Understanding Data Management Disciplines for Business Usage

Data management is now a crucial part of business as the value of high-quality data keeps growing. Professionals in various fields now have to understand at least the basics of data management in order to be efficient and competitive at what they do. Many firms do a lot of data collection and storing on their own, while others turn to Data-as-a-service, a.k.a. DaaS providers. However, even in the latter case, knowledge of how the main data management disciplines work is necessary to choose the right provider. Thus, let us go over these disciplines and their pivotal effect on business success.

The Main Data Management Disciplines

Discipline in academic or other knowledge-related context refers to a branch of knowledge or a field of study. As such, data management itself could be taken as a discipline about the methods, expertise, and modes of knowledge related to the theory and practice of handling data. However, handling of data is a very broad enterprise with many different features, thus data management consists of many more specific disciplines. It is just like with disciplines, for example, physics, which actually consists of many branches from thermodynamics to quantum field theory.

The list of subdisciplines can always be expanded as new distinctions in science appear. But at the moment we can distinguish the following main data management disciplines.

• Data governance. The main concern of this discipline is figuring out the guidelines for retaining the high quality of an organization’s data assets. Additionally, data governance ensures that data is used most efficiently at every stage of its life cycle to advance the organization’s main objectives.
• Data security. Concerned with the privacy and security of data, avoiding data leaks, and ensuring that sensitive information is used for the purposes it was approved to be used.
• Database and storing management. Data management disciplines also include those related to the hardware and software infrastructure needed for the safe and efficient storage of information.
• Data stewardship. This discipline is defined as a way of assigning particular data records to the people with the most knowledge regarding their utilization for business benefits. Additionally, data stewardship is concerned with generally improving the data flow within the organization.
• Data integration. This discipline is concerned with the ways in which data from two or more different sources can be integrated together and presented as a unified set of information.

An integral component of data management is the discipline of data matching. Data matching involves comparing data from different sources to find, link, or merge related entries. This process is crucial to eliminate inconsistencies, duplicates and improve the overall data quality. It aids in creating a unified, accurate view of data that supports all other data management disciplines. To properly master this discipline, a comprehensive data matching guide becomes an invaluable tool. For instance, data matching enhances data governance by ensuring data accuracy, it bolsters data security by reducing redundant information and supports data integration by aligning disparate datasets. Understanding the nuances of data matching thus contributes to creating efficient data strategies and reinforces the other disciplines in their respective roles.

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Aside from these subdisciplines, there can be many data management disciplines distinguished by the type of data they are primarily concerned with. An example of this could be metadata management. This also means that different disciplines can overlap in particular cases, as the same aspects of data handling can concern, for example, both metadata management and data governance.

Disciplines for Better Business Results

Now let us look at how understanding different data management disciplines can help improve data usage in business. Of course, most benefits come from knowledge in specific spheres of data management. But there are also advantages based on the general understanding of data management disciplines and how they differ from one another.

For example, knowing the difference between the disciplines will allow understanding what sort of professionals need to be hired to properly take care of data. Some might be proficient in data governance, while a whole different team will be needed to take care of questions relating to building a proper data infrastructure.

Having the necessary skillset in your team will help to use your data assets to the fullest. And the effective usage of data assets is especially crucial for small business productivity, in order to stay competitive and grow.

Additionally, knowledge of such disciplines helps to choose the right third-party data providers. Whether you need the assistance of DaaS providers or just some outside knowledge to improve data management, being aware of which discipline experts you need will ensure that firm resources are not wasted on something else.

Furthermore, general proficiency in data management theory helps to understand particular issues in each discipline better. Just like general understanding of physics enables one to tackle the problems of mechanics faster. Thus, knowing the main tenets of data stewardship and how it differs from data governance will allow finding the answers to the particular problems of each of these two subdisciplines.

Finally, data management disciplines follow the general principle of the division of labor. The work is done better when everyone concentrates on the task, they are best suited for. Understanding this will help to properly allocate resources for various data-related tasks.

Separated but Related

At the end of the data, it is also important to remember that ultimately all data management disciplines are interested in the same thing – efficient usage of data. Thus, despite all their differences, it is crucial to understand how they relate to and supplement each other.

The key ideas of data governance will also increase data security while metadata management rules can be valuable in data integration. Taking data management discipline by discipline will ultimately help to figure it out and reach the best results. If you wish for your company to enhance its mobility, flexibility, and efficiency, you can consider opting for a desktop-as-a-service provider.