What is data modeling and why do I need it?

Data modeling is a crucial process for structuring raw, event-level data by applying business logic, making it easier to query and use, particularly for non-data experts within an organization. This process transforms unstructured data from multiple sources into structured, meaningful datasets that can be easily accessed and analyzed using basic SQL skills, thereby facilitating data-informed decision-making. The modeled data, which is mutable, reflects changes in business logic and can be tailored to specific organizational needs, unlike the immutable raw data stream that serves as a comprehensive, unopinionated archive. This approach democratizes data, empowering various teams to self-serve and create custom reports and dashboards that mirror the unique aspects of their business. By centralizing data and integrating it with business logic, companies can enhance their data maturity, enabling quicker responses to business questions and promoting a data-first culture. The process involves defining key metrics and business logic upfront, which provides more flexibility compared to pre-packaged analytics solutions, particularly for complex business models like two-sided marketplaces.