1 Introduction to Oracle Airlines Data Model Customization

Components of the Oracle Airlines Data Model

Oracle Airlines Data Model includes the following components:

• Logical model which is a third normal form (3NF) entity-object model. The logical model follows aviation industry standards and is described in Oracle Airlines Data Model Reference.

• Physical model defined as an Oracle Database schema.

• Intra-ETL database packages and SQL scripts to extract, transform, and load (ETL) data from the Oracle Airlines Data Model 3NF physical tables to the derived and aggregate tables in Oracle Airlines Data Model.

• Sample reports and dashboards developed using Oracle Business Intelligence Suite Enterprise Edition.

• DDL and installation scripts

Oracle Products That Make Up Oracle Airlines Data Model

Several Oracle technologies are involved in building the infrastructure for Oracle Airlines Data Model:

• Oracle Database with OLAP, Data Mining and Partitioning Option

• Oracle Development Tools

• Oracle Business Intelligence Suite Enterprise Edition Presentation Tools

Oracle Database with OLAP, Data Mining and Partitioning Option

Oracle Airlines Data Model uses a complete Oracle technical stack. It leverages the following data warehousing features of the Oracle Database: SQL model, compression, partitioning, materialized views, data mining, and online analytical processing (OLAP).

Oracle Development Tools

You can use the following Oracle tools to customize the predefined physical models provided with Oracle Airlines Data Model, or to populate the target relational tables and materialized cube views.

Oracle Business Intelligence Suite Enterprise Edition Presentation Tools

Oracle Business Intelligence Suite Enterprise Edition is a comprehensive suite of enterprise BI products that delivers a full range of analysis and reporting capabilities. You can use Oracle Business Intelligence Suite Enterprise Edition Answers and Dashboard presentation tools to customize the predefined sample dashboard reports that are provided with Oracle Airlines Data Model.

Prerequisite Knowledge for Implementors

As outlined in "Oracle Products That Make Up Oracle Airlines Data Model", the Oracle Airlines Data Model uses much of the Oracle stack. Consequently, to successfully implement the Oracle Airlines Data Model, the implementation team needs:

• Experience performing information and data analysis and data modeling. (Experience using Oracle SQL Data Modeler, is a plus.)

• An understanding of the Oracle technology stack, especially data warehouse (Database, Data Warehouse, OLAP, Data Mining, Oracle Business Intelligence Suite Enterprise Edition)

• Hands-on experience using:

  • Oracle Database

  • PL/SQL

  • SQL DDL and DML syntax

  • Analytic Workspace Manager

  • Oracle SQL Developer

  • Oracle Business Intelligence Suite Enterprise Edition Administrator, Answers, and Dashboards

Responsibilities of a Data Warehouse Governance Committee

Governance is of concern to any enterprise, executive team or individual with an interest in the processes, standards, and compliance. It is even more important to organizations that have invested in data warehousing.

Data warehouse governance occurs within the context of overall IT governance. It provides the necessary policies, process and procedures, which must be clearly communicated to the entire corporation, from the IT employees to the front-end operational personnel.

Before you customize Oracle Airlines Data Model, setup a data warehouse governance steering committee if one does not exist. The role of this steering committed is to oversee the data warehouse to provide an environment that reaches across the enterprise and drives the best business value.

Data Warehouse Governance Committee: Overall Responsibilities

The data warehouse governance steering committee sets direction and response for the governance framework and covers the follow areas:

• The entire data warehouse life cycle.

• Agree on the data to process and make available to end-users.

• Determine what is the minimum quality criteria for the data that is available to end users and determine how to measure and analyze these criteria against the quality of the data that is the source data for the data warehouse.

• The business goals of the organization to apply core information from data warehouse.

• The policies, procedures and standards for data resource and data access.

• The life cycle of data warehouse component management.

Data Warehouse Governance Committee: Data Governance Responsibilities

The more detailed focus in data warehouse governance is data governance. Data governance tasks include:

• Approving the data modeling standards, metadata standards and other related standards. This includes determining a metadata strategy as discussed in "Managing the Metadata for Oracle Airlines Data Model"' and identifying the data modeling tools to use that support these standards.

• Determining the data retention policy.

• Designing a data access policy based on legal restrictions and data security rules.

• Designing a data backup strategy that aligns with the impact analysis to the business unit.

• Monitoring and reporting on data usage, activity, and alerts.

Metadata Categories and Standards

Metadata is organized into three major categories:

• Business metadata describes the meaning of data in a business sense. The business interpretation of data elements in the data warehouse is based on the actual table and column names in the database. Gather this mapping information and business definition and rules information into business metadata.

