Course Information
Course Name: Microsoft SQL Server 2019 – Introduction to Data Analysis
Total Video Hours: 13 Hrs 58 Min
Total Videos: 77
Instructor: James Ring-Howell
This course introduces data analysis responsibilities and methods aligned with business and technical requirements. Instruction covers querying data with T-SQL, ingesting and transforming data, modeling datasets, implementing security, and designing reports and dashboards using Power BI and SQL Server 2019.
Included in This Course
77 professionally structured video lessons
Nearly 14 hours of data analysis instruction
SQL Server 2019 querying fundamentals
Transact-SQL SELECT query development
Data preparation, transformation, and modeling
Power BI report, dashboard, and paginated report creation
Advanced analytics and data visualization techniques
Power Apps and Analysis Services integration
Course Outline
Query Tools
Introduction to T-SQL Querying
Basic SELECT Queries
Querying Multiple Tables
Sorting and Filtering Data
Introduction to Business Intelligence and Data Modeling
Prepare DataClean, Transform, and Load Data
Design a Data Model
Create Model Calculations using DAX
Create Reports
Create Dashboards
Create Paginated Reports
Perform Advanced Analytics
Create and Manage Workspaces
Create Power App Visuals
Analysis Services and Power BI
Microsoft SQL Server 2019 – Introduction to Data Analysis
Microsoft SQL Server 2019 – Introduction to Data Analysis Online Course addresses the foundational skills required for modern data analysis within enterprise environments. Data analysts play a critical role in transforming raw data into meaningful insights that support strategic decision-making. SQL Server 2019, combined with Power BI, provides a powerful platform for querying, modeling, visualizing, and sharing data securely across organizations.
Query tools form the starting point of analytical workflows. The course explains how to work with SQL Server Management Studio and command-line query tools, ensuring familiarity with environments used for executing and managing queries. Understanding these tools allows analysts to interact directly with databases and validate data sources effectively.
Transact-SQL querying is central to data analysis using SQL Server. The course introduces T-SQL concepts and explains how SQL Server processes queries using set-based logic. Understanding sets and the logical order of operations in SELECT statements enables analysts to write accurate and efficient queries that return meaningful results.
Basic SELECT queries establish the foundation for data retrieval. The course explains how to write simple SELECT statements, eliminate duplicate values using DISTINCT, and apply column and table aliases to improve query readability. CASE expressions are introduced to support conditional logic within queries, enabling dynamic data interpretation.
Querying multiple tables is essential when working with normalized relational databases. The course explains different join types, including inner joins, outer joins, cross joins, and self joins. Understanding how tables relate to one another allows analysts to combine datasets accurately and maintain data integrity during analysis.
Sorting and filtering data refines analytical output. The course explains sorting techniques and filtering using predicates. Methods such as TOP and OFFSET-FETCH are covered to limit result sets efficiently. Handling unknown values ensures accurate filtering when working with incomplete or nullable data fields.
Business intelligence and data modeling concepts provide the bridge between raw data and analytical insight. The course explains the role of business intelligence within organizations and introduces the Microsoft Business Intelligence platform. Data warehouse exploration clarifies how analytical data structures differ from transactional systems, while data models demonstrate how relationships and measures support reporting.
Data preparation is a critical step in analytics workflows. The course introduces Power BI as a data preparation and visualization tool. Methods for accessing data from various relational and non-relational sources are explained, ensuring flexibility when working with diverse datasets. Previewing source data allows analysts to assess quality and structure before transformation.
Cleaning, transforming, and loading data ensures consistency and usability. The course explains data transformation concepts through practical examples. These transformations include shaping data, correcting inconsistencies, and preparing datasets for efficient modeling. Structured transformation processes improve report performance and accuracy.
Data modeling is addressed in depth. The course explains how to design data models that support scalability and performance. Relationship modeling, table configuration, and interface design are covered to ensure clarity and usability. Many-to-many relationships and row-level security are addressed to support complex analytical scenarios and secure data access.
Model calculations using Data Analysis Expressions (DAX) extend analytical capabilities. The course explains DAX context, calculated tables, and calculated columns. Managing date tables supports time-based analysis, while measures and filter manipulation enable advanced calculations. Time intelligence functions allow analysts to evaluate trends, comparisons, and period-over-period performance.
Report creation translates analytical models into visual insights. The course explains basic report creation and walks through multiple example report pages. Publishing reports enables sharing across teams, while enhancements such as drill-through pages, conditional formatting, buttons, and bookmarks improve interactivity and user experience.
Dashboards provide consolidated views of key metrics. The course explains dashboard basics and introduces real-time dashboards for monitoring live data. Enhanced dashboards support interactive exploration and executive-level reporting, enabling rapid insight delivery.
Paginated reports address structured reporting requirements. The course explains Power BI Report Builder, report layouts, data integration, and table design. Paginated reports support precise formatting and printing requirements commonly used in operational reporting.
Advanced analytics techniques extend analytical depth. The course explains tools such as scatter charts, forecasting, decomposition trees, and key influencers. These features enable analysts to identify patterns, predict outcomes, and understand drivers behind performance metrics.
Workspace management supports collaboration and governance. The course explains how to create and manage workspaces within the Power BI service. Working with the portal ensures proper access control, content organization, and deployment workflows.
Power App visuals integrate application functionality directly into reports. The course explains Power Apps concepts and demonstrates how to embed apps within Power BI. Context-aware data interaction allows users to take action directly from reports, enhancing operational efficiency.
Analysis Services integration connects Power BI with enterprise-grade semantic models. The course explains Analysis Services concepts, multidimensional model connectivity, and premium workspace integration. These features support large-scale deployments and advanced enterprise analytics.
The course concludes by reinforcing the role of SQL Server 2019 and Power BI in modern data analysis. By combining querying, modeling, visualization, and application integration, analysts gain the skills required to manage data effectively and support informed decision-making across organizations.
Frequently Asked Questions
Who should enroll in this SQL Server 2019 data analysis course?
This course is suitable for data analysts, business intelligence professionals, and IT staff responsible for querying, modeling, and visualizing data.
Does this course cover basic T-SQL query development?
Yes, the course includes instruction on writing SELECT queries, querying multiple tables, and sorting and filtering data.
Is Power BI included in the training?
Yes, Power BI is covered extensively, including data preparation, modeling, reporting, dashboards, and advanced analytics.
Are data security and access controls addressed?
Yes, the course explains row-level security, workspace management, and secure dataset handling.
Does the course include advanced analytics features?
Yes, forecasting, key influencers, decomposition trees, and advanced visualizations are included.
Are paginated reports and Power Apps integration covered?
Yes, the course includes paginated report creation and embedding Power Apps into Power BI reports.
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