The Water-Ecosystem of Data: Setting the Scene for Data Governance and Data Management

This is the second article in our Data Governance Series. If you missed the first, you can access it here [The Importance of Data Governance: A Vivid Comparison with Water]

Previously, we introduced the idea of how a data ecosystem can be compared to a water-ecosystem. In this article, we continue to explore this analogy, as it sets a scenic backdrop against which we can understand the practical purpose and objectives of Data Governance and Data Management.

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Understanding the underlying Ecosystem

When we turn on a tap and clean water pours out, we generally don’t stop to think about the complex infrastructure that is in place to make this possible. We generally also don’t question the safety of our tap water, assuming that whatever pours into our glass is perfectly drinkable and poses no threat to our health.

But how was the infrastructure created? And how does it continue to serve millions of people all over the world?

Most modern cities rely on a complex infrastructure that is the result of careful planning and significant government investment to build or maintain water-ecosystems. Public services also provide administrative services that are aimed at ensuring consumers have access to water when and where needed. Society has come to trust that the water in taps is safe because we expect that there are governance and management processes in place to assure the quality of the water.

Similarly, we should govern and manage our data practices to ensure that our data users can readily access the data they need and trust the insights derived from it.

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Practical view of Data Governance and Management

Building on this comparison and further unpacking the purpose and objectives of Data Governance and Management, there are some broad groups of services and activities that contribute to providing these complex services, such as: 

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     1.      Enable: Building new eco-system components

Imagine a growing company’s data solution needs as if it was a burgeoning town that needs an increasing supply of water. Just as a town needs new reservoirs, treatment plants, and pipelines, a data-driven organisation has an ongoing need to access new and different data from different sources and for different purposes.

Water governance sets standards for construction, ensuring each new addition fits the existing ecosystem. Similarly, data governance lays down rules for data solution engineering to ensure each new pipeline or report consistently complies with industry standards and regulations. The context and need for data changes and grows as a business evolves and grows. As the need increases, more data teams are established, and new data solutions are built. Governance standards ensure that irrespective of who builds a data solution in the organisation, the quality and reliability of each and every use-case improves due to consistent adherence to the governance framework.

Data management is comparable to the municipality working with construction managers and architects to oversee each active construction project. They manage every step their team members take to ensure they meet governance standards and pass inspections. Similarly, Data Managers, Project Managers, and Technical Leads direct and guide data engineering and analytics projects to ensure the reports and predictive models are reliable.

     2.      Maintenance: Ensuring ongoing Clean, Usable Data

In the realm of water services, maintenance involves constant vigilance over water quality and infrastructure integrity, swiftly addressing any issues to maintain long-term reliability and sustainability. Governance dictates the protocols for routine inspections and sets benchmarks for service response times, ensuring that standards are consistently met by the various teams responsible for maintenance of the infrastructure. Management functions ensure that monitoring and maintenance is carried out effectively, employing technology like sensors to track water usage and orchestrating maintenance teams to handle repairs efficiently, adhering to service agreements.

In parallel, data governance sets the policies for routine checks and balances, such as data quality audits and compliance reviews to prevent "data pollution”. Data Governance may also provide minimum standards for monitoring scheduled data pipelines to detect when they fail and then guide minimum standards for recovering and restoring problems to working features.

Guided by such governance standards, the data management function then leads people and teams to execute their maintenance duties of monitoring solutions, fixing breakdowns of data pipelines, investigating reported data errors and correcting them, and conducting data quality audits in alignment with the standards.

     3.      Effective Administration: The end-consumer lifecycle

In this final comparison, water system administration extends beyond physical maintenance of the infrastructure. It should also ensure good administrative services, like sending monthly water bills, processing payments and switching water connections on or off. The aim of governance in such scenarios, is to set clear usage rules for different consumer types and outline procedures for granting and revoking access to water. Management then ensures that administrative staff execute their daily duties of handling customer-service requests and billing accurately.

Similarly, data governance stipulates guidelines and criteria that guide who can access and use which data and for what purpose. It establishes policies guiding data lifecycle management, like archiving, back-ups, and recoverability, as well as responsible data handling such as sharing and deleting.

Data management leads the administrative functions, granting and revoking access to data and establishing clear procedures and methods for administrative staff to follow to ensure these activities are done in alignment with the standards, with the primary aim of providing an effective and efficient service to the end-user community.

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The Crucial Role of People in Data Ecosystems

At the heart of both water and data ecosystems are people … people who build, maintain, and administrate these systems; it is not the water, or the data, that the systems need to manage, but the people who operate these systems.

“Data Governance” should not be interpreted as “governing the data”, but rather, the focus of data governance is to guide managers on how best to manage the people who build, maintain, and administer data solutions. It also guides managers of people who capture or consume data for reporting or other purposes.

The primary objective of data governance is to clarify roles and responsibilities, providing clear guidance on what may and may not be done, and, in doing so, prevent regulatory missteps and ensure consistency and reliability to positively impact data and analytics.

In contrast to governance, the primary goal of data management is to maximise the value generated for the company from their data. Data governance guides data management to achieve this by making the standards and rules clear and practical.  

If you follow the same logical processes that are evident in a water ecosystem, data governance and data management will be as straightforward as filling a glass of water.

Just as a well-managed water system is essential for the health and well-being of a community, a well-governed data system is critical for the health and success of an organisation. At Calybre, we have the expertise to help organisations on their journey towards mature data governance and data management. Contact us here or reach out directly to find out more.

Additionally, stay tuned for future articles in this series as we continue to explore data governance and data management and how to implement these practices effectively in your organisation.