The issue of Data Governance vs. Data Management lies at the heart of the effective operation of organizations.
In a context where proper data handling has become a critical factor, these two key concepts have emerged to play a fundamental role in corporate data management.
Both data management and data governance have their own importance, and there are clear differences between the two. However, the reality is that their true power lies in their effective combination.
Thus, the union of Data Governance and Data Management can be a powerful driver of efficiency and informed decision-making in any company that relies on data for its operations.
Therefore, we propose to explore how, far from being interchangeable, these two approaches are, in fact, complementary pieces of the data management puzzle. Let's get started!
In summary, a first glance at the definitions of both disciplines reveals the first of the differences between Data Governance vs. Data Management.
On one hand, Data Governance is concerned with mapping the structures around data production. It establishes who the owners are, as well as the policies, methodologies, and metrics that govern data throughout its entire lifecycle. In short, Data Governance could be understood as all the processes that guide and coordinate activities around data.
In this sense, it covers at least the following 10 areas, following the description of Data Management conceived by the International Data Management Association:
On the other hand, Data Management deals with implementing everything established by data governance. Therefore, the operations encompassed as data management are concerned with controlling both the input of data and its transformation into valid information. Thus, the purpose of Data Management is to provide accurate reports and initiate data-based business decisions.
From the previous definition, it is clear that, when comparing Data Governance vs. Data Management, both disciplines have different scopes.
Data Management is responsible for defining the policies and controls to be implemented for data storage, manipulation, or use.
Some of the specific tasks to be addressed include establishing:
Conversely, Data Governance defines the tools, procedures, and methods for managing the data lifecycle. This involves the following specific tasks:
Data Governance mainly involves executive-level personnel and data governance committees that establish policies and oversee compliance.
On the other hand, data Management involves IT professionals and data analysts who work on the practical implementation of data policies. Purely technical positions appear here, such as data engineers, architects, or database administrators.
To implement a data governance process, technologies capable of documenting policies and rules are used: from data dictionaries and glossaries to catalogs.
In contrast, data management will need technologies related to data storage, processing, and exploration.
Effective Data Governance processes result in a set of policies, regulations, and a governance framework that ensures data quality and accountability.
In the case of Data Management, the final result is to have a solid data infrastructure, efficient processes, and high-quality data available for use.
As we have advanced above, Data Governance and Data Management are complementary: on one hand, Data Governance establishes the rules and guidelines, while Data Management implements them.
Thus, both are essential for effective data management and reinforce each other, ensuring the data cycle differently. If data governance ensures its viability, data management applies it.
Therefore, depending on the phase in which a business finds itself, it will have to resort to one methodology or another (or both, if it is a matter of carrying out an integral process).
In other words, the benefits of data governance are essential for any organization that seeks to optimize its data management and vice versa: data governance that does not take into account data management will be inoperative.
Beyond the differences between Data Governance vs. Data Management, organizations seeking to integrate both disciplines must have the appropriate computer tools.
These are delicate processes, in which issues such as compliance with Data Governance policies, as well as cost reduction, must be balanced.
From icaria Technology, we have developed our icaria Data Governance tool with the aim of helping organizations to implement the proper data control process, ultimately ensuring the quality of the data they handle.
Through this solution, we enable organizations to achieve full control over all processes in terms of managing, understanding, and sharing your organization's data.
To this end, the tool activates key functionalities such as efficient data discovery, secure and structured classification, improvement in data quality, and the possibility of effective collaboration (for example, through the creation of a business term dictionary).
Likewise, the tool takes care of the consistent management of data, ensuring the consistency of reference data and the coherence of structures between applications. With a focus on data uniformity, the tool is capable of applying standards and business rules, avoiding duplications. In turn, it ensures regulatory compliance and initiates audits in all actions taken, guaranteeing traceability.
At icaria Technology, we have worked to make our icaria Data Governance solution a crucial ally for companies seeking to leverage the full potential of data in a secure, efficient manner and in accordance with regulations.
If you want to know more about our tool, get in touch with our team and discover how we can help you achieve the structure and capabilities necessary to effectively manage your company's data assets.
