{"id":19756,"date":"2022-11-08T14:43:26","date_gmt":"2022-11-08T13:43:26","guid":{"rendered":"https:\/\/careerfoundry.inbearbeitung.de\/en\/?p=19756"},"modified":"2023-09-05T15:52:38","modified_gmt":"2023-09-05T13:52:38","slug":"what-is-data-modeling","status":"publish","type":"post","link":"https:\/\/careerfoundry.inbearbeitung.de\/en\/blog\/data-analytics\/what-is-data-modeling\/","title":{"rendered":"What Is Data Modeling?"},"content":{"rendered":"

Data can be messy.<\/strong> <\/span><\/p>\n

This is often a headache for data analysts<\/span><\/a>. But understanding a dataset\u2019s structure and the relationship between different data points can also help you manipulate it to meet your business intelligence needs.<\/span><\/p>\n

To figure all this out, data analysts typically use a process known as data modeling. Data modeling allows you to dive deep into data, helping design, implement, and manage complex database systems. Data models also keep data analysts, software designers, engineers, and other stakeholders on the same page, ensuring everyone\u2019s needs are being met.<\/span><\/p>\n

These benefits sound great, but what exactly does data modeling involve? Why is it important? And what different types of data models exist?\u00a0<\/span><\/p>\n

Learn other data analyst skills in CareerFoundry’s free 5-day data short course<\/strong><\/a>.<\/p>\n

In this introductory guide, we\u2019ll answer all your questions, including:<\/span><\/p>\n

    \n
  1. What is data modeling?<\/span><\/a><\/li>\n
  2. Why is data modeling important?<\/span><\/a><\/li>\n
  3. Types of data models<\/span><\/a><\/li>\n
  4. The data modeling process<\/span><\/a><\/li>\n
  5. Examples of data modeling<\/span><\/a><\/li>\n
  6. Data modeling tools (and how to choose one)<\/span><\/a><\/li>\n
  7. Benefits and challenges of data modeling<\/span><\/a><\/li>\n
  8. Summary<\/span><\/a><\/li>\n<\/ol>\n

    Ready to demystify data modeling? Then let\u2019s jump in.<\/span><\/p>\n

    1. What is data modeling?<\/span><\/h2>\n

    Data modeling is the process of mapping how data moves from one form or component to another, either within a single database or a data management system. <\/span><\/p>\n

    Data modeling is a fundamental <\/span>data wrangling<\/span><\/a> and design task that should happen before any database, computer system, app, algorithm, or other data structure is created. By defining the relationship between different data elements and visually representing these, data modeling helps analysts build systems that are fit for purpose.<\/span><\/p>\n

    If this feels a bit abstract, it might help to think of data modeling as a little like designing a new building. Before an engineer constructs a block of apartments, they must first understand the different elements required and how these interact. Where will the windows and doors go? Where should the pipes come in and out of the building? Crucially, how do all these elements relate to one another? Only with these details mapped out can the engineer hope to create a solid structure that does what it is supposed to do.<\/span><\/p>\n

    Similarly, data modeling helps data analysts define everything they need to know about their data, from data formats and data flows to data handling functions. Only once they have all this information can they hope to create a solid structure that meets their needs.<\/span><\/p>\n

    Data modeling doesn\u2019t just serve an upfront purpose, either. Once a database is up and running, the model acts as an all-important reference guide. This allows future data engineers and analysts to understand the principles underlying the database\u2019s original design and construction, how it works, and how data is shared between different systems. This is important because no system or database stays the same. Imagine trying to upgrade a building without a blueprint explaining how it was constructed. It would be a bit of a mess!<\/span><\/p>\n

    While it\u2019s possible to create a database without first carrying out data modeling, it won\u2019t be nearly as effective. Backward engineering a poorly planned system takes much more time and effort than simply investing the necessary resources upfront.<\/span><\/p>\n

    2. Why is data modeling important?<\/span><\/h2>\n

    As we explained in section one, the main reason why data modeling is so important is that it informs data structures that are fit for purpose.\u00a0<\/span><\/p>\n

    However, data modeling offers numerous additional benefits. Some of these include:<\/span><\/p>\n