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    Data Warehousing & Visualization In Microsoft Bi & Power Bi

    Posted By: ELK1nG
    Data Warehousing & Visualization In Microsoft Bi & Power Bi

    Data Warehousing & Visualization In Microsoft Bi & Power Bi
    Last updated 5/2022
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 3.97 GB | Duration: 8h 16m

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

    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 Business Intelligence tools (SSIS and SSRS)
    Understand and use ETL via 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
    Requirements
    Basic knowledge of SQL
    Description
    Data WarehousingLearning 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 BIConverting 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.

    Overview

    Section 1: Introduction

    Lecture 1 Introduction to course

    Lecture 2 Course contents

    Lecture 3 Control the pace of a video

    Lecture 4 What is Data Warehousing

    Lecture 5 OLTP and OLAP

    Lecture 6 What is ETL

    Lecture 7 What is Data Management

    Lecture 8 Course Rating

    Section 2: Database Management System

    Lecture 9 What is Relational Database Management System (RDBMS)

    Lecture 10 Install MS SQL Server and Management Studio

    Lecture 11 Introduction to SQL Server Management Studio (SSMS)

    Section 3: Introduction to Microsoft Business Intelligence

    Lecture 12 Introduction to Microsoft Business Intelligence

    Lecture 13 Install MS Business Intelligence package

    Section 4: ETL Project 1 (Companies Expenses and Profits)

    Lecture 14 Data types in MS SQL Server

    Lecture 15 Overview on the data file

    Lecture 16 Clean the data in MS Excel

    Lecture 17 Create the database in SSMS

    Lecture 18 Create the SSIS project in MS Visual Studio Shell for the ETL process - Part 1

    Lecture 19 Create the SSIS project in MS Visual Studio Shell for the ETL process - Part 2

    Lecture 20 Create the working table in SSMS for data analysis

    Lecture 21 Course Rating

    Section 5: ETL Project 2 (Car Sales)

    Lecture 22 Overview on the data file

    Lecture 23 Clean the data file in MS Excel

    Lecture 24 Create the database in SSMS

    Lecture 25 Create the SSIS project in MS Visual Studio Shell for the ETL process

    Lecture 26 Create the working table in SSMS for data analysis

    Lecture 27 Course Rating

    Section 6: ETL Project 3 (Boston Crimes)

    Lecture 28 Clean the data file in MS Excel

    Lecture 29 Create the warehouse database in SSMS

    Lecture 30 Create the SSIS project in MS Visual Studio Shell - Part 1

    Lecture 31 Check the anomalies rows

    Lecture 32 Create the working table in SSMS for data analysis

    Lecture 33 Homework

    Lecture 34 Homework Solution

    Section 7: ETL Project 4 (Movies Data)

    Lecture 35 Clean the data file in MS Excel

    Lecture 36 Create the warehouse database in SSMS and ETL SSIS project

    Lecture 37 Create the working table in SSMS for data analysis

    Section 8: ETL Project 5 (Bank Customers Complaints)

    Lecture 38 Clean the data file in MS Excel

    Lecture 39 Create the warehouse database in SSMS and ETL SSIS project

    Lecture 40 Create the working table in SSMS for data analysis - Part 1

    Lecture 41 Create the working table in SSMS for data analysis - Part 2

    Section 9: ETL Homework Project

    Lecture 42 Introduction to homework

    Section 10: SSRS Project1 (Companies Expenses and Profits)

    Lecture 43 Create SSRS Project and Report

    Lecture 44 Create Datasource, Dataset, and Table

    Lecture 45 Add formatting to report

    Section 11: SSRS Project 2 (Movies Data)

    Lecture 46 Create SSRS project and a report

    Lecture 47 Use Group by in the report

    Lecture 48 Use visibility and hidden functions in the report

    Lecture 49 Add calculated field to the report

    Lecture 50 Add parameters to the report - Part 1

    Lecture 51 Add parameters to the report - Part 2

    Section 12: SSRS Project 3 (Employee Reviews)

    Lecture 52 Create SSRS project and report

    Lecture 53 Use visibility and hidden functions in report

    Lecture 54 Use parameters to filter report data

    Lecture 55 Use matrix in report

    Lecture 56 Create a chart to visualize data

    Section 13: SSRS Project 4 (Cars Sales)

    Lecture 57 Create SSRS project and report

    Lecture 58 Create a chart to visualize data

    Lecture 59 Use matrix in report

    Section 14: SSRS Project 5 (Boston Crimes)

