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Data Governance Strategy

A data governance strategy is crucial for any major enterprise application programs such as ERP, CRM, or SCM as they allow your organization to effectively manage and utilize associated data assets.Our methodology provides a comprehensive approach to defining the most suitable governance strategy that aligns with your enterprise applications programs and objectives, covering the following key areas:

Business objectives: Aligning your organization's overall business objectives and with your data governance strategy.

Stakeholders: Identify the key stakeholders involved in your data governance strategy, including IT, legal, compliance, and other business units. Establish an organizational structure that creates an efficient framework for involving stakeholders in alignment with their respective roles and responsibilities.

Data policies: Establish data policies that clearly define the standards, procedures, and guidelines for managing data within the scope of your data governance strategy.

Data Quality Management: Establish the process of ensuring the accuracy, completeness, and consistency of data. This involves defining data quality metrics, monitoring data quality, identifying data quality issues, and implementing corrective actions. The primary objective of data quality management is to ensure that governed data is trustworthy.

Data Profiling: Analyze data to uncover its characteristics, such as data types, patterns, and relationships, in order to gain insights into the data quality, completeness, and consistency. Data profiling is often used to identify data quality issues and to determine the appropriate data cleansing strategies.

Data Cleansing: Identify and correct or remove data that is inaccurate, incomplete, or inconsistent. This involves using techniques such as data validation, standardization, and matching to improve the quality of data.

Data classification: Classify data based on its criticality and sensitivity to ensure that it is appropriately managed, secured, and used.

Security and privacy: Define security and privacy measures to protect sensitive data from unauthorized access.

Data governance framework: Establish a data governance framework that includes roles and responsibilities, decision-making processes, and escalation procedures.

Monitor and review: Establish regular monitoring and review procedures to ensure that your data governance strategy is effective, and identify areas that require improvement.


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