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Data Management Gap Analysis

Understand Where Your Journey Begins

Perform a Data Gap Analysis

Perform a Data Gap Analysis

Data management (DM) practices play a critical role in the success of your organization, but without a thorough understanding of the existing gaps, it can be challenging to make informed decisions and prioritize improvements effectively.
 

Conducting a comprehensive gap analysis of your organization's DM practices will provide insights into your current state, identify areas for improvement, and develop recommendations to bridge the gaps.
 

The gap analysis will cover the following areas:

 

Data Governance: Review your organization's data governance policies, procedures, and standards, and identify any gaps.
 

Data Quality: Evaluate the quality of data collected and maintained by your organization and identify any necessary remediations.
 

Data Security: Review your organization's data security measures and identify any gaps in your current security protocols.
 

Data Architecture: Evaluate your organization's data architecture, including data modeling and data mapping, and identify any gaps.
 

Data Integration: Evaluate your organization's data integration practices and identify any gaps in your current integration protocols.
 

Data Analytics: Evaluate your organization's data analytics practices and identify any gaps in your current analytics capabilities.

Key Deliverables

 

Gap Analysis: A comprehensive report detailing the results of the gap analysis, including a detailed analysis of your organization's current data management practices and identified gaps.

Suggested Enhancements: Recommendations for improving your organization's data management practices, including best practices, industry standards, and benchmarking data.

Roadmap: An implementation plan outlining steps your organization can take to address the identified gaps and improve your data management practices.
 

Scorecard & Maturity Model: A data management scorecard that can be used to track progress your over time and monitor your organization's data management practices.
 

Leadership Presentation: A presentation of the findings and recommendations to your organization's leadership team, stakeholders, and relevant departments.
 

Outcomes

  • Improved data quality, leading to more accurate and reliable decision-making.

  • Improved data security, protecting sensitive information from unauthorized access and potential breaches.

  • Increased efficiency and effectiveness of data management practices, leading to cost savings and improved business outcomes.

  • Improved risk mitigation and compliance with regulatory requirements and industry standards.

  • Enhanced data analytics capabilities, leading to better insights and more informed decision-making.

  • Improved stakeholder confidence in the organization's data management practices.

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Data Strategy

Having a well-defined data strategy is crucial for unlocking data’s full potential and creating value. Without one, you are at risk of missing opportunities, spending inefficiently on data resources, lacking alignment in data collection and analysis across departments, and more. 

 

We’ll develop a data strategy that aligns with your goals and focuses on optimizing your data infrastructure, management, and utilization.

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Establish your Data Governance Practice

Establish your Data Governance Practice

Operating even a modestly sized company without a data governance practice often results in poor data quality, compliance violations, security breaches, inefficient data management, and obscured insights.

 

We'll simplify the complex process of establishing a data governance practice and equip you with clear governance scope and objectives, a framework, and a team equipped with the right tools and processes for your business. 

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