This Advanced Power BI course is meticulously designed to equip professionals with the expertise needed to master data analytics and visualization at an advanced level. By delving into critical aspects such as data transformation, modeling, and visualization, this course ensures you gain comprehensive skills to handle complex data scenarios effectively. Participants will learn to connect and consolidate data from diverse sources, automate data processes, and build robust data models. The course also covers advanced topics like role-level security, fuzzy matching, and the creation of transformation tables, enabling you to manage and protect data with confidence.

Taking this course will provide you with practical, hands-on experience through real-world applications and case studies. You will learn to create insightful reports and compelling visualizations that drive informed decision-making. By the end of the course, you will be equipped not only with advanced technical skills but also with the ability to apply these techniques to solve business problems and optimize data-driven strategies. This course is ideal for professionals looking to elevate their Power BI capabilities and leverage data analytics to achieve business success.Course Outline:

Introduction to Advanced Power BI Course

Introduction to the trainer

Overview of the course

Common challenges in mastering Power BI

Importance of core concepts

Data Cycle: Getting Data

Starting with a vision and end goals

Identifying data sources

Connecting to disparate systems

Centralized data warehouses

Methods for importing data

Data Cycle: Data Transformation

Importance of data transformation

Common data issues

Automating data transformation

Data wrangling and munging

Data Cycle: Data Consolidation

Importance of data consolidation

Data flattening vs. data modeling

Benefits of data modeling

Handling large datasets

Data Cycle: Enrichment, Visualization & Sharing

Data enrichment techniques

Creating compelling visualizations

Effective data sharing methods

Data Transformation: Finding Problems & Understanding Column Profile

Identifying data problems

Understanding column profiles

Using data profiling tools

Data Transformation: Fuzzy Match

Concept of fuzzy matching

Implementing fuzzy matching in Power BI

Handling data quality issues

Data Transformation: Transformation Table with Fuzzy Match

Creating transformation tables

Using transformation tables with fuzzy matching

Best practices for accurate data mapping

Data Transformation: Fuzzy, Transformation Table Practice

Hands-on practice with transformation tables

Troubleshooting common problems

Performing sense checks

Data Transformation: Transforming City Data Set

Case study: transforming city data

Applying learned techniques

Reinforcing key concepts through practical application

Data Transformation: Completing Sales File

Cleaning and transforming sales data

Handling errors and missing values

Making executive decisions on data handling

Data Transformation: Product File

Importing and cleaning product data

Standardizing product information

Dealing with inconsistent data entries

Data Consolidation: Model Formatting

Understanding automatic relationship detection

Deactivating auto-detect for manual relationship management

Formatting and enriching data

Data Enrichment: Calendar Table (Simple)

Creating a simple calendar table

Using DAX for date-related calculations

Enhancing reports with date intelligence

Data Enrichment: Calendar Table (Fiscal Year)

Creating a fiscal year calendar table

Customizing date intelligence for fiscal reporting

Utilizing DAX for advanced date calculations

Q&A Session

Recap of previous sessions

Addressing participant questions and concerns

Practical tips and insights from real-world use cases

Data Model: Fact Table

Understanding fact tables

Characteristics and purpose of fact tables

Creating and managing fact tables in Power BI

Data Model: Dimension Table & Star Schema

Understanding dimension tables

Characteristics and purpose of dimension tables

Implementing star schema in data modeling

Data Model: Cardinality and Cross Filter Direction

Understanding cardinality in relationships

Managing cross-filter direction

Best practices for relationship management

Data Model: Merge and Role-Playing Dimensions

Merging tables for optimized data models

Creating role-playing dimensions

Advanced data modeling techniques

Data Model: Comparing 2 Fact Tables (Theory)

Theoretical concepts of comparing fact tables

Understanding common grains

Implications of comparing different grains

Data Model: Comparing 2 Fact Tables (Practice)

Practical application of comparing fact tables

Handling many-to-many relationships

Best practices for accurate comparisons

Comparing Sales and Inventory (Considerations & Reporting)

Comparing sales and inventory data

Managing data discrepancies

Effective reporting techniques

Recap and Data Enrichment Using Custom Columns CC

Recap of key concepts

Data enrichment techniques using custom columns (CC)

Practical examples and hands-on exercises

Comparing Order Date and Ship Date

Comparing different date fields

Handling date discrepancies

Creating meaningful insights from date comparisons

Comparing Target Sales vs Actual Sales Part 1

Introduction to target vs actual sales comparison

Setting up the data model

Creating relationships and calculations

Comparing Target Sales vs Actual Sales Part 2

Advanced techniques for comparing target vs actual sales

Handling complex data models

Best practices for accurate reporting

Role Level Security

Implementing role-level security in Power BI

Managing user access and permissions

Best practices for secure data models

Normalizing a Flat File

Introduction to normalizing flat files

Step-by-step process for creating dimension tables

Best practices for efficient data modeling

Closing and Q&A

Recap of the entire course

Final questions and answers