The model's Sales table has the following partitions: Partitionįiscal years 2010, 2011, 2012, 2013, 2014, 2015. For example, a tabular model can have a Sales table which includes sales data for the current fiscal year and each of the previous fiscal years. In many cases, such as with fact tables, dividing a table's single partition into multiple partitions can better utilize available resources for processing.Īn effective model design and processing strategy utilizes partitions to eliminate unnecessary processor load and memory consumption, while at the same time making certain that data is refreshed often enough to reflect the most recent data from data sources. Granularityīy default, each table in a model has a single partition. Individual partitions, each containing a unique segment of data, can then be incrementally processed either sequentially or in parallel independent of other partitions, or excluded from processing operations altogether. Partitions work by dividing a table into logical partition objects.

There's no need to process all of the data when only a portion of it needs to be processed. For example, a fact table may include certain row sets that contain data that rarely changes, but other row sets have data that changes often. Partitions divide portions of data you need to process (refresh) frequently from data that can be processed less frequently.

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