Data Materialization

How to ensure correct rule behavior when using entity sorting
*NEW—includes video demonstration. Build Along with Board Follow along as we provide a demonstration to further illustrate the basic principles shared here. 1. Abstract Rules applied to an Entity are widely used in Board to support aggregation logic within reporting structures. A common example is a P&L Reporting Line…
On-the-fly Calculations: Pros and Cons
1. Abstract The term “on-the-fly calculation” refers to all the calculations executed directly at the layout level, meaning that the result is not physically stored in a Cube. This directly affects drill-down functionality and has advantages in terms of reducing the overall size. 2. Context During the development phase the…
Rule Consolidation
1. Abstract The rule is a key functionality that allows on-the-fly calculations between members of the same entity. The consolidation is a further step to physically store the result in the data model. This step is needed only in specific cases, usually when the calculated rows need to be reused as a source for following…

How to ensure correct rule behavior when using entity sorting
*NEW—includes video demonstration. Build Along with Board Follow along as we provide a demonstration to further illustrate the basic principles shared here. 1. Abstract Rules applied to an Entity are widely used in Board to support aggregation logic within reporting structures. A common example is a P&L Reporting Line…
On-the-fly Calculations: Pros and Cons
1. Abstract The term “on-the-fly calculation” refers to all the calculations executed directly at the layout level, meaning that the result is not physically stored in a Cube. This directly affects drill-down functionality and has advantages in terms of reducing the overall size. 2. Context During the development phase the…
Rule Consolidation
1. Abstract The rule is a key functionality that allows on-the-fly calculations between members of the same entity. The consolidation is a further step to physically store the result in the data model. This step is needed only in specific cases, usually when the calculated rows need to be reused as a source for following…

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See the Board Merchandiser Agent in action
Smarter merchandising planning with built-in AI Every season, merchandising teams need to decide where to invest, whether the plan is working, and where inventory risk needs action. Too often, those decisions happen in separate cycles. Category plans are set pre-season. Performance is reviewed later. OTB and WSSI risk is…
AI-native planning for decision-ready supply chains
When demand shifts, supply tightens, or costs change, supply chain teams need to respond quickly. But understanding the impact, comparing options, and aligning operations and finance can take too long. Fragmented plans, disconnected workflows, and manual coordination slow decisions across demand, supply, inventory, S&OP,…

See the Board Merchandiser Agent in action
Smarter merchandising planning with built-in AI Every season, merchandising teams need to decide where to invest, whether the plan is working, and where inventory risk needs action. Too often, those decisions happen in separate cycles. Category plans are set pre-season. Performance is reviewed later. OTB and WSSI risk is…
AI-native planning for decision-ready supply chains
When demand shifts, supply tightens, or costs change, supply chain teams need to respond quickly. But understanding the impact, comparing options, and aligning operations and finance can take too long. Fragmented plans, disconnected workflows, and manual coordination slow decisions across demand, supply, inventory, S&OP,…