Real-Time Reporting
Most Eagle clients design data workflow to follow a daily cycle:
Once markets close and regular-hours trading ends, the daily accounting update cycle sees trades updating positions, prices applied to create market values and reference and analytical data updated. Accounts are reconciled and submitted for automated and manual error checking.
When this activity is complete, end-of-day processing such as entity builds commences, with performance measurement calculations usually coming last. Further data QA and approvals take place.
With all warehouse contents in a validated state, clients build their Mart and use it to deliver enriched information during the ensuing business day.
In an ideal world, there would be no reason to make further changes to data values updated as of past completed business days. However, this is not the case in the real world. Vendor data corrections impact previously loaded security information. Late trades and trade reversal/re-entry activity affect accounting data values in the open accounting period.
It is physically possible to use Process Manager to build a workflow that automatically detects every such intra-day data change and updates the Mart accordingly soon afterward. However, such a “real-time” Mart is likely to produce undesirable results, primarily for two reasons:
A real-time approach may allot insufficient time for data QA, especially when the consumer is a client of the firm. Proper evaluation of updated information must allow for at least the possibility of human intervention in exception-management mode. It is unlikely that this type of discipline can be applied to high-frequency intra-day changes.
If updates take place on a continuous random basis, there is no “snapshot stability” of information. Unstable data is likely to lead to more questions of how recent or how clean the numbers on the page or screen are.
Two approaches to incorporation of data changes are considered best practices:
Batch each day’s corrections and accounting restatements during the day, and evaluate those using standard data QA procedures. As part of the overnight Mart build, incorporate these changes into selective required rebuilds of the Mart for all past dates affected.
Take the same approach, but do so at one or two regular times during the day as well as at end of day.
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