• Technical metadata represents the technical aspects of data, including attributes such as data types, lengths, lineage, results from data profiling, and so on

• Process execution metadata presents statistics on the results of running the ETL process itself, including measures such as rows loaded successfully, rows rejected, amount of time to load, and so on

Since metadata is so important in information management, many organizations attempt to standardize metadata at various levels, such as:

• Metadata Encoding and Transmission Standard (METS). A standard for encoding descriptive, administrative, and structural metadata regarding objects within a digital library.

• American National Standards Institute (ANSI). The organization that coordinates the U.S. voluntary standardization and conformity-assessment systems.

• International Organization for Standardization (ISO). The body that establishes, develops, and promotes standards for international exchange.

• Common Warehouse Metamodel (CWM). A specification, released and owned by the Object Management Group, for modeling metadata for relational, non-relational, multi-dimensional, and most other objects found in a data warehousing environment.

When you implement your metadata management solution, reference your data warehouse infrastructure environment and make the decision which standard to follow.

Working with a Metadata Repository

You manage metadata using a Metadata Repository. At the highest level, a Metadata Repository includes three layers of information. The layers are defined in the following order:

1. A Physical layer. This metadata layer identifies the source data.

2. A Business Model and Mapping layer. This metadata layer organizes the physical layer into logical categories and records the appropriate metadata for access to the source data.

3. The Presentation layer. This metadata layer exposes the business model entities for end-user access.

The first step in creating a Metadata Repository is to scope your metadata management needs by:

• Identifying the metadata consumers. Typically, there are business consumers and technical consumers.

• Determine the business and technical metadata requirements.

• Aligning metadata requirements to specific data elements and logical data flows.

Then:

• Decide how important each part is.

• Assign responsibility to someone for each piece.

• Decide what constitutes a consistent and working set of metadata

• Where to store, backup, and recover the metadata.

• Ensure that each piece of metadata is available only to those people who need it.

• Quality-assure the metadata and ensure that it is complete and up to date.

• Identify the Metadata Repository to use and how to control that repository from one place

After creating the metadata definitions, review your data architecture to ensure you can acquire, integrate, and maintain the metadata.

As the data keeps on changing in your data warehouse day by day, update the Metadata Repository. When you want to change business rules, definitions, formulas or process (especially when customizing the Oracle Airlines Data Model), your first step is to survey the metadata and do an impact analysis to list all of the attributes in the data warehouse environment that would be affected by a proposed change.

Browsing the Metadata Repository Supplied With Oracle Airlines Data Model

To customize the Oracle Airlines Data Model model, you must understand the dependencies among Oracle Airlines Data Model components -- especially how the report KPIs are mapped to the physical tables and columns.

Oracle Airlines Data Model provides a tool called the "OADM Metadata" browser that helps you discover these dependencies. When you install Oracle Airlines Data Model with its sample reports, the metadata browser is delivered as a sample Dashboard in the webcat.

To browse the metadata repository:

1. In the browser, open the login page at http://servername:9704/analytics where servername is the server on which the webcat is installed.

2. Login with username of oadm, and provide the password.

3. Select the Metadata Browser dashboard.

4. Use the tabs in the Metadata browser to explore the metadata:

   • Measure-Entity tab

     On the Measure-Entity tab you can see the business areas (relational, OLAP, mining), the measures description, corresponding formula, responsible entities, and attributes for the measure.

     To browse the data, select the business area and measure description that you are interested in.

   • Entity-Measure tab

     Using the Entity-Measure tab, you can discover the mappings between entities, attributes, supported measures, and calculations of the measures. You can discover information about particular entities and attributes.

     For example, you take the following steps to learn more about an entity:

     1. Select the entity.

     2. Click GO.

   • Program-Table tab

     Using the Program-Table tab you can browse for information on the intra-ETL mappings and report information. Take the following steps:

     1. Select the program type (that is, intra-ETL or report) and program name.

     2. Select GO.

   • Table-Program tab

     By default when you go to the Table-Program tab you see all of the tables used for all the reports.

     To discover what reports use a particular table, you must move a particular table from the right pane to the left (Selected) pane.

     For example, to see the reports that use a particular table, take the following steps:

     1. In the right pane of the Table-Program tab, select the table.

     2. Move the table to the Selected list on the left by clicking on < (left arrow).

     3. Click OK.

     4. Select GO.

     The reports for the selected table are displayed.