Power BI
$1595
Per Participant
In this instructor-led training, Microtek Learning teaches students how to write T-SQL queries for database analysis, reporting, and business intelligence. This course presents TSQL within the data analysis context to be specific, creating purpose using data rather than developing transaction-oriented data-tier applications. The course explains measurement levels and quantitative research methodology and submerges all the explained concepts with the presented TSQL topics. The objective here is to give a continuous, straightforward, and meaningful learning path for data retrieval from relational databases to use in analytical tools including SQL SRS, R, Power BI, and Excel.
This training is designed based on the objectives of the course variant 55232A.
Before going to 55232: Writing Analytical Queries for Business Intelligence course, understudies must have:
The course is aimed at IT pros and data scientists seeking to learn how to use database analysis and reporting tools: SQL SRS, Power BI, R, SAS, Excel and more. They also look to learn using TSQL queries to retrieve data sets effectively through SQL server RDBMS to use with other tools.
Microtek Learning is a Microsoft Certified Partner for Learning Solutions. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
This module discusses writing analytical queries vs. transactional DML queries, and describes the typical architecture of a business intelligence environment. It discusses the role of SELECT queries in retrieving data for analysis from relational databases. It introduces the sample database to be used in the course, and begins a presentation of the SELECT query.
Lessons
Lab: Introduction to TSQL for Business Intelligence
After completing this module, students will be able to:
This module covers the identification of and relationship between levels of measurement and column data types. It continues a discussion of the SELECT query and adds the WHERE and ORDER BY clauses.
Lessons
Lab: Write queries using:
After completing this module, students will be able to:
Module 3 discusses creating single datasets for analysis by combining results from multiple database tables using JOIN.
Lessons
Lab: Write SELECT queries using:
After completing this module, students will be able to:
This module covers the aggregation of quantitative column values across grouping factors for the purpose of groupwise comparisons and/or changing the granularity of a dataset.
Lessons
Lab: Write queries using:
After completing this module, students will be able to:
This module covers the use of subqueries, derived tables, and common table expressions in SELECT queries as techniques for creating intermediate result sets.
Lessons
Lab: Write queries using:
After completing this module, students will be able to:
This module discusses the encapsulation of data retrieval logic in views, table-valued functions, and stored procedures. It also describes scenarios in which these techniques are useful for producing datasets for analysis. Finally, it describes the database security issues involved, and techniques for creating and using these database objects while maintaining current permission sets on source data.
Lessons
Lab: Encapsulating Data Retrieval Logic
After completing this module, students will be able to:
This module covers common techniques for making datasets produced by SELECT queries available to analytical client tools such as SQL Server Reporting Services, PowerBI, Excel, and R. It discusses running queries directly from the client tool, in addition to exporting datasets to text files which can then be accessed by the client tool.
Lessons
Lab: Getting Your Dataset to the Client
After completing this module, students will be able to:
For many years, Microtek Learning has been helping organizations, leaders, and professionals to reach their maximum performance by addressing the challenges they are facing.
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