oriented Architecture has evolved from concept to reality in the last decade. The right methodology coupled with mature SOA technologies has helped customers demonstrate success in both innovation and ROI. In this session you will learn how Oracle SOA Suite's orchestration, virtualization, and governance capabilities provide the infrastructure to run mission critical business and system applications. And we'll take a special look at the convergence of SOA & BPM using Oracle's Unified technology stack.
Innovations in Grid Computing with Oracle CoherenceBob Rhubart
Learn how Coherence can increase the availability, scalability and performance of your existing applications with its advanced low-latency data-grid technologies. Also hear some interesting industry-specific use cases that customers had implemented and how Oracle is integrating Coherence into its Enterprise Java stack.
Trending use cases have pointed out the complementary nature of Hadoop and existing data management systems—emphasizing the importance of leveraging SQL, engineering, and operational skills, as well as incorporating novel uses of MapReduce to improve distributed analytic processing. Many vendors have provided interfaces between SQL systems and Hadoop but have not been able to semantically integrate these technologies while Hive, Pig and SQL processing islands proliferate. This session will discuss how Teradata is working with Hortonworks to optimize the use of Hadoop within the Teradata Analytical Ecosystem to ingest, store, and refine new data types, as well as exciting new developments to bridge the gap between Hadoop and SQL to unlock deeper insights from data in Hadoop. The use of Teradata Aster as a tightly integrated SQL-MapReduce® Discovery Platform for Hadoop environments will also be discussed.
See how mid-market companies can take advantage of tools like Microsoft Business Intelligence and Oracle OBIEE as a base to their program and use Kalido to provide the agility that those tools can’t.
Watch the webinar replay at www.kalido.com/road-to-agility.htm
Never Upgrade Again With Siebel Innovation PacksJerome Leonard
Were you at Open World 2011? This presentation addresses one of the top issues on CRM stakeholders minds : Never Upgrade Again With Siebel Innovation Packs