Metadata Analysis & eprentise Technology

eprentise® is a knowledge-based system that incorporates hundreds of thousands of rules about relational databases. eprentise gathers these rules through a process called Metadata Analysis. During Metadata Analysis, eprentise software uses a proprietary technique to “mine” information about your database installation by examining the data dictionaries, applying patterns and algorithms of relational databases, and comparing your actual instance(s) against the standard “Gold” versions of E-Business Suite it already knows.

eprentise Metadata Analysis mines these database rules from the application, and stores the valid rules in an active knowledge base. Metadata Analysis discovers all database objects (e.g., tables and columns, primary and unique keys, rows and objects, foreign keys, other constraints, triggers). When it finds information about your environment, it confirms the information by checking every row of data to see if the information is consistent within the database, and then validates the information against the eprentise Knowledge Repository. After all the rules about the metadata are confirmed and validated, Metadata Analysis populates the eprentise Knowledge Repository with information specifically about your database, your schemas, all the constraints, and other database objects.

Along with user-created rules, the knowledge from Metadata Analysis allows eprentise to perform the functions of copy, merge, filter, and change to any data or data object in the database. The rules serve as selection criteria to allow eprentise to manipulate the data and maintain the relational integrity of the database. The sequence of rules and the objects that the rules act upon can be re-used or modified to repeat the process with different nuances and twists until the data is changed to meet a customer’s business requirements. Once rules are created, eprentise uses what it has learned from Metadata Analysis to generate code to transform the data everywhere in the E-Business Suite.

Data Levels

In addition to the understanding the database objects, eprentise Metadata Analysis operates at four levels of data in a typical database environment, each representing a different origin and purpose:

Seed Data – Data that comes with the application when it is installed such as standard currencies. The currency is installed (based on the user selection) at the time of install. As is the case with currency, some seed data may vary by localization or version of the application that is installed, among other factors. Seed data is embedded in the application and generally can’t be changed.

Configuration Data – Parameters for the application that are set up by the user. Configuration data may include a chart of accounts, a supplier’s payment terms, or a list of diagnostic codes. For example, the user may configure the units of measure or quantity to display as “doz” while another instance may have this same property defined as “dz”. Configuration data is used everywhere in the system. Transaction data relies on configuration and master data.

Master Data – Generally speaking, this constitutes customers, suppliers, employees and products – the building blocks of a company’s information system that is specific to the business of that company.

Transaction Data – Records of the operation of the business processes. Examples of transactions include orders, invoices, or payment records, payroll, expense reports, or sales, etc.

While eprentise software works at each of these data levels, Metadata Analysis is primarily concerned with the relationships between these levels. By learning about the relationships and rules that have been built into the instance, the software can make sure that the results of copying, filtering, merging, and changing data start at the seed data level then move “up” to the transaction level. By the time changes are made to the transaction data, all of the related data that affects each transaction has been changed to provide it with consistent support. The resulting target is complete, consistent, correct, and aligned with the user-defined business rules. No changes are made to the data during Metadata Analysis; this is simply a fact-finding mission to determine the structure, composition, and relationships found in the database.

Configuration Analysis, an optional part of eprentise Metadata Analysis, is used to compare configuration or set-up data when executing an eprentise merge solution. Configuration Analysis determines the implementation of the base parameters and flexfields in the Oracle E-Business Suite and compares the set-up across different database instances or even across candidate duplicates. For example, Configuration Analysis will determine if you have the same calendar periods in different sets of books, or whether your approval hierarchies are consistent across operating units.

Metadata Analysis can also be used to compare your test instance(s) against the production instances of Oracle E-Business Suite. With eprentise, the user can revise the rules as many times as needed, until the user achieves the desired results. Since the software can be re-used, it offers the possibility of replicating results in other contexts or business units of an enterprise at minimum cost and in minimal time. For example, data quality standards selected and applied to Customers can be applied as well to Suppliers without additional preparation. Changes to an accounting structure made in one set of books can be replicated in another set of books with only a few keystrokes. Work, once done, is captured in eprentise software and need not be redone.