Course Code: 29426

Advanced Data Modeling and DAX in Power BI

Class Dates:
1/1/0001
Length:
2 Days
Cost:
$1495.00
Class Time:
Technology:
Business
Delivery:
Instructor-Led Training, Virtual Instructor-Led Training

Overview

  • Course Overview
  • In this Power BI course, participants develop a deep understanding of Power BI’s data modeling and DAX capabilities. They explore advanced techniques for creating and optimizing data relationships, categorization, and hierarchical structures. The course also covers powerful DAX expressions, statistical functions, and best practices for enhancing performance. Through hands-on exercises, participants learn to build efficient, high-performing reports and dashboards using advanced Power BI techniques.

    Understand and implement different data modeling approaches, including Star and Snowflake schemas, Create and optimize relationships, hierarchies, and groupings for efficient data representation, Develop proficiency in writing and debugging complex DAX expressions, Apply statistical and ranking functions to perform advanced analytics in Power BI, Optimize Power BI performance using best practices, query folding, and performance analysis tools
  • Audience
  • Setup Requirements A computer with an internet connection is required. A remote lab VM with all necessary accounts will be provided to each participant.

Prerequisites

  • Basic understanding of Power BI, including data loading and report creation
    Familiarity with fundamental DAX functions and concepts
    Basic knowledge of relational database concepts and SQL (recommended)

Course Disclaimer

*Course Cost listed does not include the cost of courseware. Course is subject to a minimum enrollment to run. Course may run virtually as a Virtual Instructor-Led (VILT) class if the minimum enrollment is not met. If the course is under the minimum enrollment the course may run as 1 day class (Bootcamp Style). For more information, please contact learn@vtec.org or call 207-775-0244.

Course Details

  • Data Modeling in Power BI
  • Understanding Data Modeling
  • Star vs. Snowflake Schema: When to Use Each
  • Creating Relationships: One-to-One, One-to-Many, and Many-to-Many
  • Organizing Data: Display Formats, Categorization, and Folders
  • Building Hierarchies for Efficient Data Navigation
  • Grouping and Binning for Aggregated Insights
  • A Quick Overview of DAX
  • What is DAX?
  • Calculated measures, columns, and tables
  • Using SUM and SUMX
  • Usuing FILTER
  • Using CALCULATE
  • Statistical and Ranking Functions in DAX
  • Ranking Functions: RANKX, RANK.EQ, RANK.AVG, DENSERANK, PERCENTRANKX
  • Quartile and Percentile Functions: NTILE, QUARTILE.EXC, QUARTILE.INC, PERCENTILE.EXC, PERCENTILE.INC
  • Central Tendency Measures: MEAN, MEDIAN
  • Standard Deviation and Variance: STDEV.P, STDEV.S, VAR.P, VAR.S
  • Advanced Statistical Functions: SKEWNESS, KURTOSIS, COVARIANCE.P, COVARIANCE.S, CORREL
  • ANOVA: Performing Variance Analysis in Power BI
  • Data Sampling and Filtering in DAX
  • Using SAMPLE and TOPN for Data Sampling
  • Generating Random Data with RAND()
  • Filtering Techniques: SWITCH, FILTER, and ALL Functions
  • Concatenating Text Data: CONCATENATE() and CONCATENATEX()
  • Counting Functions: COUNT(), COUNTA(), COUNTBLANK(), COUNTROWS(), DISTINCTCOUNT(), DISTINCTCOUNTNOBLANK()
  • Advanced DAX Concepts
  • Working with Calculation Groups in Tabular Editor
  • Creating Dedicated Tables for Measures
  • Using Variables in DAX for Performance Optimization
  • Advanced Variable Techniques for Complex Calculations
  • Debugging DAX Expressions Using DAX Studio
  • Power BI Performance Optimization
  • Choosing Between DirectQuery, Import, and Hybrid Models
  • Using Performance Analyzer to Identify Bottlenecks
  • Understanding Query Folding and How It Affects Performance
  • Leveraging the Best Practice Analyzer for Optimized Data Models
  • Effective Strategies for Data Grouping and Summarization