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Microsoft SQL Server 2019 – Introduction To Data Analysis

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77 Videos
13.58 Hours
75 Test Questions

Course Description

Microsoft SQL Server 2019 – Introduction To Data Analysis

The Microsoft SQL Server 2019 – Introduction to Data Analysis course is tailored for individuals new to data analysis and SQL Server 2019. This introductory course covers fundamental concepts and tools for analyzing data, making it ideal for beginners who want to build a solid foundation in data analysis using SQL Server. Participants will learn basic querying techniques, data manipulation, and how to start deriving insights from data.

Key Features:

  • Introduction to SQL Server: Get acquainted with the SQL Server 2019 environment, including installation, configuration, and basic navigation of SQL Server Management Studio (SSMS).
  • Basic Querying with T-SQL: Learn fundamental T-SQL (Transact-SQL) commands for querying data, including SELECT statements, filtering data with WHERE clauses, and sorting results with ORDER BY.
  • Data Manipulation: Understand how to insert, update, and delete data in SQL Server databases, including using basic DML (Data Manipulation Language) commands.
  • Data Aggregation: Explore aggregate functions such as COUNT, SUM, AVG, MIN, and MAX to summarize and analyze data.
  • Joining Tables: Learn how to combine data from multiple tables using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN to perform more comprehensive data analysis.
  • Introduction to Data Visualization: Gain an overview of data visualization techniques using SQL Server Reporting Services (SSRS) and other basic tools to create simple charts and reports.
  • Basic Data Transformation: Understand fundamental data transformation techniques, including using functions to manipulate and format data.
  • Introduction to Data Analysis Concepts: Get familiar with basic data analysis concepts such as data types, normalization, and the importance of data integrity.
  • Exploring SQL Server Tools: Discover additional SQL Server tools and features that support data analysis, such as SQL Server Integration Services (SSIS) and SQL Server Analysis Services (SSAS) at a basic level.

This course provides a comprehensive introduction to data analysis with SQL Server 2019, giving beginners the skills needed to start working with data and perform essential analysis tasks effectively.


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Step-by-Step Courses List

Chapter One:

Module 1 – Query Tools

1. Course Introduction
2. Intro to Management Studio
3. Intro to command-line query tools

Chapter Two:

Module 2 – Introduction to T-SQL Querying

1. Introducing T-SQL
2. Understanding Sets
3. Understanding the Logical Order of Operations in SELECT statements

Chapter Three:

Module 3 – Basic SELECT Queries

1. Writing Simple SELECT Statements
2. Eliminate Duplicates with DISTINCT
3. Using Column and Table Aliases
4. Write Simple CASE Expressions

Chapter Four:

Module 4 – Querying Multiple Tables

1. Understanding Joins
2. Querying with Inner Joins
3. Querying with Outer Joins
4. Querying with Cross Joins and Self Joins

Chapter Five:

Module 5 – Sorting and Filtering Data

1. Sorting Data
2. Filtering Data with Predicates
3. Filtering with the TOP and OFFSET-FETCH
4. Working with Unknown Values

Chapter Six:

Module 6 – Introduction to Business Intelligence and Data Modeling

1. Introduction to Business Intelligence
2. The Microsoft Business Intelligence Platform
3. Exploring a Data Warehouse
4. Exploring a Data Model

Chapter Seven:

Module 7 – Prepare Data

1. Introduction to Power BI
2. Get data from various data sources
3. Preview source data

Chapter Eight:

Module 8 – Clean, Transform, and Load Data

1. Data Transformation Intro
2. Transformation Example 1
3. Transformation Example 2
4. Transformation Example 3
5. Transformation Example 4
6. Transformation Example 5
7. Transformation Example 6

Chapter Nine:

Module 9 – Design a Data Model

1.Introduction to Data Modeling
2.Model Relationships
3.Table Configuration
4.Model interface
5.Quick Measures
6.Many-to-many relationships
7.Row-level security

Chapter Ten:

Module 10 – Create Model Calculations using DAX

1. DAX context
2. Calculated Tables
3. Calculated Columns
4. Managing Date Tables
5. Measures
6. Filter Manipulation
7. Time Intelligence

Chapter Eleven:

Module 11 – Create Reports

1. Basic Report Creation
2. Example Page 1
3. Example Page 2
4. Example Page 3
5. Report Publishing
6. Enhancing Reports
7. Drill-Through Pages
8. Conditional Formatting
9. Buttons and Bookmarks

Chapter Twelve:

Module 12 – Create Dashboards

1. Dashboard Basics
2. Real Time Dashboards
3. Enhanced Dashboards

Chapter Thirteen:

Module 13 – Create Paginated Reports

1. Introduction to Power BI Report Builder
2. Report Layouts
3. Report Data
4. Report Tables

Chapter Fourteen:

