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Microsoft SQL Data Analysis Training Series – 3 Courses
Become a Microsoft SQL server expert today with this Microsoft SQL Data Analysis Training Series course that contains everything you need to know! It includes Databases, Administration and an introduction to Power BI which will all help set yourself up for success in the future. Having these skills under your belt will be highly beneficial when it comes to job opportunities and salary growth – so don’t wait any longer; get started now!
Included In This Course
Included In This Course
31 Training Hours
183 On-demand Videos
Closed Captions
36 Topics
225 Prep Questions
Certificate of Completion
Course Description
Microsoft SQL Data Analysis Training Series and our comprehensive learning experience
This trio series will give you everything you need for Microsoft SQL Server Data Analysis toolsets. It contains SQL Server 2019 Introduction to Data Analysis, Database Administration, SQL Server Big Data and introduction to Microsoft Power BI for business intelligence professionals. SQL server will be around for years to come and becoming an expert will really help improve your employment opportunity and salary!
This training series includes the following courses:
- Introduction to Microsoft Power BI
- Microsoft SQL Server 2019 – Big Data
- Microsoft SQL Server 2019 Introduction to Data Analysis
What is a Data Analyst?
A data analyst is a professional who is responsible for collecting, organizing, and analyzing data in order to help businesses and organizations make informed decisions. Data analysts often work with large sets of data, using tools and techniques such as statistical analysis, data visualization, and machine learning to identify actionable insights, identify trends, patterns, critical insights and relationships in the data. They may also be responsible for developing and implementing processes for collecting and storing data, and for creating reports and presentations to share their findings with others. Data analysts may work in a variety of industries, including finance, healthcare, marketing, and retail.
Learn more about Microsoft PowerBI and Microsoft Big Data by visiting the Microsoft website.
Frequently Asked Questions About Microsoft SQL Data Analysis Training Series
What will I learn from the Microsoft SQL Data Analysis Training Series?
The training series is designed to turn you into a Microsoft SQL server expert. It covers various aspects including Databases, Administration, and an introduction to Power BI. These skills are essential for job opportunities and salary growth in the field of data analysis​​.
What does the course package include?
The training series includes three courses: Introduction to Microsoft Power BI, Microsoft SQL Server 2019 – Big Data, and Microsoft SQL Server 2019 Introduction to Data Analysis. These courses will provide you with a comprehensive understanding of Microsoft SQL Server Data Analysis toolsets.
How long is the course and what kind of materials will I get?
The course involves 31 hours of training, which includes 183 videos covering 36 topics. Additionally, you’ll get 225 practice questions to help reinforce what you’ve learned.
How does the subscription work? Can I cancel it anytime?
Yes, you can! When you subscribe, you get access to this training along with over 2,500 hours of on-demand content with the All Access Monthly Subscription. You can start with a 7-day free trial with no obligation and have the freedom to cancel at any time.
What is a data analyst and why would I want to become one?
A data analyst is a professional who collects, organizes, and analyzes data to help businesses make informed decisions. They use tools and techniques like statistical analysis, data visualization, and machine learning to find actionable insights, trends, patterns, and relationships in the data. If you’re keen on helping businesses make data-driven decisions or have a knack for numbers and patterns, this could be an exciting career path for you.
Will learning SQL Server be beneficial for my career in the long run?
Absolutely! SQL Server is a staple in the realm of data analysis and is expected to be around for years to come. Becoming an expert in SQL Server can significantly improve your employment opportunities and salary potential.
Proudly DisplayYour Achievement
Upon completion of your training, you’ll receive a personalized certificate of completion to help validate to others your new skills.
