Why is information modelling important?

During this blog post, we explain why information models can be important for an organization. In the previous blog post, we discussed what information modeling is, but to refresh your memories, here's a brief recap. Information modeling is the process of describing the data needed for a specific purpose, such as a website, an app, or a report. Data can include names, addresses, phone numbers, orders, inventories, and so on. Information modeling has many benefits, both for the analysis and the realization of information provision. Here, we mention a few.

Clear scope

An information model provides an overview of all relevant data within a certain context. It helps to delineate what is and is not within the domain, and to set priorities. For example, if you want to create a website for an online store, you need to know what data you need about the products, customers, orders, payments, and so on. You don't need to concern yourself with data that is not relevant to your goal, such as the salaries of the employees or the birthdays of the suppliers.

Less cost

An information model prevents redundant or missing data from being defined, which can cause problems later. It saves time and money in the design, construction, and maintenance of systems. For example, if you want to create an app for a restaurant, you need to know what data you need about the menu, reservations, reviews, and so on. You don't want to discover later that you've forgotten an important piece of data, such as allergens or opening hours. That would mean you have to adjust or rebuild your app.

Insight into complexity

An information model makes the complexity of the domain comprehensible before starting to build systems. It helps to identify and manage risks and to evaluate alternatives. For example, if you want to create a report for a school, you need to know what data you need about the students, teachers, subjects, grades, and so on. You also want to know how these data interrelate and what rules apply. This can be quite complicated. An information model helps you to make this clear and to choose the best solution.

Better data quality

An information model establishes the rules that data must comply with, such as definitions, formats, validations, and obligations. This improves the quality and reliability of the data. For example, if you want to create a form for a survey, you need to know what data you want to collect and how you want to process it. You also want the data to be correct and complete. An information model helps you to ensure this by indicating what each piece of data means, what it should look like, what it may or must contain, and how it should be filled in.

Better documentation

An information model gives meaning to data by linking them to concepts from the domain. It also maps the dependencies and relationships between data. This facilitates communication and understanding among stakeholders. For example, if you want to create a database for a library, you need to know what data you need about the books, members, loans, and so on. You also want everyone who works with these data to speak the same language and give the same meaning to these data. An information model helps you achieve this by showing what each piece of data entails, how it relates to other data, and how it is used.

Interoperability and consistency

An information model provides a common frame of reference for data, making them easier to exchange and reuse. It also ensures consistency and unambiguity in the naming and interpretation of data. For example, if you want to link a website to an app, you need to know what data you want to share and how you want to present it. You also want the data on both platforms to mean the same and be named the same. An information model helps you achieve this by ensuring a standardized and uniform way of handling data.

In summary, we can say that information modeling is a useful technique for describing and structuring the data needed for a specific purpose. It offers many benefits, such as a clear scope, less cost, insight into complexity, better data quality, better documentation, and interoperability and consistency. In the next blog post, we will delve into how to create an information model and what steps you need to follow.

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