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

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

The Oracle Database 12c: Analytic SQL for Data Warehousing course is tailored to equip learners with the expertise to leverage the advanced analytical features of Oracle Database 12c for data warehousing. It covers a comprehensive suite of SQL features, including grouping and aggregating data, hierarchical queries, regular expressions, and analytical functions like ranking and reporting. The course also introduces advanced techniques such as pivoting operations, pattern matching, and data modeling using SQL.

Participants will learn through practical examples how to create more complex reports and data analysis queries, improving their capability in data manipulation and retrieval. Additionally, an overview of Oracle Business Intelligence Cloud Service highlights how to integrate various data sources and gain insights with the speed and flexibility of the cloud. By mastering these skills, learners will be able to enhance their data warehousing solutions and drive efficient data analysis within their organizations. This training is crucial for database professionals looking to leverage Oracle Database 12c features for data analysis and reporting in a data warehousing environment.

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  • Live Online Training (Duration : 16 Hours)
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  • Live Online Training (Duration : 16 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

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.