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Oracle Database 11g: Data Warehousing & Oracle Warehouse Builder
Duration
5 Days
Course
dbor-935
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Oracle Database 11g: Data Warehousing & Oracle Warehouse Builder course is designed to provide students with an understanding of data warehouse and data mining operations support, along with data warehousing concepts and requirements to configure a data warehouse installation. Students will also demonstrate a knowledge of how the Oracle Warehouse Builder (OWB) product is used to implement and maintain transactional and warehouse databases, and the movement of data between those two different types of installations.Objectives
Upon completion of the Oracle Database 11g: Data Warehousing & Oracle Warehouse Builder course, students will be able to:
- Understand star and snowflake schemas and other data warehouse physical and logical database objects.
- Comprehend and encourage optimization of star queries.
- Create and maintain 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.
- Create and maintain dimensions and hierarchies to enhance ad-hoc query performance and support sophisticated data mining.
- Perform dimensional analysis of data warehouse information and building cubes.
- Demonstrate understand configuration of the Oracle Warehouse Builder (OWB) repository and consideration of OWB capabilities.
- Implement data quality assurance using data rules and the OWB Data Profiler to evaluate data quality within transactional source databases and warehouse target databases.
- Utilize mappings and process flows for data correction and augmentation, as well as building Extraction, Transformation and Transformation (ETT) or Loading (ETL) processes within OWB.
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
- ORACLE DATABASE 10g: IMPLEMENT PARALLEL SQL & PARTITIONING FOR DATA WAREHOUSES
- ORACLE DATABASE 11g R2: NEW & ADVANCED FEATURES FOR DEVELOPERS
- ORACLE DATABASE 11g R1 & R2: NEW FEATURES FOR ADMINISTRATORS
Topics
- DATA warehouse concepts
- ETT / ETL
- DATA warehouse schemas
- EQUITIES data model
- EQUITIES logical data model
- EQUITIES design considerations
- ABOUT materialized views
- CREATE materialized views
- ENABLE query rewrite
- STORAGE & tablespace clauses
- PARALLEL & partition by clauses
- BUILD clause
- NESTED materialized views
- ALTER materialized view
- DROP materialized view
- DATA dictionary storage
- USING EM
- ABOUT materialized view refresh
- REFRESH methods
- CREATE materialized view log
- DROP materialized view log
- REFRESH modes
- ON commit considerations
- PERFORMING refresh operations
- REFRESHING with refresh_all_mviews()
- REFRESING with refresh()
- REFRESHING with refresh_dependent()
- USING explain_mview()
- DATA dictionary refresh metadata
- USING EM
- ENABLING query rewrite
- VIEWING execution plans
- CREATE plan¬_table
- USING autotrace
- USING EM
- CONTROLLING query write
- NOREWRITE
- REWRITE
- UTILIZING constraints with query rewrite
- ENABLE validate constraint option
- ENABLE novalidate constraint option
- DISABLE validiate constraint option
- DISABLE novalidiate constraint option
- RELY constraint option
- ENFORCED level
- TRUSTED level
- STALE_TOLERATED level
- QUERY rewrite influences
- USING EM for “what-if” scenarios?
- WHAT are dimensions?
- CREATING and maintaining dimensions
- ALTER dimensions
- DROP dimensions
- DIMENSION metadata and validation
- 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()
- WHAT is a star query?
- A star transformation scenario
- ENCOURAGING star transformation
- STAR transformation hints
- STAR_transformation hint
- 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
- OWB and the data warehouse
- OWB capabilities
- OWB architecture
- OWB repository
- OMB*plus
- REPOSITORY database configuration
- MANAGE the control center services
- CONFIGURE the repository and workspace
- LAUNCH the design center
- DEFINING the infrastructure
- DEFINING locations
- DEFINING control centers
- DESIGN center preferences
- DEFINE a project container
- DEFINE modules
- IMPORT metadata
- NAVIGATING the data object editor
- WORKING with a detail view
- DEFINING a new object
- DEPLOYING objects to a target database
- ABOUT data analysis principles
- CREATE data profiles
- USE the data profile editor
- CREATING data rules
- APPLYING data rules
- CORRECTION mappings
- DATA auditing monitors
- USING the mapping editor
- ABOUT the operators
- WORKING with staging tables
- USING process flows
Related Courses
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Oracle Database 12c: New Features for Administrators
DBOR-964- Duration: 5 Days
- Delivery Format: Classroom Training, Online Training
- Price: 3,500.00 USD
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- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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