Data Modeling – Approaches to Defining SPACEs In a hypothetical scenario where your company has more than 100 sites across different countries, each containing multiple units, it's important to organize data in a way that ensures scalability, flexibility, and ease of maintenance.We have our own perspective on the matter, but we would like to hear from other specialists, especially those experienced in data modeling approaches, like yourself. Example 01: Managing Employee Information Inside CogniteQuestion: Should we separate SPACEs for each site? Example Structure in Cognite Data Fusion:You can structure the SPACEs for your company’s sites and units as follows: Top Level: Country Create a SPACE for each country to organize data regionally.Example: US, BR, IN (for the United States, Brazil, and India). Mid Level: Site For each country, create separate SPACEs for each site within that country.Example: US_COR, BR_SAO, IN_BOM (COR for Corpus Christi, SAO for São Paulo, BOM for Mumbai). Low Level: Unit Inside each site’s SPACE, cre