Decoding Data Governance: 6 Essential Pillars

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Decoding Data Governance: 6 Essential Pillars

Data Governance

Business leaders of today’s data-centric world are faced with the need to effectively use their data to guide their business decisions.  As companies grasp the importance of and acknowledge the challenges associated with building a data-driven organization, more and more are turning to data governance as a solution.  

Implementing a robust data governance strategy turns the data into a corporate asset. Data Governance enhances data literacy, quality, and reliability, and security creating confidence in data as a foundation for business decision-making and successful outcomes in a competitive market.  

When organizations collect vast amounts of data, they need a framework that mitigates risks, reduces costs, and executes business objectives effectively.   

What is the Data Governance Framework?  

 A Data Governance Framework is a system that includes people, processes, policies, and technology that will ensure constant growth in all areas of data life cycle. Starting from data creation to transmission and usage, this system is a foundation for robust data strategy and compliance.  

  The DG framework will include the following:   

  1. People: Data governance is primarily about creating a change. And this is impossible without support from primary consumers of the data.  Recognizing and formalizing existing responsibilities for the data enables creation of Data Governance organization, where individuals are eager to see the improvement in data practices.
  2. Process: Data governance heavily relies on improving existing processes and creating additional processes that will support data maturity. Additional awareness of the existing processes allows for greater transparency and collaboration among teams eliminating siloes.
  3. Architecture: Seamless integration and data availability are an essential part of the Data Governance framework. Unifying data across sources gives a 360-degree view of business entities, supporting accuracy in business decision-making.
  4. Metadata Management: Creating and publishing company business glossary, defining critical data elements, documenting business KPIs all support data literacy and transparency supporting data intelligence and AI initiatives.
  5. Data Quality: DG enables organizations to establish regular quality checks, monitors metrics, and implements data cleansing procedures to identify and rectify errors and inconsistencies deriving actionable insights from their data.
  6. Security and Compliance: Data Security is an essential part of DG. It establishes data access controls to enforce data encryption protocols and monitor data usage patterns to prevent unauthorized access, data breaches, and data misuse. 

Bringing it all together  

Embracing a robust data governance strategy strengthens the integrity and security of organizational data while driving growth with informed decision-making.   

When creating a successful data governance framework for your organization, you need to create one that aligns with your organization’s goals and objectives by unlocking the transformative power of your data. For a successful implementation speak with our experts to tailor a governance framework that aligns seamlessly with your organizational goals.  

Empower your decision-making by unleashing the true value of data. Download your free guidebook now, “Business Intelligence Guidebook – From Data Integration to Analytics,” and uncover the secrets of data-driven transformation.  BI Guidebook

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