Module 14 – Perform Advanced Analytics

1. Introduction to Advanced Analytics
2. Scatter Chart
3. Forecast
4. Decomposition Tree
5. Key Influencers

Chapter Fifteen:

Module 15 – Create and Manage Workspaces

1. Introduction to Workspaces
2. Working with Workspaces and the Portal

Chapter Sixteen:

Module 16 – Create Power App Visuals

1. Introduction to Power Apps Visual
2. Creating the App
3. Basic Power Apps Concepts
4. Refreshing the Report

Chapter Seventeen:

Module 17 – Analysis Services and Power BI

1. Introduction to Analysis Services
2. Connecting with Multidimensional Models
3. Premium Workspaces and Analysis Services
4. Course Wrap Up

$84

course Syllabus

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Frequently Asked Questions

Instructional methods, course requirements, and learning technologies can vary significantly from one online program to the next, but the vast bulk of them use a learning management system (LMS) to deliver lectures and materials, monitor student progress, assess comprehension, and accept student work. LMS providers design these platforms to accommodate a multitude of instructor needs and preferences.

Online education may seem relatively new, but years of research suggests it can be just as effective as traditional coursework, and often more so. According to a U.S. Department of Education analysis of more than 1,000 learning studies, online students tend to outperform classroom-based students across most disciplines and demographics. Another major review published the same year found that online students had the advantage 70 percent of the time, a gap authors projected would only widen as programs and technologies evolve.

All new learning innovations are met with some degree of scrutiny, but skepticism subsides as methods become more mainstream. Such is the case for online learning. Studies indicate employers who are familiar with online degrees tend to view them more favorably, and more employers are acquainted with them than ever before. The majority of colleges now offer online degrees, including most public, not-for-profit, and Ivy League universities. Online learning is also increasingly prevalent in the workplace as more companies invest in web-based employee training and development programs.

The concern that online students cheat more than traditional students is perhaps misplaced. When researchers at Marshall University conducted a study to measure the prevalence of cheating in online and classroom-based courses, they concluded, “Somewhat surprisingly, the results showed higher rates of academic dishonesty in live courses.” The authors suggest the social familiarity of students in a classroom setting may lessen their sense of moral obligation.

Choosing the right course takes time and careful research no matter how one intends to study. Learning styles, goals, and programs always vary, but students considering online courses must consider technical skills, ability to self-motivate, and other factors specific to the medium. Online course demos and trials can also be helpful.
Our platform is typically designed to be as user-friendly as possible: intuitive controls, clear instructions, and tutorials guide students through new tasks. However, students still need basic computer skills to access and navigate these programs. These skills include: using a keyboard and a mouse; running computer programs; using the Internet; sending and receiving email; using word processing programs; and using forums and other collaborative tools. Most online programs publish such requirements on their websites. If not, an admissions adviser can help.

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Description

Microsoft SQL Server 2019 – Introduction To Data Analysis

The Microsoft SQL Server 2019 – Introduction to Data Analysis course is tailored for individuals new to data analysis and SQL Server 2019. This introductory course covers fundamental concepts and tools for analyzing data, making it ideal for beginners who want to build a solid foundation in data analysis using SQL Server. Participants will learn basic querying techniques, data manipulation, and how to start deriving insights from data.

Key Features:

  • Introduction to SQL Server: Get acquainted with the SQL Server 2019 environment, including installation, configuration, and basic navigation of SQL Server Management Studio (SSMS).
  • Basic Querying with T-SQL: Learn fundamental T-SQL (Transact-SQL) commands for querying data, including SELECT statements, filtering data with WHERE clauses, and sorting results with ORDER BY.
  • Data Manipulation: Understand how to insert, update, and delete data in SQL Server databases, including using basic DML (Data Manipulation Language) commands.
  • Data Aggregation: Explore aggregate functions such as COUNT, SUM, AVG, MIN, and MAX to summarize and analyze data.
  • Joining Tables: Learn how to combine data from multiple tables using INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN to perform more comprehensive data analysis.
  • Introduction to Data Visualization: Gain an overview of data visualization techniques using SQL Server Reporting Services (SSRS) and other basic tools to create simple charts and reports.
  • Basic Data Transformation: Understand fundamental data transformation techniques, including using functions to manipulate and format data.
  • Introduction to Data Analysis Concepts: Get familiar with basic data analysis concepts such as data types, normalization, and the importance of data integrity.
  • Exploring SQL Server Tools: Discover additional SQL Server tools and features that support data analysis, such as SQL Server Integration Services (SSIS) and SQL Server Analysis Services (SSAS) at a basic level.

This course provides a comprehensive introduction to data analysis with SQL Server 2019, giving beginners the skills needed to start working with data and perform essential analysis tasks effectively.


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