    Lecture 60 Create SSRS project and report

    Lecture 61 Use Group by in report - Part 1

    Lecture 62 Use Group by in report - Part 2

    Lecture 63 Use Group by in report - Part 3

    Lecture 64 Create a chart to visualize data

    Section 15: SSRS Homework Project

    Lecture 65 Introduction to homework

    Section 16: ETL Homework Project Solution

    Lecture 66 Clean dataset in MS Excel

    Lecture 67 Implement ETL prcess - Part 1

    Lecture 68 Implement ETL prcess - Part 2

    Lecture 69 Create Work Table for data analysis in SSMS

    Section 17: SSRS Homework Project Solution

    Lecture 70 Number of issues

    Lecture 71 Number of issues per year

    Lecture 72 Products have most issues

    Lecture 73 States have most issues

    Lecture 74 Number of issues per bank(company)

    Lecture 75 Number of issues that are not timely response

    Lecture 76 Issues that are not closed yet

    Lecture 77 Create a report using a matrix to address the number of issues per bank and year

    Lecture 78 Create a chart showing number of issues in every month

    Lecture 79 Final Course Rating

    Section 18: Introduction to Data Visualization

    Lecture 80 Introduction to Course

    Lecture 81 Introduction to Section 1

    Lecture 82 What is Power BI

    Lecture 83 Install Power BI Desktop

    Lecture 84 Change setting in Power BI Desktop

    Lecture 85 Start Power BI Desktop

    Section 19: Data Cleaning and Preparation

    Lecture 86 Overview on the business dataset

    Lecture 87 Connect to a data source

    Lecture 88 Remove N/A rows and use first row as headers names

    Lecture 89 Introduction to Pivot and Unpivot operators

    Lecture 90 Unpivoting columns

    Lecture 91 Split columns and change data types

    Lecture 92 Other ways to split columns

    Lecture 93 Introduction to M Language

    Lecture 94 Remove empty rows from a dataset

    Lecture 95 Identify the granular data level in the dataset

    Lecture 96 Remove duplicated rows in a dataset

    Lecture 97 Connect to another data source

    Lecture 98 Introduction to Append operator

    Lecture 99 Append queries in Power BI Query Editor

    Lecture 100 Introduction to data types in Power BI

    Lecture 101 Set proper data types in a dataset

    Lecture 102 Fix a data conversion error

    Lecture 103 Introduction to Star Schema Model

    Lecture 104 Create a Star Schema Model in Power BI

    Lecture 105 Create the Country dimension table

    Lecture 106 Create the Product and Segment dimensions tables

    Lecture 107 Create the Fact Sales table

    Lecture 108 Introduction to the Merge operator

    Lecture 109 Merge queries in Power Query Editor

    Lecture 110 Organize datasets in groups

    Lecture 111 More useful functions in Power Query Editor

    Lecture 112 Disable loading unused files into Power BI

    Lecture 113 Project 2 file in Power BI

    Section 20: Data Visualization

    Lecture 114 Introduction to Data Visualization

    Lecture 115 Create the first chart

    Lecture 116 Filter data in charts

    Lecture 117 Use top N feature in filters

    Lecture 118 Formatting charts part-1

    Lecture 119 Formatting charts part-2

    Lecture 120 Add analytical lines to charts

    Lecture 121 Fix the merging problems between queries

    Lecture 122 Create a TreeMap chart

    Lecture 123 Advanced color formatting in charts

    Lecture 124 Add Slicer to charts

    Lecture 125 Create a Map chart

    Lecture 126 Measure vs Calculated column

    Lecture 127 Create a measure in Power BI Desktop

    Lecture 128 Create a calculated column

    Lecture 129 Create a Pie chart

    Lecture 130 Prepare a time series dataset

    Lecture 131 Create a Line chart

    Lecture 132 Drilling in a Hierarchy dimensions

    Lecture 133 Change themes of reports

    Lecture 134 Introduction to DAX Language

    Lecture 135 Arithmetic functions in DAX

    Lecture 136 DAX operators

    Lecture 137 Date functions in DAX

    Lecture 138 Logical functions in DAX

    Lecture 139 Text concatenation functions in DAX

    Section 21: Work on Projects in the Cloud with Power BI Pro

    Lecture 140 Introduction to Power BI Pro

    Lecture 141 Login to Power BI Pro

    Lecture 142 Quick overview on Power BI Pro interface

    Lecture 143 Browse and edit projects in Power BI Pro

    Lecture 144 Create a Dashboard in Power BI Pro

    Lecture 145 Overview on My workspace in Power BI Pro

    Lecture 146 Install a Gateway

    Lecture 147 Overview on Workspaces in Power BI Pro

    Lecture 148 Apps in Power BI Pro

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