A n00b’s OneStream Journey No. 3 — OneStream XF Relational Blending 101, part 1

Introduction

This post is proof that my quite meager salesmanship skills are sometimes successful in convincing others to do my work. This time round, that means that my colleague Mike Gialanella agreed to write a guest post on XF’s relational blending. Thanks, Mike, for giving me the week off. And oh yeah, Gentle Reader, you too should thank Mike for writing about a really exciting and unique tool bit of functionality.

And with that, heeeeeerrrreeee’s Mike.

XF Relational Blending 101

When Cameron Lackpour asks you to write a guest blog post, the answer is yes. It is one of those things that you just can’t say no to. If Santa Claus asked you to deliver Christmas presents to kids-in-need, you would need an incredibly good reason to decline such a request.

XF networking event Nov 2017. Me on the right, Santa on the left.

So, for all you technical and finance experts that are attracted to Cameron’s wit and wisdom this blog, here’s my best-most-humble effort to deliver, by request of the man Cameron himself…. here you go:

OneStream XF is a unified SmartCPMTM platform solution, it is not a siloed set of solutions that are fused together. OneStream XF solutions can be expanded upon, extended, and in a very real sense – blended together to meet the needs of a data consumer.

  • XF Stage – this is a Relational Stage table (many tables) that is the destination for data that is imported to OneStream XF.
  • XF Financial Model – this is the Cube (one to many Cubes) for the Consolidation, Planning, and Analytic engine.
  • XF Framework – this is the vertebrae of the platform: Security, reporting interfaces, auditing, metadata management, etc…
  • The OneStream XF Workflow manages this process with fully customizable user tasks and steps to ensure data quality, accuracy, traceability, and auditing capabilities.
    • Where applicable you can setup a drill-back connector that executes SQL statements to see the source data in the external system.
    • In the case the Import/Load is a CSV or delimited file, you can see the source file in its original state before transformation. That is the dictionary definition of transparency.

OneStream XF combines Analytic, Stage, Relational, and Source transactional data in One Model. It provides a simple end user experience to collect and update detailed relational data. There is full auditability with all relational data naturally connected to analytic data and which is drillable. This permits the data to live where it belongs, not all data belongs in the cube. OneStream XF balances the right mix of where analytical and operational data resides for the best performance and analysis.

So that is a lot of words, here’s a diagram that has some arrows, database tables, cubes and other good visuals for those of you who don’t like to read and just look at pictures. Did anyone just read that sentence or did you jump right to the picture?

Data Blending

The example above is a simple illustration to show Stage data being loaded to a Cube. The reverse of which is the Drill Back to Source feature so data consumers can see the data in Stage before any calculation or translation is done on the source data.

Above is a single Stage table sending raw data to a Cube. Data in the Cube when applicable is consolidated, calculated, translated via FX rate table, reported on, audited, re-calculated, etc. The Cube View reporting interface is how a data consumer views data in OneStream. In the Data Explorer view the user can right-click on any cell to Drill Down to see how that number originated.

Right-click menu functionality from a Cube View: Drill Down on a data cell

Drill Down window: Right-click again to see Load Results for Imported Cell

Load Results for Imported Cell window: There’s a button here to Navigate to Source Data

This is basic XF functionality that requires no developer or consultant coding or special configuration. Here’s a step up from that simple 1-to-1 Stage table to Cube that shows how a single cube can be the target for multiple Stage tables. XF knows how the data got there and regardless of complexity or quantity of source systems and import channels, the tool knows where to go to provide the data consumer with full transparency and auditability of the data.

XF MarketPlace solutions that leverage Relational Blending capabilities

The OneStream XF MarketPlace is the download center for OneStream solutions, Software downloads, Release notes, Training videos… content for Customers and Implementation Partners. Here are 4 examples of how customers can extend the platform and, known or unbeknownst to them, use Relational Blending in the approach and solution.

OneStream XF People Planning

OneStream XF Thing Planning

OneStream XF Cash Planning

Reconciliation Control Manager

When would you use one of these Specialty Planning solutions? Note just because is says Planning in the name, does not mean these are only for Forecast or Budget scnearios. The Specialty solutions can be leveraged for Actual, What if, LRP, Flash, or any Scenario type that is in OneStream XF.

The OneStream Specialty Planning Engine (SPE) blends the relational data and analytic model

capabilities of the OneStream XF Platform. This creates a completely different way to approach the

unknown nature of the Specialty Planning process. The Specialty Planning Engine uses a relational table

to collect the items intended for planning (People, Things, Cash, etc.). This enables Data to live where it belongs – again, not all data belongs in the cube. OneStream XF balances the right mix of where analytical and operational data resides for the best performance and analysis.

So that is XF Relational Blending 101, simply to introduce the topic and provide the baseline for what it is. As a follow-up please stay tuned for part 2 – the 201 blog post where I’ll hit on the XF MarketPlace solutions noted above and also get in to some more detailed business cases, solutions, and report examples.

Conclusion

Right off, no one is allowed to say that Mike’s a better author than Yr. Obt. Svt. Where are the allusions to obscure US popular culture circa 1965? References to obsolete words that even the author is not fully sure is being used correctly? In(s)ane and wildly digressive rants? Nowhere, that’s where.

Oh, you wanted to actually get to the meat of a topic without all of that folderol? Ah. Perhaps Mike is the better author. Sob. But my humiliation is your profit. Mike has generously agreed to write another post on this subject so stay tuned.

Mike, again, thank you for putting in the time and sharing your knowledge.

Be seeing you.

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