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Microsoft SQL Data Analysis Training Series
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!
$79.00
$79.00
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31 Training Hours
183 Videos
36 Topics
225 Practice Questions
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.
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.
Course Outline
Microsoft SQL Server 2019 - Introduction to Data Analysis Course Outline
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 Outline
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 Outline
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
Microsoft SQL Data Analysis Training Series
$79.00
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!
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