Kurz je určený pre tých, ktorí sa chcú naučiť písať analytické SQL dotazy pre prácu s dátovými skladmi. Preberané sú agregačné, analytické, reportovacie a skupinové funkcie, ROLLUP a CUBE operátory, práca s regulárnymi výrazmi, kontingenčnými [...]
  • ORSQLWH
  • Dĺžka 2 dni
  • 30 ITK bodov
  • 6 termínov
  • Bratislava (1 620 €)

    Brno (40 900 Kč)

    Praha (40 900 Kč)

Kurz je určený pre tých, ktorí sa chcú naučiť písať analytické SQL dotazy pre prácu s dátovými skladmi. Preberané sú agregačné, analytické, reportovacie a skupinové funkcie, ROLLUP a CUBE operátory, práca s regulárnymi výrazmi, kontingenčnými tabuľkami a ďalšie.

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  • Use SQL with aggregation operators, SQL for Analysis and Reporting functions.
  • Group and aggregate data using the ROLLUP and CUBE operators, the GROUPING function, Composite Columns and the concatenated Groupings.
  • Analyze and report data using Ranking functions, the LAG/LEAD Functions and the PIVOT and UNPIVOT clauses.
  • Perform advanced pattern matching.
  • Use regular expressions to search for, match and replace strings.

Potrebné vstupné požiadavky:

  • Familiarity with SQL
  • Data Warehouse design, implementation, and maintenance experience
  • Good working knowledge of the SQL language
  • Familiarity with Oracle SQL Developer and SQL*Plus
  • Oracle Database 11g: Data Warehousing Fundamentals
  • Oracle Database: Introduction to SQL NEW

Odporúčané vstupné požiadavky:

  • Conceptual experience designing data warehouses
  • Practical experience implementing data warehouses
  • Good understanding of relational technology

Introduction

  • Course Objectives, Course Agenda and Class Account Information
  • Describe the Schemas and Appendices used in the Lesson
  • Overview of SQL*Plus Environment
  • Overview of SQL Developer
  • Overview of Analytic SQL
  • Oracle Database SQL and Data Warehousing Documentation

Grouping and Aggregating Data Using SQL

  • Generating Reports by Grouping Related Data
  • Review of Group Functions
  • Reviewing GROUP BY and HAVING Clause
  • Using the ROLLUP and CUBE Operators
  • Using the GROUPING Function
  • Working with GROUPING SET Operators and Composite Columns
  • Using Concatenated Groupings with Example

Hierarchical Retrieval

  • Using Hierarchical Queries
  • Sample Data from the EMPLOYEES Table
  • Natural Tree Structure
  • Hierarchical Queries: Syntax
  • Walking the Tree: Specifying the Starting Point
  • Walking the Tree: Specifying the Direction of the Query
  • Using the WITH Clause
  • Hierarchical Query Example: Using the CONNECT BY Clause

Working with Regular Expressions

  • Introducing Regular Expressions
  • Using the Regular Expressions Functions and Conditions in SQL and PL/SQL
  • Introducing Metacharacters
  • Using Metacharacters with Regular Expressions
  • Regular Expressions Functions and Conditions: Syntax
  • Performing a Basic Search Using the REGEXP_LIKE Condition
  • Finding Patterns Using the REGEXP_INSTR Function
  • Extracting Substrings Using the REGEXP_SUBSTR Function

Analyzing and Reporting Data Using SQL

  • Overview of SQL for Analysis and Reporting FunctionsUsing Analytic Functions
  • Using the Ranking Functions
  • Using Reporting Functions

Performing Pivoting and Unpivoting Operations

  • Performing Pivoting Operations
  • Using the PIVOT and UNPIVOT Clauses
  • Pivoting on the QUARTER Column: Conceptual Example
  • Performing Unpivoting Operations
  • Using the UNPIVOT Clause Columns in an UNPIVOT Operation
  • Creating a New Pivot Table: Example

Pattern Matching using SQL

  • Row Pattern Navigation Operations
  • Handling Empty Matches or Unmatched Rows
  • Excluding Portions of the Pattern from the Output
  • Expressing All Permutations
  • Rules and Restrictions in Pattern Matching
  • Examples of Pattern Matching

Modeling Data Using SQL

  • Using the MODEL clause
  • Demonstrating Cell and Range References
  • Using the CV Function
  • Using FOR Construct with IN List Operator, incremental values and Subqueries
  • Using Analytic Functions in the SQL MODEL Clause
  • Distinguishing Missing Cells from NULLs
  • Using the UPDATE, UPSERT and UPSERT ALL Options
  • Reference Models
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