Course Outline
Microsoft SQL Server 2019 - Introduction to Data Analysis Course Content
Module 1 - Query Tools
1.1 Course Introduction
1.2 Intro to Management Studio
1.3 Intro to command-line query tools
Module 2 - Introduction to T-SQL Querying
2.1 Introducing T-SQL
2.2 Understanding Sets
2.3 Understanding the Logical Order of Operations in SELECT statements
Module 3 - Basic SELECT Queries
3.1 Writing Simple SELECT Statements
3.2 Eliminate Duplicates with DISTINCT
3.3 Using Column and Table Aliases
3.4 Write Simple CASE Expressions
Module 4 - Querying Multiple Tables
4.1 Understanding Joins
4.2 Querying with Inner Joins
4.3 Querying with Outer Joins
4.4 Querying with Cross Joins and Self Joins
Module 5 - Sorting and Filtering Data
5.1 Sorting Data
5.2 Filtering Data with Predicates
5.3 Filtering with the TOP and OFFSET-FETCH
5.4 Working with Unknown Values
Module 6 - Introduction to Business Intelligence and Data Modeling
6.1 Introduction to Business Intelligence
6.2 The Microsoft Business Intelligence Platform
6.3 Exploring a Data Warehouse
6.4 Exploring a Data Model
Module 7 - Prepare Data
7.1 Introduction to Power BI
7.2 Get data from various data sources
7.3 Preview source data
Module 8 - Clean, Transform, and Load Data
8.1 Data Transformation Intro
8.2 Transformation Example 1
8.3 Transformation Example 2
8.4 Transformation Example 3
8.5 Transformation Example 4
8.6 Transformation Example 5
8.7 Transformation Example 6
Module 9 - Design a Data Model
9.1 Introduction to Data Modeling
9.2 Model Relationships
9.3 Table Configuration
9.4 Model interface
9.5 Quick Measures
9.6 Many-to-many relationships
9.7 Row-level security
Module 10 - Create Model Calculations using DAX
10.1 DAX context
10.2 Calculated Tables
10.3 Calculated Columns
10.4 Managing Date Tables
10.5 Measures
10.6 Filter Manipulation
10.7 Time Intelligence
Module 11 - Create Reports
11.1 Basic Report Creation
11.2 Example Page 1
11.3 Example Page 2
11.4 Example Page 3
11.5 Report Publishing
11.6 Enhancing Reports
11.7 Drill-Through Pages
11.8 Conditional Formatting
11.9 Buttons and Bookmarks
Module 12 - Create Dashboards
12.1 Dashboard Basics
12.2 Real Time Dashboards
12.3 Enhanced Dashboards
Module 13 - Create Paginated Reports
13.1 Introduction to Power BI Report Builder
13.2 Report Layouts
13.3 Report Data
13.4 Report Tables
Module 14 - Perform Advanced Analytics
14.1 Introduction to Advanced Analytics
14.2 Scatter Chart
14.3 Forecast
14.4 Decomposition Tree
14.5 Key Influencers
Module 15 - Create and Manage Workspaces
15.1 Introduction to Workspaces
15.2 Working with Workspaces and the Portal
Module 16 - Create Power App Visuals
16.1 Introduction to Power Apps Visual
16.2 Creating the App
16.3 Basic Power Apps Concepts
16.4 Refreshing the Report
Module 17 - Analysis Services and Power BI
17.1 Introduction to Analysis Services
17.2 Connecting with Multidimensional Models
17.3 Premium Workspaces and Analysis Services
17.4 Course Wrap Up
Introduction to Microsoft Power BI Course Content
Module 1 - Prepare Data
1.1 Course Introduction
1.2 Module 1 Introduction
1.3 Introduction to Power BI
1.4 Get data from various data sources
1.5 Preview source data
Module 2 - Clean, Transform, and Load Data
2.1 Module 2 Introduction
2.2 DimEmployee Example
2.3 DimEmployeeSalesTerritory Example
2.4 DimReseller Example
2.5 FactResellersSales Example
2.6 ResellerSalesTargets Example
2.7 Color Formats Example
Module 3 - Design a Data Model
3.1 Module 3 Introduction
3.2 Introduction to Data Modeling
3.3 Model Relationships
3.4 Table Configuration
3.5 Model interface
