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ora11g205-ver1
Oracle Database 11g: Data Warehousing & Oracle Warehouse Builder (5 day)
Description
This Oracle 11g courseware training guide book will highlight the features within the Oracle database specifically intended to support data warehouses and data mining operations. It is presented as a two-volume set. The first volume considers data warehousing concepts and the requirements to initially configure a data warehouse installation. The second volume discusses how the Oracle Warehouse Builder (OWB) product may be used to implement and maintain both transactional and warehouse databases, and the movement of data between those two different types of installations.
Audience
Target audience for this course are database administrators, data warehouse administrators and application developers who will be responsible for implementing applications using data warehouse technology.
Prerequisites
A mandatory prerequisite to this course is the Sideris course ORACLE DATABASE 11g: IMPLEMENT PARALLEL SQL & PARTITIONING FOR DATA WAREHOUSES.
Additionally, it is recommended that one have attended one of the following advanced courses provided for either database developers or database administrators:
• ORACLE DATABASE 11g: NEW & ADVANCED FEATURES FOR DEVELOPERS
• ORACLE DATABASE 11g: NEW FEATURES FOR ADMINISTRATORS
Objectives
Among the specific topics considered within this course are:
• Understanding star and snowflake schemas and other data warehouse physical and logical database objects.
• Understanding and encouraging optimization of star queries.
• Creating and maintaining materialized views to enhance ad-hoc query performance against enormous volumes of transactional data.
• Manage materialized views to effectively and efficiently maintain their structure over the course of time.
• Creating and maintaining dimensions and hierarchies to enhance ad-hoc query performance and support sophisticated data mining.
• Performing dimensional analysis of data warehouse information and building cubes.
• Configuration of the Oracle Warehouse Builder (OWB) repository and consideration of OWB capabilities.
• Implementing data quality assurance using data rules and the OWB Data Profiler to evaluate data quality within transactional source databases and warehouse target databases.
• Using mappings and process flows for data correction and augmentation, as well as building Extraction, Transformation and Transformation (ETT) or Loading (ETL) processes within OWB.
Course Outline
DATA WAREHOUSE DESIGN & SCHEMAS • DATA WAREHOUSE CONCEPTS • ETT / ETL • DATA WAREHOUSE SCHEMAS • The EQUITIES Data Model • EQUITIES Logical Data Model • EQUITIES Physical Model • PHYSICAL DESIGN CONSIDERATIONS
CREATING MATERIALIZED VIEWS • ABOUT MATERIALIZED VIEWS • CREATE MATERIALIZED VIEWS • ENABLE QUERY REWRITE • STORAGE & TABLESPACE Clauses • PARALLEL & PARTITION BY Clauses • BUILD Clause • NESTED MATERIALIZED VIEWS
MAINTAINING MATERIALIZED VIEWS • ALTER MATERIALIZED VIEW • DROP MATERIALIZED VIEW • DATA DICTIONARY STORAGE • USING EM
