#73 What is Data modeling?
Data modeling sounds like a technical task related to data warehousing and data description. And this is true, but it is not the job of technical people. We interviewed company Ari Hovi (www.arihovi.com), one of Finland's leading data modeling companies, and their leading data model expert Mr. Hannu Järvi briefly stated that "the best data modeling project comes when top management, even the CEO, participates in the process". Briefly, a data modeling process that models and analyzes a company’s data needs and structure in relation to the company’s business model and processes. It is clear, therefore, that if this is left only to the shoulders of technical people, then when information is used, for example, to support decision-making, the value of the data cannot be harnessed or the data can be fully used for business purposes. And if you understand the need of data modeling, you should actively manage it as every other critical processes.
So what are the benefits of data modeling work? Many business leaders may not have thought of the entire data modeling as applying to them because the term has seemed technical and there is no full understanding of the value of high-quality data modeling and its holistic management. With the information system and structural architecture in mind, you can describe data modeling even as building construction plans or architecture, on the basis of which the whole is then started to be built. This saves time and money when understanding how the IT systems of different businesses or functions are interconnected and what are the key points in the architecture, for example in terms of data quality or strategic KPIs. This results in faster deployment of new information systems and changes, as well as performance and error minimization. While all of these factors listed above have a significant impact from many perspectives on a company’s business, the most undeniable benefit comes from the fact that properly constructed information modeling allows Business Intelligence (BI) to be leveraged effortlessly and systematically across businesses. Hannu Järvi states that "only a few Finnish companies do this with sufficient weight at the moment and this leads to the fact that global competitors will undoubtedly take the lead in utilizing data in companies. We are leaving behind.".
When data modeling is thought more as the foundation for all the utilization of data in companies, one has to think about whether a good house can be built without a foundation? If a company's data or artificial intelligence strategy does not contain the data modeling process and tasks into all key design and implementation processes, then the data cannot be fully utilized and there is a possibility that the data is then a mere cost item. Why not? Let's think about this. If you are doing procurement related to your IT system and IoT implementation and you are not able to model the integration of a new acquisition into your existing data structure, how do you know that it will not become a completely separate part or can all data be utilized everywhere where is needed? Or if you have had business KPIs used to build a product-based business and along with your entire industry you are moving toward a service-oriented business, i.e. your value proposition is changing, billing is changing, costs are changing and almost everything else in the company prior logic is changing, then how did you think to measure these in the future have not described at the data structure level?
So data modeling is all about business and you don’t want to lag behind global competitors.