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Microsoft SQL Server 2019 – Introduction To Data Analysis

Course Description

13.58 Hours

77 Videos

This course will discuss the responsibilities and functions of a data analyst. Which includes the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

This course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI. Power BI is a member of the Power Platform. Power Apps is another component that enables everyone to build and use apps that connect to business data. This course will show you how to use the Power Apps visual to pass context-aware data to a canvas app, which updates in real-time as you make changes to your report. This will allow your app users to derive business insights and take actions from right within their Power BI reports and dashboards.

Key Learning Topics In This Course

  • Ingest, clean, and transform data
  • Model data for performance and scalability
  • Design and create reports for data analysis
  • Apply and perform advanced report analytics
  • Manage and share report assets
  • Create paginated reports in Power BI
  • Embed Power Apps into Power BI
  • Understand the similarities and differences between Transact-SQL and other computer languages.
  • Write SELECT queries
  • Query multiple tables
  • Sort and filter data

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Course Syllabus

Module 1 – Query Tools

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

Module 2 – Introduction to T-SQL Querying

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

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

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

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

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

Module 7 – Prepare Data

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

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

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

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

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

Module 12 – Create Dashboards

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

Module 13 – Create Paginated Reports

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

Module 14 – Perform Advanced Analytics

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

Module 15 – Create and Manage Workspaces

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

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

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

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You Will Get Certification After Completetion This Course.

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How does online education work on a day-to-day basis?
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.
Is online education as effective as face-to-face instruction?
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.
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Is online education more conducive to cheating?
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.
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