Dynamic Cube Services are a set of features allowing developers and administrators to:

• quickly replicate finely-tuned slices of data from existing cubes to speed up reporting, without writing any code;
• create full Dimensions in code, which can automatically refresh according to custom conditions;
• expose any dataset as a cube, from any source, without having to physically load anything into our database;
• let users interact with such datasets through familiar tools like Cube Views, XFGetCells in Excel, XFDocs, and so on, without the need for custom Dashboards or Table Views.

How can we leverage these features in real-life applications?

USE CASES

Throughout our limited-availability program, we identified a number of exciting applications for this technology - and we expect to see many more emerging from the field. Here is a short list of use-cases already implemented with success:

• exposing large volumes of operational data (pre-aggregated with BiBlend) as dynamic cubes, which can be easily aligned with regular consolidation cubes to analyze results with higher granularity - without sacrificing performance;
• exposing custom relational data as cubes, dramatically simplifying user interaction via Excel;
• populating cubes with data coming from Solutions like People Planning, leveraging automatic aggregation to produce new insights;
• allowing power users to modify dimensions via Dashboards, as they prepare forecasting scenarios in an iterative fashion;
• rearranging existing structures for different reporting needs without having to physically duplicate data;
• meshing existing cube data with custom relational data, to implement custom allocation schemes and other tweaks;
• quickly producing alternate scenarios that apply different rates to existing cube data, without writing extra rules;
• implementing complex gatekeeping of collected data, by expressing conditions in code that can go beyond the capabilities of regular data-access features;
• report on historical data with different dimensionality, through BiBlend-produced snapshots of hierarchies that are then exposed dynamically.

We expect the creativity of our partners and customers will quickly surprise us with more and more applications!

THE TECHNICAL BIT

There are three main parts to DCS:

• Dynamic Data Binding: similarly to Hybrid Scenario, without any coding, administrators can quickly configure cubes that mirror existing ones. Data can be sliced with simple metadata filters, preaggregated to improve performance, or physically duplicated to quickly bootstrap a new cube.
• Dynamic Dimension Service: leveraging the Service Factory infrastructure already powering Dynamic Dashboards, developers and consultants can write code that will produce and refresh dimensions;
• Dynamic Data Service: again through the Service Factory paradigm and some code, one can populate Data Units with arbitrary values, turning any dataset into a cube!

To get familiar with these concepts, you can head to the relevant documentation, which has been revamped and expanded with the 9.0 release - including full API reference and examples in C# and VB.Net automatically available when the service files are created. We strongly encourage implementors to review these resources and reach out via the forums for questions.

Further material will be produced in the following months, including TechTalk episodes, so keep an eye out for them! We also ran a hands-on workshop at Splash in Nashville, which will likely feature again at Splash EMEA in London - where we will also discuss new exciting developments in this area.

IN CLOSING

DCS are a cornerstone of our Agile Financial Analytics strategy, empowering the Onestream ecosystem to work with complex, large, ever-changing data and unlock new business insights. Coupled with SensibleAI and Genesis, AFA will continue to evolve over the following months, as we help our partners and customers Take Finance Further.