Eagle Data Mart is a data repository within Eagle's data warehouse or other database where you can organize information for a specific business purpose and distribute it to support business needs. With the Multiple Data Marts feature, you can build as many Data Mart schemas as you need in these databases.

Eagle's data warehouse stores and supplies a full range of information to support the needs of a corporate enterprise. By contrast, Data Mart services one or more specific business needs, such as performance data for reporting and analysis. Data Mart delivers reportable data to an open platform for use by third party data presentation tools, such as Crystal Reports, Actuate, and Microsoft Reporting Services.

One of the benefits of Data Mart is that it leverages the field attributes, source rules, date rules, concentration engines, code values, sources, and performance calculations in Eagle's data warehouse. Another benefit is that it is much easier to access the data. Data Mart stores data in flat, transparent database tables, reducing the number and complexity of SQL select statements needed to access the data. 

Data Mart stores data in various tables in a Data Mart schema according to the aggregation level of the data. All data at the fully aggregated or fund level resides in the Fund Summary table. Data relating to nodes of a grouping of a portfolio, such as group subtotals or group returns, resides in group level tables. Disaggregated data relating to individual trades, positions, or security level returns resides in a series of detail level tables based on the type of data.

Analyze Your Reporting Requirements

A well-built Data Mart starts with an analysis of your reporting requirements. This means taking a complete inventory of the data you want in your Data Mart at the group, fund, and detail portfolio levels.

Create Models

Group, Fund Summary, and Detail models define how to populate the group, fund, and detail level tables in Data Mart for reporting purposes. The following figure illustrates how Data Mart displays data stored at the group, fund, and detail portfolio levels.

Figure 1: Portfolio Valuation Report

Group Models

Group models define group level data, such as the Technology and Energy sectors and the partially aggregated fund totals for each sector as shown in the previous figure.
Group models are user defined according to your unique reporting requirements. You can create one or more Group models.
Data Mart stores group level data in the group tables in the Data Mart schema. Table names are user assigned.

Fund Summary Models

The Fund Summary model defines fund level (entity) data, such as the fund name, manager name, and fully aggregated fund totals as shown in previous figure.
The Fund Summary model is pre-defined in terms of its basic structure. However, it requires configuration according to your unique reporting requirements.
Data Mart stores fund level data in the Fund Summary table in a mart schema.

Detail Models

Detail models define detail level data, such as the name of each security, book value, and market value shown in the previous figure. Data Mart provides the following Detail models:

• Position Details
• Position Look through Details
• Lot Level Position Details
• Transaction Details
• Cash Flow Details
• Ledger Activity Details
• Security Details
• Issuer Details
• Performance Details

Detail models are pre-defined in terms of their basic structure. However, they require configuration according to your unique reporting requirements.
Data Mart stores detail level data in the Position Details, Lot Level Position Details, Trade Details, Cash Flow Details, Performance Details, Ledger Activity Details, Security Details, and Issuer Details tables in a Mart schema.
Data Mart has the flexibility to differentiate reporting at the group, fund, and detail levels. For example, you can report on market values at the fund, group, and detail levels. Additionally, if you forget to add a field during the initial set up of your Data Mart, you can add it later.
A Data Mart schema also contains the Fund Master table, which defines the Entity and Effective Date of each table row. The system identifies the unique combination of Entity ID and Effective Date as the Data Mart Fund ID.

Submit Models

When you submit a model, the Data Mart engines launch one or more OLAP (online analytical processing) processes based on the type of fields in the model. For example, if you submit a model that contains performance fields, the Data Mart engines would generate a performance analysis OLAP process that provided a number of field values, such as the following:

• Field List

The list of performance database columns to return.

• Entity List

The list of entities for which performance data must be provided.

• Effective Date

The end date of the performance records that the report must return. This date is combined with the time span of the longest linked return of a model or extension.
After selecting data from the database based on the types of fields in the model, additional processing may be done, such as return linking. The Data Mart engines would then save the results of the performance analysis report in the specified tables of a Data Mart schema for reporting purposes.
Since OLAP reports are specialized by field type, such as position, performance, or transaction, it may take four or more OLAP reports to provide the necessary fields for a fund level or group level table. You have the option of defining table extensions for the Fund Summary and Detail models. A table extension stores a subset of the model's fields in a separate physical table that has a key structure identical to the main table, but is populated by its own OLAP reports.