GRC-104FT: Intensive Data Modeling For Microsoft Power BI Creators [Fastrack]

Name: GRC-104FT: Intensive Data Modeling For Microsoft Power BI Creators [Fastrack]
Brand: GemRain

RM 3,000.00

Data Modeling is one of the features used to connect multiple data sources in BI tool using a relationship. A relationship defines how data sources are connected with each other and you can create interesting data visualizations on multiple data sources.

With the data modeling for Microsoft Power BI feature, you can build custom calculations on the existing tables and these columns can be directly presented into Power BI visualizations. This allows businesses to define new metrics and to perform custom calculations for those metrics.

Training Duration: 2 Days

Certificate Of Completion Available
Group Private Class
VILT Class Available
SBL-Khas Claimable

Download Course Outline

This workshop is a complete course about building the most optimal data models for your Power BI reports. It introduces the audience to the basic techniques of shaping data models in Power BI. It offers many real-world examples that will help you look at your reports in a different way – pretty much like experienced data modelers do.
After completing this course, students will be able to:

Learn the vast techniques of shaping and building a correct data model to be used in Power BI.

Understand the common challenges and mistakes that people have in creating a data model.

Learn the most optimum way of building a sustainable data model for Power BI reports.
Module 1: Introduction to Data Modeling

What is Data Modeling?

Analytical limits

Increasing the analytical power

Introducing the facets of data modeling

Leveraging the data model

Normalization and denormalization

Facts and dimensions

Introducing star schemas

Chains of relationships

How many dimensions?

Why data modeling is useful?

Lab 01 – Basic data modeling

Module 2: Header / Detail Tables

Introduction to header / detail schemas

Bidirectional filtering is not the way!

Denormalizing the discount

Back to star schema

Lab 02 – Header / detail

Module 3: Working with Date and Time

Date attributes in the fact table

Building a date dimension

CALENDARAUTO function

The model with a date dimension

Automatic date grouping in Power BI

Quick calculations in Power BI Desktop

Disable automatic date columns

Handling multiple dates

Multiple date tables

Multiple date tables with multiple fact tables

Multiple relationships with date

Handling date and time

Computing with working days

Create a holidays table (one country)

Create a holidays table (multiple countries)

Weekends are not always the same!

Handling special periods of the year

Non-overlapping periods in the model

Non-overlapping special periods

Overlapping period measure

Lab 03 – Working with date and time

Module 4: Using Snapshot Tables

What is a snapshot table?

Sales versus inventory in the same model

Non-additive measures

LASTDATE function does not work here!

Optimizing performance

Snapshots and granularity

Transition matrix

Parameter tables

Lab 04 – Snapshots

Module 5: Analyzing Date and Time Intervals

What are intervals?

Solving with DAX… too complex!

Changing granularity

Split hours AND amount!

Analyzing active events

Open orders: the starting model

Open orders with DAX

Open orders in a snapshot table

Events with different durations

Daily salary in DAX

Precompute the values

Lab 05 – Date and time interval

Module 6: Many-to-Many Relationships

What are many-to-many relationships?

Possible solutions to this complex scenario

Bidirectional filtering

Using CROSSFILTER function

Using expanded table filtering

CROSSFILTER versus expanded tables

Understanding non-additivity

Cascading many-to-many

Lab 06 – Many-to-many relationships

Module 7: Working with Different Granularities

Dimensions define granularity

Analyzing budget data

Reduce granularity on all the tables

Using DAX to move the filters

Filtering through relationships

Using the correct column to slice

Leveraging relationships

Checking granularity in the report

Hiding or reallocating?

Lab 07 – Granularity

Frequently Asked Questions

What is an AI agent?

An AI agent is a system that can autonomously perform tasks, make decisions, and interact with tools or systems to achieve specific goals.

Who should attend the Agentic AI Builder course?

This course is suitable for programmers, DevOps engineers, IT professionals, and technical specialists working on AI or automation projects.

Do I need programming experience for this course?

Yes. Participants should have programming experience, preferably in Python, and foundational knowledge of AI concepts.

What is RAG in AI agents?

Retrieval-Augmented Generation (RAG) is a technique that enhances AI responses by retrieving relevant external data and combining it with model-generated outputs.

What tools are used to build AI agents?

Tools include Python, APIs, LLM services (such as OpenAI), Docker environments, and development tools like Visual Studio Code.

Is this course HRDC Claimable?

Yes. This course is HRDC claimable, subject to HRDC approval and company eligibility requirements.

Can this course be customized for our organization?

Yes. The course can be tailored to your organization’s AI architecture, workflows, and use cases.

Does this course prepare learners for certification?

Yes. This course prepares participants for the CertNexus Agentic AI Builder™ (AGB-110) certification.

GRC-104FT: Intensive Data Modeling For Microsoft Power BI Creators [Fastrack]

WHAT WILL YOU LEARN

OBJECTIVES

PREREQUISITES

COURSE MODULE

Frequently Asked Questions

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