OneStream Planning: The Why, How and When

This article first appeared on the OneStream blog

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The Need for Speed

The pattern of Planners’ data interaction with OneStream is (roughly) as follows: retrieve, review, input, save, calculate, sum to totals, retrieve and then repeat, ending only when the Planning process is complete. The longest system step is typically around summing Entity Parents because the processing of tens of thousands (or hundreds of thousands or more) of Base Dimension data intersections to Parent hierarchy levels takes time to retrieve, compute in memory, and write to disk. Time-consuming or not, the ability to see the impact of inputs and calculations at summed hierarchy levels is key to understanding plan data. Implementors try to alleviate the time impact by making the Entity Dimension Consolidation process optional at a Form level, or by running it on a scheduled basis. These approaches may improve the User Experience but will delay analysis and may lead to data quality issues when those totals become stale and do not foot to base data.

Adding It Up

Happily, the mitigation strategies of scheduled or explicitly delayed processing are required only for the Entity-type Dimension; all other Dimension totals in OneStream are dynamic Aggregations. Entity is a stored hierarchy (largely for the purposes of true accounting-focused Financial Consolidations), and its totals can only be viewed after a Consolidation materializes them. The overhead concomitant with accounting principles and statutory requirements are not typically needed in a Planning application.

The release of OneStream 6.5 removes the need to perform a Consolidation to see data at Entity Parents by providing the option of a simpler Aggregation. Aggregations are fast.

What’ll It Do, Mister?

How fast? Using an example of a 17,000-Member Entity Dimension with two years’ worth of data (UD1 through UD6 were also populated), aggregating was seven times faster than consolidating.

Note: A 17,000-Member Entity Dimension is atypical in its size. A more reasonable Entity Dimension size of 700 saw a similar 83% improvement in speed. Fast, indeed. Of course, every Cube is different in size, density of data, and design of Dimensions, all of which impact Cube performance; therefore, actual performance in your Cube may vary.

Read the full excerpt here: OneStream Planning: Aggregated, Never (usually) Consolidated

Cameron Lackpour

Cameron Lackpour first worked with Corporate Performance Management technology in the dinosaur days of mainframe multidimensional databases and saw the OneStream light in 2017. He has been in the consulting business since 1996, creating solutions for customers using best of breed planning and analytic tools. Cameron blogs on and is a host on the podcast This is Cameron’s third book. He hopes you enjoy it.

Headshot - Pill - Calvin Kattookaran

Celvin Kattookaran

Celvin Kattookaran has more than 15 years of experience in Business Intelligence and Corporate Performance Management. He has successfully implemented enterprise-wide performance management solutions across many industries with heavy experience in the OneStream XF Platform and various Specialty applications. Celvin is an avid blogger and shares his ideas and utilities on his blog and is a host on the podcast

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