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Data Governance: what does it do?
WHAT does Data Governance mean, and what does it do?
Data Governance means "the exercise of decision-making and authority for data-related matters."
More specifically, 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."
When people refer to Data Governance, they might be talking about
• organizational bodies
• rules
• decision rights (how we "decide how to decide")
• accountabilities, or
• monitoring, controls, and other enforcement methods.
Data Governance programs can differ significantly, depending on their focus (on Compliance, on Data Integration, on Master Data Management, etc.) Regardless of the "flavor" of governance, however, every program will have essentially the same three-part mission :
to make/collect/align rules,
to resolve issues, and
to monitor/enforce compliance while providing ongoing support to Data Stakeholders.
WHEN do organizations need formal Data Governance?
Organizations need to move from information governance to formal Data Governance when one of four situations occur:
1. The organization gets so large that traditional management isn't able to address data-related cross-functional activities.
2. The organization's data systems get so complicated that traditional management isn't able to address data-related cross-functional activities.
3. The organization's Data Architects, SOA teams, or other horizontally-focused groups need the support of a cross-functional program that takes an enterprise (rather than siloed) view of data concerns and choices.
4. Regulation, compliance, or contractual requirements call for formal Data Governance.
WHO is involved with Data Governance?
Data Governance is of concern to any individual or group who has an interest in how data is created, collected, processed and manipulated, stored, made available for use, or retired. We call such people Data Stakeholders. Often, Data Stakeholders are OK with letting various IT Management and Data Management teams decide how to do the tasks we've listed above. But sometimes, these activities require decisions that really should be made by groups of stakeholders according to an agreed-upon process for making those decisions; that's when Data Governance comes into play. Such decision-making (and other activities) are facilitated and coordinated by centralized resources; in The DGI Data Governance Framework, we describe a Data Governance Office (DGO). We also describe roles and responsibilities for Data Stewards across the organization
For more reading: http://www.datagovernance.com/adg_data_governance_basics.html
Data Governance software generally falls into three categories:
Team workspaces
Repositories holding policies, business rules, data definitions, metadata
Data Management, MDM, ETL, or Data Quality software that includes governance or stewardship functionality.
It can be difficult to develop apples-to-apples comparisons of products and services, especially for offerings in category #3. Here are some tips to help you build questions, set requirements, and evaluate software. First, start with the basics. For Data Governance tools - just like for any other type of application - start with standard tool selection criteria and considerations:
vendor information
pricing
maintenance costs and other costs
functionality and features
suites versus stand-alone tools
best-of-breed considerations
customer service
implementation assistance
training
availability of consultants and the depth of consulting experience available
vendor stability
merger and acquisition considerations.
More reading: http://www.datagovernance.com/software.html
Using Informatica Convert Data Into a Strategic Business Asset with Data Governance
The Informatica solution for data governance is based on lean and agile data management principles. It quickly brings to life your organization’s data governance policy. The solution focuses on improving data quality, protecting sensitive data, promoting the efficient sharing of information, providing trusted business-critical data, and managing information throughout its lifecycle. This unique approach to data governance is underwritten by a set of implementation best practices that minimize risk and deliver business value quickly.
The Informatica solution for data governance converts enterprise data into a strategic asset that can be used to create competitive advantage and drive economic value. This solution serves as the foundation for an effective data governance program.
Improve financial performance
Increase operational effectiveness and efficiency
Fully comply with regulatory requirements
For more reading: http://www.informatica.com/ca/solutions/enterprise-data-integration-and-management/data-governance/
Meta data manager
Manage Change Effectively In Enterprise Data Integration Environments
Metadata Manager is a key feature of Informatica PowerCenter Advanced Edition. It collects metadata from across data integration environments and provides a visual map of the data flows within that environment. Metadata Manager, along with Business Glossary, provides the visibility and control needed to manage change, reduce errors caused by change, and ensure data integrity.
Enhance the management of data integration change and reduce the errors caused by change
Increase IT productivity by making it easy to scope projects and understand the impact of proposed data integration changes before they are implemented
Ensure regulatory compliance by avoiding errors and by providing a complete audit trail of data flows and transformations
More reading:
Metadata Management for Holistic Data Governance
http://www.informatica.com/Images/02163_metadata-management-data-governance_wp_en-US.pdf