Fragmented inconsistent Customer data hides revenue recognition, introduces risk, creates sales inefficiencies, and results in misguided marketing campaigns and lost customer loyalty. According to Forrester, 92% of companies believe having an integrated view of customer data is either “critical” or “very important.” Only 2% have actually achieved that goal.
Why have only 2% of companies achieved a 360 Degree Customer view?
Because customer data integration (CDI) isn’t just about customer relationship management (CRM). Customer data is often created and maintained in non-CRM. Moreover data warehouse is an analytical solution, not an operational, transactional solution.
And building your own customer master application is too risky–and expensive. Building instead of buying will keep you mired in data model design for years.
MDM (Master Data Management) is the technical foundation of data management while Data Governance is its facilitating and supporting framework. More precisely, DG is a convergence of people, technology and processes that helps a business to manage the availability, utilization and security of their data assets.
SUMMARY
MDM is the technical foundation of data management while data governance is the overall business management framework that facilitates and supports technology implementations and ensures alignment with corporate strategy.
Governance has its own set of program components. In this context, a technology namely (Data Governance Manager) DGM is designed to facilitate data quality and data stewardship processes for the data steward. It provides an intuitive graphical user interface that acts as the single management destination and reference for data stewards and business users to manage customer data throughout various stages of the lifecycle.
Most companies do not combine data governance and MDM when getting started, so they fall short in addressing the people and process issues that cause data quality issue in the first place. Oracle’s Data Governance Manager simplifies and streamlines data stewardship
tasks and is a core tool for improving data quality –which is a key to MDM success.
DATA GOVERNANCE
Data governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.
A sound data governance strategy not only aligns business and IT to address data issues; but also, defines data ownership and policies, data quality processes, decision rights and escalation procedures.
Why have only 2% of companies achieved a 360 Degree Customer view?
Because customer data integration (CDI) isn’t just about customer relationship management (CRM). Customer data is often created and maintained in non-CRM. Moreover data warehouse is an analytical solution, not an operational, transactional solution.
And building your own customer master application is too risky–and expensive. Building instead of buying will keep you mired in data model design for years.
MDM (Master Data Management) is the technical foundation of data management while Data Governance is its facilitating and supporting framework. More precisely, DG is a convergence of people, technology and processes that helps a business to manage the availability, utilization and security of their data assets.
SUMMARY
MDM is the technical foundation of data management while data governance is the overall business management framework that facilitates and supports technology implementations and ensures alignment with corporate strategy.
Governance has its own set of program components. In this context, a technology namely (Data Governance Manager) DGM is designed to facilitate data quality and data stewardship processes for the data steward. It provides an intuitive graphical user interface that acts as the single management destination and reference for data stewards and business users to manage customer data throughout various stages of the lifecycle.
Most companies do not combine data governance and MDM when getting started, so they fall short in addressing the people and process issues that cause data quality issue in the first place. Oracle’s Data Governance Manager simplifies and streamlines data stewardship
tasks and is a core tool for improving data quality –which is a key to MDM success.
DATA GOVERNANCE
Data governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.
A sound data governance strategy not only aligns business and IT to address data issues; but also, defines data ownership and policies, data quality processes, decision rights and escalation procedures.
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