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You should protect the field attributes you use to build your Data Mart fields against unintended changes by PACE users unaware of their use in your Mart models. Any change could produce invalid data in your reports, and some changes, especially changes of field type, could cause a model to fail. It is difficult to detect a field attribute change except by checking the update of each field used in a model.

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Support Portfolio Look-through

Look-through reporting at the detail level is supported in a Position Details look-through model and table. The granularity of a row in this table is the look-though position piece. The piece is the position in the portfolio or in any child find at whatever level of nesting. This is the same granularity as in a position OLAP report having look-through fields. The data is returned flattened for look-through in Data Mart.

Look-through in Data Mart Group Level Models

Group level models support look-through by enabling look-through processing. By default, the Enable Look thru Processing checkbox on the Model dialog box is blank. When you select it, it conditions the model to support only look-through processing.

Support Long-Term Summaries of Trade Activity

You may need to report summaries of trade or cash activity over long periods of time, such as the sum of buys year-to-date. Any generic trade field attribute can build this type of data. While it is possible to rebuild these field attributes over a long time period every day in the mart, this is an inefficient practice. A more efficient strategy is to build that summary field on a month-to-date basis daily, then sum over a set of monthly fields at the report level, perhaps with the use of a general-purpose stored procedure.

Support General Ledger Data

Data Mart supports General Ledger data. Although Eagle Accounting was enhanced to facilitate building ledger data in Data Mart, other accounting systems may send ledger data to Data Mart if they load the gl_detail_posting table of the ledger database in the same way as Eagle Accounting does.

Eagle Accounting sends ledger data under different sources for different accounting bases and for daily versus monthly balances. If you want to support more than one basis or periodicity in your reporting, it is best practice to use a separate snapshot for each.

Support NAV Data

Data Mart does not directly support fields from the Net Asset Value (NAV) table. However, it does support Dynamic Mutual Fund field attributes. A series of field categories and about 20 different effects were added to the Dynamic Mutual Fund field attribute type to allow a wide range of NAV fields to be supported in Data Mart.

Limitations of Selective Fields

The Build Selective Fields option has a number of significant benefits, such as selective back-filling. For example, when you add one or more new fields to a model that you have been populating for a while you can use this option to populate values for the new fields only. Otherwise, you have to submit the model to populate every field of each row. When you re-populate fields that already have data values, the values are not deleted, but re-generated. This can lead to an unintended restatement of reported data values.

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