Oracle Database 12c: Analytic SQL for Data Warehousing Course Overview

To successfully undertake the Oracle Database 12c: Analytic SQL for Data Warehousing course, the following prerequisites are recommended:

• Basic understanding of relational databases and data warehouse concepts, including the roles of tables, rows, and columns.
• Familiarity with the fundamentals of SQL, including how to construct SELECT, INSERT, UPDATE, and DELETE statements.
• Experience with basic SQL functions such as WHERE, JOIN, and GROUP BY clauses.
• Prior exposure to using Oracle's SQL*Plus or SQL Developer tools for executing SQL queries is beneficial.
• An understanding of elementary data warehousing concepts such as ETL (Extract, Transform, Load), star schema, and snowflake schema can be advantageous.
• Enthusiasm to learn about advanced SQL techniques and Oracle-specific SQL extensions for data analysis and reporting.

Please note that these prerequisites are intended to ensure you have a strong foundation to build upon when taking the Oracle Database 12c: Analytic SQL for Data Warehousing course. The course is designed to be accessible to learners who are at an intermediate level of SQL knowledge.

Target Audience for Oracle Database 12c: Analytic SQL for Data Warehousing

1. This Oracle Database 12c course equips professionals with advanced SQL skills for effective data warehousing.

   
   

2. Target Audience and Job Roles:

   
   

• Database Administrators
• Data Warehouse Administrators
• Business Intelligence Professionals
• Data Analysts
• SQL Programmers
• IT Managers overseeing Data Management teams
• Data Scientists requiring SQL knowledge
• Database Developers
• Report Developers
• Technical Consultants
• Professionals working with Oracle BI Cloud Service

Learning Objectives - What you will Learn in this Oracle Database 12c: Analytic SQL for Data Warehousing?

Introduction to Course Learning Outcomes and Concepts:

Gain in-depth knowledge of Oracle Database 12c's analytic features to enhance data warehousing capabilities, including advanced querying, reporting, and data modeling within SQL.

Learning Objectives and Outcomes:

• Understand the use and management of schemas, SQL*Plus, and SQL Developer environments for data analysis.
• Master grouping and aggregation in SQL, using functions such as ROLLUP, CUBE, and GROUPING SETS to generate insightful reports.
• Employ hierarchical queries to retrieve data in natural tree structures, using syntax like CONNECT BY and the WITH clause.
• Utilize regular expressions in SQL for pattern matching, searching, and extracting data, enhancing data processing capabilities.
• Apply analytic functions and understand SQL's role in analysis and reporting to create complex data summaries.
• Perform data transformation using pivoting and unpivoting operations to reshape data sets for better analysis.
• Implement pattern matching with SQL for sophisticated data sequence analysis, utilizing row pattern navigation operations.
• Model data using the SQL MODEL clause, incorporating cell and range references, and managing missing data.
• Gain insights into Oracle Business Intelligence Cloud Service, including its integration, exploratory analysis features, and cloud benefits.
• Ensure readiness to implement Oracle's analytics and reporting functions in real-world scenarios, aligning with enterprise-grade service reliability.