Active Data Governance
Continuous Data Quality
Improved Business Processes

Organizations strive to exercise positive control over the processes, assets and methods used by their data stewards and custodians to manage global data. Data governance offers the collaborative framework for strictly managing and defining these enterprise-wide policies, business rules and assets in order to provide the required level of control.

Traditionally, data governance and data quality have, to some extent, been separate disciplines. Collibra’s Data Governance Center unlocks extremely significant benefits to tightly integrating these initiatives in order to ensure accountability and positive business results. It provides full cycle data governance by enabling:
• business data stakeholders to define policy;
• operations team members to implement that 
policy through business rules and data quality rules;
• data stewards to enforce policy compliance through issue management and data quality reporting.

The aim is for organizations to maximize the value of enterprise data as an asset by improving risk management and ensuring good data governance best practices to make it easier to monitor and manage customer and multi-domain data. In parallel, they can also reduce operational costs, improve customer retention, and ensure a laser focus on data governance and data quality without the need to implement large, costly and far-reaching hardware and software application/architecture solutions.

“You can’t improve the quality of data if you can’t get business stakeholders to define what quality means – data governance is the forum to accomplish that.”

Make your rules and policies accessible and visible

Collibra offers a business-focused collaboration platform that is used by business stakeholders and data stewards alike to define business policies, definitions, business rules and data quality metrics to link these to the actual results of data quality measurements.
By combining your data quality initiatives within a broader data governance context, it’s possible to gain enormous business benefit. Once the data quality process is deeply integrated and integral to your data governance initiative, data quality improvement efforts become more effective in providing the necessary visibility into your organization.

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Data quality Reporting

The implemented governance model also enables you to intelligently aggregate data quality scores into business-meaningful dashboards that answer questions such as:
• What is the quality of the data for “Customer”?
• How complete is the data that flows into your product MDM Hub?
• Is the completeness score improving for all the data?
You can now easily report data quality outputs (thresholds, failing rows, quality scores, etc.) to nominated data owners and data stewards across different parts of the organization. This includes the ability to enable organizational roll-up (e.g., comparing sales versus finance data thresholds across different lines of business).

Business driven issue management

Collibra’s business-facing collaborative environment allows business stakeholders and data stewards to easily become involved in resolving data issues. Collibra will intelligently route issues to the correct stakeholders on the basis of your data governance operating model.
You can then easily configure different issue resolution processes depending on the type of data, type of issue, its criticality and so on. 
The impact of data governance has made data quality more relevant than ever to the business user, who requires increased accessibility and visibility into data and information.

DQ-issuemanagement
"Information Governance originally started as an IT initiative. After the groundwork had been established, ownership for governance was then moved into the business. "

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