Writing Analytical Queries for Business Intelligence - MOC55232


This three-day instructor-led course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. Specifically, this course presents TSQL within the context of data analysis – in other words, making meaning from the data rather than transaction-oriented data-tier application development. The course starts with a brief discussion of levels of measurement and quantitative research methodogy, and integrates these concepts into each TSQL topic presented. The goal is to provide a consistent, direct, and purposeful learning path from RDBMS data retrieval through analytical tools such as SQL Server Reporting Services, PowerBI, Excel, R, SAS, and SPSS.

Nach Abschluss dieses Seminars haben die Teilnehmer Wissen zu folgenden Themen:
  • Identify independent and dependent variables and measurement levels in their own analytical work scenarios.
  • Identify variables of interest in relational database tables.
  • Choose a data aggregation level and data set design appropriate for the intended analysis and tool.
  • Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others.
  • Create stored procedures, views, and functions to modularize data retrieval code.

expand_more chevron_right Zielgruppe

Dieses Seminar richtet sich an:
  • This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools.

expand_more chevron_right Vorkenntnisse

Für dieses Seminar werden folgende Kenntnisse empfohlen:
  • Context knowledge of data analysis and business intelligence scenarios. For example, an understanding of a work-related business intelligence project or need.
  • Basic knowledge of the Windows operating system and its core functionality, including file system navigation.
  • Basic understanding of the purpose of relational database management systems such as SQL Server.

expand_more chevron_right Detail-Inhalte

  1. Introduction to TSQL for Business Intelligence
    1. Two Approaches to SQL Programming
    2. TSQL Data Retrieval in an Analytics / Business Intelligence Environment
      1. The Database Engine
  2. SQL Server Management Studio and the CarDeal Sample Database
    1. Identifying Variables in Tables
    2. SQL is a Declarative Language
    3. Introduction to the SELECT Query
  3. Turning Table Columns into Variables for Analysis: SELECT List Expressions, WHERE, and ORDER BY
    1. Turning Columns into Variables for Analysis
    2. Column Expressions, Data Types, and Built-in Functions
    3. Column aliases
    4. Data type conversions
    5. Built-in Scalar Functions
    6. Table Aliases
    7. The WHERE clause
    8. ORDER BY
  4. Combining Columns from Multiple Tables into a Single Dataset: The JOIN Operators
    1. Primary Keys, Foreign Keys, and Joins
    2. Understanding Joins, Part 1: CROSS JOIN and the Full Cartesian Product
    3. Understanding Joins, Part 2: The INNER JOIN
    4. Understanding Joins, Part 3: The OUTER JOINS
    5. Understanding Joins, Part 4: Joining more than two tables
    6. Understanding Joins, Part 5: Combining INNER and OUTER JOINs
    7. Combining JOIN Operations with WHERE and ORDER BY
  5. Creating an Appropriate Aggregation Level Using GROUP BY
    1. Identifying required aggregation level and granularity
    2. Aggregate Functions
    3. GROUP BY
    4. HAVING
    5. Order of operations in SELECT queries
  6. Subqueries, Derived Tables and Common Table Expressions
    1. Non-correlated and correlated subqueries
    2. Derived tables
    3. Common table expressions
  7. Encapsulating Data Retrieval Logic
    2. Table-valued functions
    3. Stored procedures
    4. Creating objects for read-access users
    5. Creating database accounts for analytical client tools
  8. Getting Your Dataset to the Client
    1. Connecting to SQL Server and Submitting Queries from Client Tools
    2. Connecting and running SELECT queries from:
    3. Excel
    4. PowerBI
    5. RStudio
    6. Exporting datasets to files using
    7. Results pane from SSMS
    8. The bcp utility
    9. The Import/Export Wizard

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