Data Governance is Required in a Data-Driven Organization
Data governance’s Goal is to assure Data quality and integrity throughout the Data lifecycle, as well as regulatory compliance.
In an era when Data privacy, legislation and accountability are becoming increasingly important Data governance is required to specify how organisations utilise data, enable experiment repeatability and record and evaluate Data-Driven choices.
Data Governance's Advantages
Making Better Decisions
Ensure that judgments are based on accurate information.
Better Business Planning
Across the organization, Data-Driven decision-making
Improved Financial Results
Cost-cutting and profit-boosting strategic and operational decisions
Regulatory Compliance
Ensure that Data usage and security requirements are followed.
Enhance Security and Lower Risk
Improve Data handling techniques to reduce security breaches.
Data Understanding and Lineage
Confidence in the accuracy, reliability, and usability of Data for analysis.
Improved Data Consistency
Make the most of both organized and Unstructured Data in your business.
Reproducibility of Data Processes
Historical business decision transparency and accountability
What is the significance of Phoenix Intelligence?
Phoenix Intelligence provides the knowledge and experience to help policymakers and
practitioners meet regulatory obligations, decrease risk and get more value out of data.
Data services are customized to your company's requirements.
We can use any cloud or on-premises solution to deploy.
Migration and integration that is both safe and seamless.
Ensure that all Data channels are encrypted according to industry standards.
Business disruption is Small and quick.
Connect Data from various sources to get a better view of your organization.
Maintain and enhance the Integrity and quality of your Data.
Testing, validation, and reporting ensure complete transparency.
Developing a Framework for Data Governance
The methodology to developing a Data governance framework will be determined by the size of the organisation, the industry it operates in, the types of Data it collects, and regulatory constraints. The following are some of the most important phases in developing an effective Data governance system.
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