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 Cognite
Question: 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:
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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, create resources for specific units to manage data related to individual equipment or operational segments.
Example: US_COR_UNIT1, BR_SAO_UNIT3.
Example 02: Adding KPIs for an OEE (Overall Equipment Effectiveness) Solution
In this example, we may also want to track KPIs for OEE across the company’s operations.
Question: Should we create a unique SPACE for all sites and organize the information with containers, or should we segregate the SPACEs as shown in the example below?
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KPIs for Each Unit
Create a set of KPIs (such as availability, performance, and quality) for each unit within a site.
Example:
US_COR_UNIT1_OEE_Availability,
US_COR_UNIT1_OEE_Performance,
BR_SAO_UNIT3_OEE_Quality. -
KPIs for Each Site
Aggregate KPIs at the site level to get an overall view of the OEE for that specific site.
Example:
US_COR_OEE_Availability_Avg,
BR_SAO_OEE_Quality_Avg. -
KPIs for Each Country
Further aggregate KPIs by country to compare OEE performance across regions.
Example:
US_OEE_Availability_Avg,
BR_OEE_Performance_Avg.