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Oracle Database 11g: Analytic SQL for Data Warehousing |
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| Format: Formation en classe avec formateur |
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In this course students use Analytic SQL to aggregate, analyze and report, and model data. Students learn to interpret the concept of a hierarchical query, create a tree-structured report, format hierarchical data, and exclude branches from the tree structure. Students also learn to use regular expressions and subexpressions to search for, match, and replace strings.
Before attending this course, students should be familiar with relational database concepts, data warehouse theory and implementation, Oracle server concepts including application and server tuning, and the operating system environment on which the Oracle Database Server is running. Students use Oracle SQL Developer to develop these program units. SQL*Plus and JDeveloper are introduced as optional tools.
This course is intended for data warehouse builders and implementers, database administrators, system administrators, and database application developers who design, maintain, and use data warehouses.
Learn to:
- Use Analytic SQL to aggregation, Analyze and Reporting, and Model Data
- Group and aggregate data using the ROLLUP and CUBE operators
- Analyze and report data using Ranking, LAG/LEAD, and FIRST/LAST functions
- Use the MODEL clause to create a multidimensional array from query results
- Interpret the concept of a hierarchical query, create a tree-structured report, format hierarchical data, and exclude branches from the tree structure
- Use regular expressions to search for, match, and replace strings
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Compétences acquises |
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Create a tree-structured report, format hierarchical data, and exclude branches from the tree structureIdentify the benefits of using regular expressionsUse the regular expressions and subexpressions functionsIdentify the benefits of using Analytic SQLReview the available SQL for aggregation operators, SQL for Analysis and Reporting functions, and the SQL for Modeling using the SQL MODEL clause
| | Group and aggregate data using the ROLLUP and CUBE operators, the GROUPING function, Composite Columns, and the Concatenated GroupingsAnalyze and report data using Ranking functions, the LAG/LEAD functions, and the PIVOT and UNPIVOT clausesUse the MODEL clause to create a multidimensional array from query results and then apply formulas to this array to calculate new valuesInterpret the concept of a hierarchical query, create a tree-structured report, format hierarchical data, and exclude branches from the tree structure
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Qui peut en profiter |
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Application DevelopersData Warehouse Administrator
| | Data Warehouse DeveloperSupport Engineer
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| Code: |
11g-ANALYTIC-SQL |
| Format: |
Formation en classe avec formateur |
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| Durée: |
1 |
| Certifié par: |
Oracle |
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| Frais d’inscription (CAD): 825$ |
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 | Ce cours n'est pas prévu à l'horaire pour l'instant. Si vous êtes intéressé à suivre ce cours, utilisez le lien ci-dessous pour demander une date. |
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Oracle Database 11g: Analytic SQL for Data Warehousing Contenu détaillé |
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- Course Objectives
- Course Agenda
- Class Accounts Information
- Appendices Used in this Course
- Sample Schemas Used in this Course
- SQL Environments Available in the Course
- Overview of Oracle SQL Developer
- Oracle 11g SQL and Data Warehousing Documentation and Additional Resources
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| Grouping and Aggregating Data Using SQL
| - What is Analytic SQL?
- Analytic SQL in Data Warehouses Agenda: SQL for Aggregation, SQL for Analysis and Reporting, and SQL for Modeling
- Generating Reports by Grouping Related Data
- Using the GROUP BY Clause With the ROLLUP and CUBE Operators
- Using the ROLLUP and CUBE Operators
- Using the GROUPING Function
- Working With GROUPING SETS
- Working With Composite Columns and Concatenated Groupings
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| Analyzing and Reporting Data Using SQL
| - Overview of SQL for Analysis and Reporting Functions
- Identifying the SQL Ranking Functions
- Controlling the Ranking Order
- Ranking on Multiple Expressions
- Using the RANK, DENSE_RANK, and PERCENT_RANK Functions
- Ranking Per CUBE and ROLLUP
- Using the LAG/LEAD Functions
- Performing Pivoting Operations Using the PIVOT and UNPIVOT Clauses
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- Overview of SQL for Modeling Data
- Integrating Inter-row Calculations in SQL
- Working With the SQL MODEL Clause
- Cell and Range References
- Using the CV()Function
- Using the FOR Construct with IN List Operator, Incremental Values, and a Subquery
- Using Reference Models
- Cyclic Rules in Models
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- Hierarchical Retrieval: Overview
- Natural Tree Structure
- Hierarchical Queries
- Walking the Tree
- Walking the Tree: From the Bottom Up and From the Top Down
- Ranking Rows with the LEVEL Pseudocolumn
- Formatting Hierarchical Reports Using LEVEL and LPAD
- Pruning Branches and Nodes
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| Analyzing Data Using Regular Expressions
| - The Benefits of Using Regular Expressions
- Using the Regular Expressions Functions and Conditions in SQL
- Using Metacharacters with Regular Expressions
- Performing a Basic Search Using the REGEXP_LIKE Condition
- Finding Patterns Using the REGEXP_INSTR Function
- Extracting Substrings Using the REGEXP_SUBSTR Function
- Replacing Patterns Using the REGEXP_REPLACE Function
- Using Subexpressions with Regular Expression Support
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