Data Warehousing & Visualization in Microsoft BI & Power BI

Name: Data Warehousing & Visualization in Microsoft BI & Power BI
Rating: 4.3 (528 reviews)

Learn ETL, Data Analysis and Visualization using Microsoft Excel, Microsoft Business Intelligence tools and Power BI

Created byData Science Guide

Last updated 8/2025

English

What you'll learn

Understand Data Warehousing Terminology
Understand the difference between OLTP and OLAP
Install and use MS SQL Server and SQL Server Management Studio
Install and use Microsoft Business Intelligence tools (SSIS and SSRS)
Understand and use how to extract, transform, and load data (ETL process) with SSIS
Introduced to different Flat files
Clean CSV files using Microsoft Excel
Use simple and efficient ETL that avoid many of expecting errors
USE SSRS to create different types of business reports
Practice data analysis while creating SSRS reports

Course content

21 sections • 149 lectures • 8h 17m total length

Introduction to course3:42
Course contents2:13
Explore data warehousing fundamentals and ETL concepts, install and use Microsoft SQL Server tools, and build end-to-end projects from data cleaning in Excel to BI reporting.
Control the pace of a video0:44
What is Data Warehousing0:54
Which of the following steps is not part of data warehousing
OLTP and OLAP2:55
Which of the following is not a characteristic of OLAP
What is ETL1:28
The difference between ETL and ELT0:29
Which of the following two is correct
What is Data Management1:03
Which of the following is not part of data management
Course Rating0:16

What is Relational Database Management System (RDBMS)1:15
Which one of the following is not a database management system
Install MS SQL Server and Management Studio2:39
Install SQL Server Express 2017 and SQL Server Management Studio by downloading from the official download center, following the basic install steps, and then learn to navigate SSMS.
Introduction to SQL Server Management Studio (SSMS)2:44

Data types in MS SQL Server3:51
Overview on the data file3:49
Clean the data in MS Excel7:25
Copy original file, convert it to txt, import into excel as comma-delimited csv, set text formats with text to columns, save as csv, and move to load folder for ETL.
Create the database in SSMS2:11
Create a database in SQL Server Management Studio to serve as a data warehouse. Connect to the server, run create database with a meaningful name, and review the generated objects.
Create the SSIS project in MS Visual Studio Shell for the ETL process - Part 19:21
Create the SSIS project in MS Visual Studio Shell for the ETL process - Part 21:54
Create the working table in SSMS for data analysis4:07
Create a working table in ssms for data analysis by defining a new table from the stage table, setting correct data types, and loading data for analysis.
Course Rating0:16

Overview on the data file1:05
Examine a semicolon-delimited csv where Excel cannot split columns, revealing car sales by manufacturer, model, sale date, fuel efficiency, and price in thousands, with cleaning preview for the ADL process.
Clean the data file in MS Excel5:38
Create the database in SSMS0:59
Create the SSIS project in MS Visual Studio Shell for the ETL process5:48
Create the working table in SSMS for data analysis5:24
Course Rating0:16

Clean the data file in MS Excel3:51
Create the warehouse database in SSMS0:35
Open SQL Server Management Studio, create a new database named Boston, execute the command, and refresh databases to confirm the warehouse setup for the FTL process.
Create the SSIS project in MS Visual Studio Shell - Part 110:38
Check the anomalies rows2:40
Create the working table in SSMS for data analysis5:06
Homework0:58
Homework Solution4:54
Solve the homework by cleaning a faulty comma-delimited file, importing it into Excel, restoring headers from the CSP file, and transferring seven rows via a flat file data flow.

Clean the data file in MS Excel4:41
Clean the movies dataset in MS Excel by converting a CSV to Excel, applying text formatting across columns, and preparing data for loading into a data warehouse for BI reporting.
Create the warehouse database in SSMS and ETL SSIS project4:19
Create a warehouse database in SSMS, set up an SSIS ETL project, configure a flat file source, map to a raw movies data table, load 5043 records and verify.
Create the working table in SSMS for data analysis6:41

Clean the data file in MS Excel2:50
Create the warehouse database in SSMS and ETL SSIS project3:45
Create the working table in SSMS for data analysis - Part 13:02
Validate the transfer of 84,811 records, then create a fresh working table in SSMS from the raw data, drop the existing table, and define appropriate data types for quality assurance.
Create the working table in SSMS for data analysis - Part 24:38
Insert data into the working table and identify a conversion error from non-numeric zip codes. Create a second table with a different data type for zip codes, using length 100.

Requirements

Basic knowledge of SQL

Description

Data Warehousing

Learning how to extract, clean and load data into a SQL database warehouse are highly required skills for data analysis field. You will learn in this course how to use Microsoft Excel to clean your data before loading them into a Microsoft SQL Server database. You will learn how to use SQL Server Integration Services (SSIS) which is one of Microsoft Business Intelligence tools to perform ETL process. You will learn a simple technique that save you a lot of time and help to avoid many possible errors during the ETL process. You will learn also how to use SQL Server Reporting Services (SSRS) to create business reports and data analysis with SQL queries. This course is designed to be more practical by putting your hands on real projects with diverse business scenarios to learn by practice. Learning via practice is the best way to get knowledge stuck in your mind because it is similar to acquire experience through work.

Power BI

Converting raw data to insightful diagrams and charts to make informative decisions is a crucial analytical skill in data science. You will learn in this course how to create insightful and powerful charts and perform data analysis. First, you will understand data visualization, and why data visualization. After that you will understand Power BI services and the use of each of them. After you became familiar with these services you will learn how to install and navigate in Power BI Desktop. After that, you will learn how to use the advanced functions in Power BI Editor in data preparation and cleaning. You will learn appending and merging datasets to create one dataset. After that you will learn how to turn your datasets into insightful charts using many powerful functions. You will learn how to filter your data according to your business requirements. You will learn how to create measures and calculated columns for your own data analysis. You will have an introduction to DAX language where you can learn how to create new tables and columns according to your needs. After that you will learn how to take your projects in the Cloud where you can work with other users. You will learn how use Power BI Pro interface to create, edit and share reports with others.

Who this course is for:

Anyone wants to learn data warehousing, data analysis, and ETL from scratch using Microsoft BI

Data Warehousing & Visualization in Microsoft BI & Power BI

What you'll learn

Explore related topics

Course content

Introduction9 lectures • 14min

Database Management System3 lectures • 7min

Introduction to Microsoft Business Intelligence2 lectures • 4min

ETL Project 1 (Companies Expenses and Profits)8 lectures • 33min

ETL Project 2 (Car Sales)6 lectures • 19min

ETL Project 3 (Boston Crimes)7 lectures • 29min

ETL Project 4 (Movies Data)3 lectures • 16min

ETL Project 5 (Bank Customers Complaints)4 lectures • 14min

ETL Homework Project1 lecture • 2min

SSRS Project1 (Companies Expenses and Profits)3 lectures • 13min

Requirements

Description

Who this course is for: