Data Governance: One of the best tools you have

 


As we continue to remove the mystery around data strategies, we will spend the next few weeks diving into the components and principles that make up data strategies.  My hope is that as you start putting the pieces of this puzzle together in your own mind, you will start to see that with a methodical and measured approach, a solid data strategy is within your grasp. 

Today, we are going to start focusing on data governance.  Data governance is a key component of a successful data strategy. It ensures data reliability, security, and usability throughout an organization. Data governance manages data from creation to deletion. It involves defining roles, responsibilities, processes, policies, and standards that guide data management and protection.

But don’t worry.  We are going to take our time.  Today, we will cover data governance at a high level, and as the days go by, we will get into the details.  When we are done, you will all have greater confidence in Data Governance, and I hope you will have a desire to find ways to implement it in your own organizations.

The Pillars of Data Governance:

Data governance is built on these key pillars.  How strong your overall data governance execution is will be determined by how completely you are able to accomplish these things:

  1. Data Quality: Data quality focuses on ensuring data accuracy, completeness, consistency, and reliability. It uses standards, validation rules, monitoring, and cleansing techniques to prevent errors.
  2. Knowledge Sharing (Data Catalogs and Data Glossaries): This pillar focuses on making data discoverable and understandable for business users. Data catalogs provide an inventory of data assets with metadata. Data glossaries define key terms and concepts, ensuring a shared understanding of data across the organization.
  3. Data Lineage: This pillar tracks data from its source to its destination, including any transformations or modifications. It provides a comprehensive view of how data flows through systems, enabling transparency and accountability.

How the Pillars Weave Together:

Why do we care about these seemingly independent areas of data?  On the surface, they seem related but not cohesive.  The fact is that these three pillars work together to create an understanding of the data that the business can trust.

  • Data Quality: High-quality data enables accurate analysis and decision-making.
  • Knowledge Sharing: Data catalogs and glossaries make data accessible and understandable, allowing users to find and utilize the data they need with confidence.  For a business user, this is just as important as if the data is correct because we are transferring all of the technical knowledge of the data to the business.  This step puts the business in the driver's seat.  If they see a transformation that is not right or an improper business rule being applied, they have the power to correct that with this pillar. 
  • Data Lineage: Data lineage provides transparency into the data's origin and transformations, reinforcing trust in its accuracy and enabling traceability for auditing and compliance purposes.

Empowering the Organization Through Data Governance:

Here comes another why.  Why do we, as technicians, care about making the organization smarter about its data?  Shouldn’t they just take what we give them and be happy?  The answer to that boils down to one simple fact.  Most technicians do not have a strong business sense.  We can make the data presentable, we can create the relationships within the data, but the business is what makes the relationship to the business objectives.  They provide the critical information that turns our well-crafted data platform into actionable processes.  So, how does data governance do that?  In a few ways, actually:

  • Early Detection of Data Quality Issues: Teams can use data governance policies and procedures, along with data quality monitoring tools, to identify and address data quality issues at the source.
  • Departmental Data Ownership: Data governance assigns data ownership to specific departments or individuals, making them accountable for data quality. This encourages responsibility and proactive data management.
  • Delegated Security: Data governance allows delegating security responsibilities to data owners, enabling them to define and manage access controls and permissions. This protects sensitive data while granting access for business needs.

The Foundation for Self-Service BI:

Have you ever wondered what was at the end of a successful data strategy?  I mean, really, why are we doing all of this?  When we leave work and know that the business can make data-informed decisions without us, that is when we will have reached the peak implementation of our data strategy.  That is not to say that we will not be needed, because the data platform that is needed to reach this goal will always need nurturing and care, but if a department can start thinking of a way to improve and access our system without us and figure out how to do that, then we have done our job.

What I just described is known as self-service BI.  Creating a capability for a business user to piece together different departments' data on their own, and return a reliable result to take action on.  Data governance is the foundation for self-service BI.  Without robust data governance, self-service BI can lead to data inconsistencies, inaccuracies, and security risks.

By establishing clear policies, procedures, and standards for data quality, data sharing, and data lineage, data governance ensures the data used for self-service BI is trustworthy. This empowers business users to generate accurate insights and make informed decisions, fostering a data-driven culture.

In essence, data governance builds trust in data assets. This trust is essential for empowering business users with self-service BI capabilities, unlocking the full potential of data, and driving business success.  This is our nirvana, and over the next few weeks, we will dive deep into how you can get there.

As a side note, I need to ask you, my readers, for some help.  If you find what I have to say helpful, please share my posts on whatever social media site you found me on.  My goal is to help as many people as I can, but I can only do that with your help.

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