3.6 Quick Measures
3.7 Many-to-many relationships
3.8 Row-level security
Module 4 - Create Model Calculations using DAX
4.1 Module 4 Introduction
4.2 DAX context
4.3 Calculated Tables
4.4 Calculated Columns
4.5 Managing Date Tables
4.6 Measures
4.7 Filter Manipulation
4.8 Time Intelligence
Module 5 - Create Reports
5.1 Module 5 Introduction
5.2 Basic Report Creation
5.3 Example Page 1
5.4 Example Page 2
5.5 Example Page 3
5.6 Report Publishing
5.7 Enhancing Reports
5.8 Drill-Through Pages
5.9 Conditional Formatting
5.10 Buttons and Bookmarks
Module 6 - Create Dashboards
6.1 Module 6 Introduction
6.2 Dashboard Basics
6.3 Real Time Dashboards
6.4 Enhanced Dashboards
Module 7 - Create Paginated Reports
7.1 Module 7 Introduction
7.2 Introduction to Power BI Report Builder
7.3 Report Layouts
7.4 Report Data
7.5 Report Tables
Module 8 - Perform Advanced Analytics
8.1 Module 8 Introduction
8.2 Introduction to Advanced Analytics
8.3 Scatter Chart
8.4 Forecast
8.5 Decomposition Tree
8.6 Key Influencers
Module 9 - Create and Manage Workspaces
9.1 Introduction to Workspaces
9.2 Working with Workspaces and the Portal
Module 10 - Create Power App Visuals
10.1 Module 10 Introduction
10.2 Introduction to Power Apps Visual
10.3 Creating the App
10.4 Basic Power Apps Concepts
10.5 Refreshing the Report
Module 11 - Analysis Services and Power BI
11.1 Module 11 Introduction
11.2 Introduction to Analysis Services
11.3 Connecting with Multidimensional Models
11.4 Premium Workspaces and Analysis Services
11.5 Course Wrap Up
Microsoft SQL Server - Big Data Course Content
Module 1: What are Big Data Clusters?
1.1 Introduction
1.2 Linux, PolyBase, and Active Directory
1.3 Scenarios
Module 2: Big Data Cluster Architecture
2.1 Introduction
2.2 Docker
2.3 Kubernetes
2.4 Hadoop and Spark
2.5 Components
2.6 Endpoints
Module 3: Deployment of Big Data Clusters
3.1 Introduction
3.2 Install Prerequisites
3.3 Deploy Kubernetes
3.4 Deploy BDC
3.5 Monitor and Verify Deployment
Module 4: Loading and Querying Data in Big Data Clusters
4.1 Introduction
4.2 HDFS with Curl
4.3 Loading Data with T-SQL
4.4 Virtualizing Data
4.5 Restoring a Database
Module 5: Working with Spark in Big Data Clusters
5.1 Introduction
5.2 What is Spark
5.3 Submitting Spark Jobs
5.4 Running Spark Jobs via Notebooks
5.5 Transforming CSV
5.6 Spark-SQL
5.7 Spark to SQL ETL
Module 6: Machine Learning on Big Data Clusters
6.1 Introduction
6.2 Machine Learning Services
6.3 Using MLeap
6.4 Using Python
6.5 Using R
Module 7: Create and Consume Big Data Cluster Apps
7.1 Introduction
7.2 Deploying, Running, Consuming, and Monitoring an App
7.3 Python Example - Deploy with azdata and Monitoring
7.4 R Example - Deploy with VS Code and Consume with Postman
7.5 MLeap Example - Create a yaml file
7.6 SSIS Example - Implement scheduled execution of a DB backup
Module 8: Maintenance of Big Data Clusters
8.1 Introduction
8.2 Monitoring
8.3 Managing and Automation
8.4 Course Wrap Up
Your Training Instructor
James is a full-stack developer with over 40 years of experience. He has developed applications across all major industries and for Fortune 100 companies as well as local small businesses. James has also been teaching technology courses for over 20 years. In addition to his extensive background in technology, he has also worked as a professional opera singer.
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Microsoft SQL Data Analysis Training Series – 3 Courses
ON SALE 40% OFF
Microsoft SQL Data Analysis Training Series – 3 Courses
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