March 26, 2024

Elevating Data Governance With Unified Data Models

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In the era of data-driven business, effective data governance is pivotal to any organization’s success. It ensures that high quality data is available, usable, and secure, facilitating trustworthy and reliable business operations and decision-making. Implementing a data warehouse and establishing unified data models can significantly enhance an organization’s data governance posture.

What do we mean when we talk about “data governance”? It ultimately comes down to the organisation’s data is ingested, stored, handled, and consumed in a manner that ensures the data is consistently interpreted across the organisation, is securely and safely consumed, and maintains relevance and integrity.

It is a long journey to improving an organisation’s data governance posture, but it is one which is becoming business critical.

Establishing a Single Source of Truth

Everyone has heard of, and most have used the term “Single Source of Truth”, but for most organisations it is as much a concept as it is a way of designing, operating, and managing not just the data outputs but the end-to-end of the data lifecycle.

To begin the journey, it starts with looking at how data is handled, and stored.

A data warehouse consolidates data from a variety of sources into one comprehensive database thereby reducing data inconsistencies and discrepancies that can compromise data governance.

In a time when many organisations have multiple systems with varying degrees of interconnectedness it becomes even more important to bring the data together in a single data warehouse to mitigate business risk from poor data governance.

We have seen instances time and time again where inconsistent or inaccurate data is presented but all sources believe their data to be correct because it is coming from the same “system”.

Once the need for a data warehouse has been established it is important to consider how that data is efficiently stored, and ultimately consumed.

A data warehouse provides a historical context for data, allowing for the tracking and auditing of data changes over time – a critical aspect of data governance. Also, it enhances data security by providing a centralized area for applying access controls and monitoring data usage.

Having now established a central “source” with visibility, and auditability of the data, and its usage your organisation is making big strides towards improving its data governance posture.

Creating Consistency With Unified Data Models

Once your organisation’s data has landed in the data warehouse it does not end there. There is not a lot of benefit of having a data warehouse if the data is inconsistent, disjointed, and needs to be constantly manipulated for usage.

With most organisational data usage now involving data from multiple operations, functions, and processes ensuring that this data is brought together in a consistent manner where all users have the same understanding of what the data means, how to use the data, and where the data comes from is key.

The next step is to establish data models, and unified or consolidated data models. A unified data model presents a consistent view of business data across the organization. This standardizes data definitions, metrics, and attributes, reducing misunderstanding and misuse of data.

By implementing unified data models, organizations can ensure that all users understand data in the same way, regardless of the business unit or role they belong to. This consistency is key to effective data governance as it ensures data reliability and aids in compliance with regulatory standards. The last thing any organisation wants is for two users to interpret the same data differently thereby creating a risk that data might be misused unknowingly.

Enabling Effective Data Governance

By utilizing a data warehouse and unified data models, organizations can overcome many of the challenges associated with data governance. Here are a few specific ways these tools can benefit data governance:

Data Quality: A data warehouse can help improve data quality by eliminating duplicates, correcting errors, and ensuring consistency. A unified data model further enhances data quality by standardizing definitions and attributes.

Data Security: Both tools can enhance data security. The centralized nature of a data warehouse allows for effective implementation of access controls, while a unified data model can help identify sensitive data that needs to be protected.

Regulatory Compliance: A data warehouse provides a historical record of data, which can assist in audit trails and regulatory compliance. Unified data models can ensure that data is consistently classified and managed according to regulatory requirements.

Ensure your organisation maintains a strong data governance posture and is leveraging its data effectively, contact us today to learn more!



Jeff Stubbs

Jeff is the founder of Zentrix, a leading provider of Business Intelligence solutions for SAP. Known for his professionalism and reliability with over 20 years of experience, Jeff has spearheaded many transformative projects for clients, enhancing decision-making and business performance across industries. Through his blog, Jeff shares valuable insights into data analytics, systems integration, and business intelligence, offering practical advice for navigating the evolving SAP BI landscape. Follow Jeff for IT insights and updates, and discover how Zentrix is revolutionizing SAP BI solutions.