MATERIALIZED VIEW REFRESH • ABOUT MATERIALIZED VIEW REFRESH • REFRESH METHODS • CREATE MATERIALIZED VIEW LOG • ALTER MATERIALIZED VIEW LOG • DROP MATERIALIZED VIEW LOG • REFRESH MODES • ON COMMIT Considerations • PERFORMING REFRESH OPERATIONS • Refreshing With REFRESH_ALL_MVIEWS() • Refreshing With REFRESH() • Refreshing With REFRESH_DEPENDENT() • Using EXPLAIN_MVIEW() • DATA DICTIONARY REFRESH METADATA • USING EM
CONTROLLING THE QUERY REWRITE FACILITY • ENABLING QUERY REWRITE • VIEWING EXECUTION PLANS • Create PLAN_TABLE • Using AUTOTRACE • Using EM • CONTROLLING QUERY REWRITE • NOREWRITE • REWRITE • UTILIZING CONSTRAINTS WITH QUERY REWRITE • ENABLE VALIDATE Constraint Option • ENABLE NOVALIDATE Constraint Option • DISABLE NOVALIDATE Constraint Option • DISABLE VALIDATE Constraint Option • RELY Constraint Option • ENFORCED Level • TRUSTED Level • STALE_TOLERATED Level • QUERY REWRITE INFLUENCES • USING EM FOR "WHAT-IF?" SCENARIOS
DIMENSIONS • WHAT ARE DIMENSIONS? • CREATING & MAINTAINING DIMENSIONS • ALTER DIMENSION • DROP DIMENSION • DIMENSION METADATA & VALIDATION
DIMENSIONAL ANALYSIS OF DATA • DATA SAMPLING • DIMENSION AGGREGATION TECHNIQUES • The GROUPING() Function • Using CUBE() • BUILDING THE DATA WAREHOUSE CUBE • The EQUITIES Cube • GROUPING_ID() Function • CUBE() Vs. GROUPING SETS()
STAR QUERIES & THE OPTIMIZER • WHAT IS A STAR QUERY? • A STAR TRANSFORMATION SCENARIO • ENCOURAGING STAR TRANSFORMATION • STAR TRANSFORMATION HINTS • STAR_TRANSFORMATION Hint
ETL: LOADING FROM EXTERNAL TABLES • ABOUT THE EXTRACTION OPTIONS • USING EXTERNAL TABLES • ORACLE_LOADER ACCESS PARAMETERS • RECORDS Parameter • BADFILE Parameter • LOGFILE Parameter • DISCARDFILE Parameter • LOAD WHEN Parameter • SKIP Parameter • The LOCATION Clause • REJECT LIMIT Clause • FIELDS TERMINATED BY Parameter • MISSING FIELD VALUES Parameter • ORACLE_DATAPUMP ACCESS DRIVER • MAINTAINING EXTERNAL TABLES • USER_EXTERNAL_TABLES • USER_EXTERNAL_LOCATIONS • Using ALTER TABLE
ETL: TRANSFORMATION WITH TABLE FUNCTIONS
ABOUT ORACLE WAREHOUSE BUILDER • OWB & THE DATA WAREHOUSE • OWB CAPABILITIES • OWB ARCHITECTURE • OWB Repository • OMB*Plus
CONFIGURE ORACLE WAREHOUSE BUILDER • REPOSITORY DATABASE CONFIGURATION • MANAGE THE CONTROL CENTER SERVICES • CONFIGURE THE REPOSITORY & WORKSPACE
USING THE DESIGN CENTER & BUILDING THE INFRASTRUCTURE • LAUNCH THE DESIGN CENTER • DEFINING THE INFRASTRUCTURE • DEFINING LOCATIONS • DEFINING CONTROL CENTERS • DESIGN CENTER PREFERENCES
DEFINE MODULES & IMPORT METADATA • DEFINE A PROJECT CONTAINER • DEFINE MODULES • IMPORT METADATA
MAINTAINING THE RELATIONAL MODEL • NAVIGATING THE DATA OBJECT EDITOR • WORKING WITH A DETAIL VIEW • DEFINING A NEW OBJECT • DEPLOYING OBJECTS TO A TARGET DATABASE
DATA QUALITY ASSURANCE & MANAGEMENT • ABOUT DATA ANALYSIS PRINCIPLES • CREATE DATA PROFILES • USE THE DATA PROFILE EDITOR
DATA RULES & CORRECTION MAPPINGS • CREATING DATA RULES • APPLYING DATA RULES • CORRECTION MAPPINGS • DATA AUDITING MONITORS
ETL MAPPINGS • USING THE MAPPING EDITOR • ABOUT THE OPERATORS • WORKING WITH STAGING TABLES
PROCESS FLOWS & SCHEDULES • USING PROCESS FLOWS • USING SCHEDULES
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