Convert Active Reports to Data Mart
You may have built your presentation-quality reports using PACE Active reports. Now that Data Mart is available as an information delivery tool, should you consider converting existing reports to source data against the Mart? This is a complex question, and involves several considerations discussed in the following sections.
Field Standardization
Each Advanced report built with underlying OLAP reports has a list of field attributes associated with it. Advanced reports often involve one or more individual field rules for each underlying OLAP report. Standardization and re-use of field attributes and field rules is possible, but many organizations find that it is all too easy to duplicate fields. Data Mart, by contrast, encourages business definition standardization and sharing of field attributes since duplication of data fields is much more easily recognizable in the Mart and thus avoidable.
Preserve Advanced Report Functionality
You will not lose the benefits of using Advanced reports under a conversion to Data Mart. You can still schedule Active reports built against the Mart to send to Portal, and still develop them as a Client reporting batch. Report ordering functionality and passing of parameters is the same as when actual OLAP reports underly the Advanced report.
If you implement Data Mart to adopt a reporting tool not supported by Advanced reports, you forego the benefits of Advanced reports related to Portal and Client Reporting.
Data Retrieval Staging versus Data Processing
When you run an Advanced report with underlying OLAPs, all of the underlying processing is done on the fly. Some calculations, especially performance calculations, can be time consuming and lead to long rendering times for reports. With Data Mart as the data source, all computations are completed before reports are run, so that reports simply retrieve field values from one or more tables.
However, if reporting in the organization is a matter of running reports in the overnight cycle and not during normal business hours rather than running reports during the day, Data Mart does not offer as much of a total production time savings.
You can create multiple snapshots allowing you to build and save your data more than once per day and use more than one source rule in the build process. Creating multiple snapshots means an organization could maintain a custodian source and a manager source for the same accounting data. By saving multiple snapshots, you could report on intra-day comparisons of data values.
Potential for Sharing Fields
Your reports share many common fields. Data Mart provides the efficiency of computing each one of them just once rather than once per report. Mart data is meant to be shared among reports. For this reason it is critical to make a careful plan of the data fields in the mart to assure that all reporting needs are covered by a minimum of fields.
Report Conversion
There is no utility that automates report conversion. It is difficult to design such a capability that would be useful in a large number of cases.
An Active reports report sources data from PACE field attributes. Data Mart can store data for the same field attributes with the exception of a short list of field types that Data Mart does not support. Refer to the Data Mart User Guide for additional information. The SQL code used by an Advanced report must be reworked in terms of tables accessed and joins used which changes in a Mart conversion.
However, Eagle Mart, which sources from Data Mart, comes with a set of standard reports including report source code for the non-performance set. These reports provide examples of building Advanced reports against the Mart that may be useful to you during report conversion.
Report Development
The Mart offers efficiencies in report development:
Data Mart simplifies the process of building SQL code for bringing your data together in a report. Data Mart places data fields of multiple types, such as position, performance, and transaction on the same line of a data source table at the group and fund levels of aggregation. This saves you the effort of creating multiple OLAP report rules and profiles and then joining their results in SQL that you must develop.
If you report data using time series, you can do so for some performance fields using the Performance Query Tool. For other types of data, OLAP processes are limiting. Through regular daily or monthly builds, Data Mart establishes a history of all data, making time series reporting easy.
Data Mart encourages standardization of field definitions and helps reduce unintended duplication of field attributes that sometimes accompanies OLAP report development. See “Field Standardization” for additional information.
Support Non-OLAP Data in the Mart
All data built by PACE in Data Mart tables comes from the action of an OLAP process. There are strong arguments for maximizing the potential of the OLAPs to populate as much required reportable data as possible, given the powerful and flexible tools available in the Data Mart for data management of the Mart. However, it is sometimes necessary to support data in the Mart not placed there by the OLAPs.
When to Move Non-OLAP Data to the Mart
Some types of data either should or must bypass the OLAP processes that build data into mart tables:
Data in structures not supported by OLAPs. The Eagle data model is very flexible and supports a wide range of data structures. You can build custom tables and join them to core tables to permit access by the OLAPs. You can also create database views and build field attributes to report their contents. However, there may be instances where data is loaded to the Eagle warehouse for which OLAP access is not readily available and cannot easily be provided.
Report-ready, single-use data loaded in high volume. Even in the case of single use data, Eagle recommends as a best practice that all data is stored in the warehouse followed by Data Mart running the OLAP processes to move a set of values from one warehouse schema to the Data Mart schema. This is the best approach if you want to load data from an external source such as report-ready performance data.
Data Moved in Anticipation of a Future Release Enhancement. You may need to deliver a type of information that is supported in Data Mart only in a future release due to a product enhancement. Release upgrade may not be practical before the information is required. If the nature of the enhancement is to enable a new type of field to be built into existing Mart tables, a temporary workaround strategy may be available. Refer to “Direct Loads to Future Table Extensions” for additional information.
How to Move Non-OLAP Data to the Mart
The following sections describe how to deploy non-OLAP data to the Data Mart schema.
Non-Materialized Views
A non-materialized view is simply a SQL query against other database tables that is exposed to reports and applications as if it were a physical table. This simplifies access since joins between tables and views are supported. The main drawback of such a view is that its use involves the latency of execution of a database query. Reserve this type of view for the simplest views in use.
Materialized Views
Materialized views are physically built from data returned by underlying SQL. They are a sort of database copy. Queries against them perform much better than those against non-materialized views of the same datasets, since data is physically present and does not have to be assembled on the fly. They are best suited to views of larger numbers of fields. A drawback of materialized views is that they must be updated and maintained. Oracle offers a powerful toolset, Oracle Materialized Views, for deploying materialized views.
Direct Loads to Reserved Columns of Mart Tables
The Selective Fields enhancement in V9.0 Data Mart allows you to directly load fields to Data Mart tables as long as you can populate all rows of those tables by a regular Data Mart Submit. You could reserve some fields in the tables that need supplemental data from direct loads. To do this, create and select a set of dummy field attributes for the model to create columns in the table to receive the external load. Selective fields are then used to avoid populating those fields in the regular build, reserving them for the external load. Eagle recommends you create and populate an extension since the Mart does not delete data, but simply updates it.
This practice introduces complexities, and you should attempt it only in consultation with our Professional Services Consulting Group. It may be simpler just to add a custom table to the Data Mart schema and join to appropriate tables in reporting.
Direct Loads to Future Table Extensions
If you want to use a type of Mart data fields that are only supported in a release after yours, you may be able to load those fields to a table having the same key structure as a Data Mart table extension. You can give the table the same name as the extension you would create for the fields in a higher release, and report against the table as if it were a regular Mart table extension. Then, when you upgrade, create the table extension in the Mart and give it the name of the table you are using for the new fields. You add to that extension the Mart fields necessary to create your table fields, now supported in the Mart. This is a simple process with the benefit that reporting data access logic need not change at all.
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