Integrating Power BI with Power Apps and Data Storytelling

Module 1: Data Mastery and Integration

Learning Objective:

Understand the role of data mastery in finance leadership and leverage Power BI for
effective data integration and storytelling.

Learning Outcome:

Participants will articulate the importance of data mastery, utilize Power BI for data
analysis, and create compelling data stories by connecting various data sources.

Content:
Understanding the importance of data mastery in leadership roles within the finance sector.

Bringing in data:

• How to leverage Power BI and its application.
• Understanding data structures, sourcing data from various platforms including Dataverse, and
  making sense of it.
• Overview of data storytelling and projecting data robustly by connecting from various sources.

Module 2: Practical Applications with Power Apps

Learning Objective:

Introduce Power Apps and its role in data management, develop skills for creating
and deploying user-friendly data interfaces.

Learning Outcome:

Participants will build their first Power App, connect it to data sources, and
understand scenarios for applying Power Apps, Python, or Power BI in finance.

Content:

• Introduction to Power Apps and its role in data management.
• Practical exercise: Creating your first Power App and connecting it to Power BI and other data
  sources.
• Advanced Power App functions for creating user-friendly interfaces.
• Live finance case studies demonstrating when to use Power Apps, Python, or Power BI.

Advanced Data Management and Workflow Automation

Module 3: Power Automate

Learning Objective:

Understand and implement workflow automation using Power Automate for
enhanced financial processes.

Learning Outcome:

Participants will be proficient in using Power Automate for creating, managing, and
optimizing workflows in a financial context.

Content:

• Incorporating Power Automate desktop and online versions for workflow automation in
  finance.
• Building your first workflow with Power Automate.
• Advanced workflow automation techniques.

Module 4: Hands-on Automation and Customization

Learning Objective:

Gain practical experience in automating and customizing financial processes using
Power Automate and Power Apps

Learning Outcome:

Participants will customize data models, automate financial workflows, and
effectively monitor and manage these workflows

Content:

• Practical exercises in creating automated financial processes using Power Automate.
• Customizing data models within Power Apps for financial data management.
• Monitoring and managing workflows effectively.

Python for Finance and Data Analysis 

Module 5: Introduction to Python and Pandas

Learning Objective:

Introduce Python and Pandas for financial data manipulation and analysis

Learning Outcome:

Participants will understand the basics of Python, manipulate financial data using
Pandas, and apply these skills to clean, transform, and analyze data.

Content:

• Introduction to Python programming for financial applications.
• Basics of Python syntax, data types, and overview of libraries and tools for financial analysis.
• Deep dive into data manipulation and analysis using the Pandas library.

Module 6: Integrating Python with Power Platform

Learning Objective:

 Learn how to integrate Python with Power BI and Power Automate for enhanced
data analysis and automation.

Learning Outcome:

Participants will incorporate Python scripts into the Power Platform, enhancing their
data analytical capabilities and automating complex financial tasks.

Content:

• Incorporating Python visuals, bringing data to Power BI, and enhancing it with Power
  Automate.
• Automating financial calculations, reporting, and data processing using Python.
• Integrating Python scripts with Power Apps, Power BI and Power Automate for seamless data
  flow.

Application, DAX, Excel, and Recap

Module 7: Financial Automation with Python

Learning Objective:

Deepen understanding of Python for automating financial tasks and analyses

Learning Outcome:

Participants will apply Python to automate various financial calculations and
reporting, and understand how to transition from Excel to Python for more advanced financial analysis.

Content:

• Continuing Python for financial automation and real-world applications.
• Relating back to Excel implementation, understanding how to transition from Excel to more
  advanced tools.

Module 8: Recap and Assessment

Learning Objective:

Recap the key concepts covered and assess participants’ understanding and ability to
apply the learned skills.

Learning Outcome:

Participants will have a comprehensive understanding of the course content and be
able to operationalize automated workflows into their business operations. They will complete an
individual certification assessment to validate their skills

Content:

• Recap of the key concepts covered over the four days.
• Operationalization of Automated Workflows into existing business operation.
• Completion of Certification Assessment (Individual) focusing on practical skills and understanding.

Exam Format :

The CDSP Certification Exam duration is 2 hours, consisting of 40 Multiple Choice Questions, with a Passing
Score of 70%. You will receive a professional CDSP Certification upon passing the exam.