Course Overview

Acquire the facilitation skills necessary to effectively manage requirements meetings and workshops.

Business analysts have the responsibility to gather, analyze, and validate business and technical requirements for their projects, thus they need facilitation skills to manage requirements meetings and workshops.

In this highly interactive two-day course, you’ll gain the skills to be an effective facilitator – one who can help stakeholders define their needs and form quantifiable requirements. You’ll learn tested techniques for meeting planning and preparation, brainstorming, analysis, and decision-making. You will have the opportunity to practice these techniques in a safe environment with a trained facilitator who will give you relevant, timely feedback. Advanced topics will also be covered, including virtual facilitation, conflict management, and root cause analysis. You will leave class with the confidence to facilitate a meeting from the planning stages, motivating group participation, building consensus, maintaining session focus, and evaluating results for lessons learned.

Students pursuing a university-recognized and/or accredited certificate in Canada or continuing education units in the US must attend at least 90% of class time, participate in class exercises and section-knowledge checks, and score at least 70% on an end-of-class, multiple-choice assessment.

Course Objectives

  • The role of facilitation in business analysis
  • Plan a facilitated meeting
  • Create an agenda and risk analysis
  • Use the appropriate facilitation techniques in a meeting
  • Plan for and facilitate in a virtual meeting environment
  • Use advanced brainstorming, analysis, and decision-making techniques
  • Manage conflict in a facilitated meeting

Course Content

  • Facilitation Basics:
  • What Facilitation Is
  • The Role of the Facilitator
  • To Facilitate or Not to Facilitate?
  • Benefits of Facilitation
  • Facilitation in Business Analysis
  • Planning a Facilitated Meeting:
  • Why Planning is Critical
  • Defining the Purpose
  • The Facilitated Meeting Planning Worksheet
  • Key Characteristics of Participants
  • Meeting Risks and Responses
  • Facilitation Techniques:
  • Building an Agenda
  • Techniques for Facilitated Meetings
  • Brainstorming
  • Gap Analysis
  • T-Charts (or Force Field Analysis)
  • Model Types
  • Impact/Effort Grid
  • Multi-Voting
  • Conducting a Meeting:
  • Facilitation Actions
  • Facilitation Behaviors
  • Virtual Meetings:
  • Challenge of Teleconferences and Web-Conferences
  • Meeting with Dispersed Participants
  • Best Practices for Virtual Meetings
  • More Techniques for Facilitation:
  • Brainwriting (Anonymous Brainstorming)
  • Root Cause Analysis
  • Criteria-Based Grid
  • How Various Models Can be Used with Groups
  • Managing Conflict:
  • Understanding Conflict
  • Good vs. Bad Conflict
  • Resolving Conflict between Participants
  • Resolving Conflict between Participant and Facilitator
  • Exercises:
  • Complete a Facilitation Meeting Plan
  • Create Meeting Agenda
  • Practice Facilitating Multiple Meetings
  • Practice Root Cause Analysis
  • Complete a Criteria-Based Grid

Course Overview

A Dynamics 365 Business Central developer develops apps that extend Business Central. This can include creating new modules and modifying existing modules.

The developer can add new business logic or change existing business logic by using events. A developer also makes it possible to integrate Business Central with other applications, including Microsoft Power Platform products.

Business Central developers are responsible for troubleshooting and debugging issues in the system. This may involve identifying the root cause of a problem, fixing bugs, and testing the solution to ensure it works as expected. Business Central developers may be required to optimize the performance of the system by identifying bottlenecks and improving code quality. Business Central developers are responsible for upgrading the system, migrating data, and maintaining the system to ensure it remains up to date and secure.

Course Objectives

Students will learn to,

  • Start your free Dynamics 365 Business Central trial
  • Introduction to the capabilities of Microsoft Dynamics 365 Business Central
  • Customize Microsoft Dynamics 365 Business Central
  • Prepare for an easy application upgrade experience in Business Central
  • Administer Dynamics 365 Business Central online
  • Manage users and implement security in Business Central
  • Introduction to the development environment for Dynamics 365 Business Central
  • Debug and deploy your extension in Dynamics 365 Business Central
  • Work with pages in Dynamics 365 Business Central
  • Design the data model of a report in Dynamics 365 Business Central
  • Work with codeunits in Dynamics 365 Business Central
  • Work with XMLports in Dynamics 365 Business Central
  • Work with entitlements and permission sets in Dynamics 365 Business Central
  • Work with queries in Dynamics 365 Business Central
  • Build control add-in objects in Dynamics 365 Business Central
  • Customize the UI experience in Dynamics 365 Business Central
  • Identify functional table types and characteristics in Dynamics 365 Business Central
  • Introduction to the basics of AL programming in Dynamics 365 Business Central
  • Learn about application performance and monitoring in Business Central
  • Work with source control using Git in Visual Studio Code for Business Central
  • Use Application Lifecycle Management for Business Central
  • Introduction to test automation in Business Central
  • Use Power Automate with Business Central
  • Access REST services from within Dynamics 365 Business Central
  • Use Azure Functions with Dynamics 365 Business Central
  • Work with web services in Dynamics 365 Business Central
  • Work with the API in Dynamics 365 Business Central

Course Content

Module 1 : Start your free Dynamics 365 Business Central trial

  • Create a Business Central account.
  • Sign in to Business Central.
  • Use a demo database.
  • Start a trial with your own data.
  • Extend your trial and subscribe or unsubscribe your organization from Business Central.

Module 2 : Introduction to the capabilities of Microsoft Dynamics 365 Business Central

  • Why Business Central is a cloud end-to-end business solution.
  • The core Business Central functionalities by browsing application areas.

Module 3 : Customize Microsoft Dynamics 365 Business Central

  • Understand the high-level technical architecture of Business Central.
  • Know the available options to tailor Business Central to specific needs.

Module 4 : Prepare for an easy application upgrade experience in Business Central

  • Understand upgrade responsibilities and best practices
  • Create proper installation and upgrade codeunits

Module 5 : Administer Dynamics 365 Business Central online

  • Know how to sign up for the Cloud Solution Provider program.
  • Use the administration center to manage environments.
  • Set up tenant notifications and inspect environment telemetry.
  • Manage support requests for customers.
  • Export a database.
  • Enable features ahead of time

Module 6 : Manage users and implement security in Business Central

  • Manage users and user groups
  • Implement and configure security
  • Setup profiles, and role centers
  • Audit changes to data

Module 7 : Introduction to the development environment for Dynamics 365 Business Central

  • Use the Microsoft Visual Studio Code development environment.
  • Create a basic new AL Language extension.
  • Design the different configuration files in an AL extension.
  • Manage multiple AL extensions in one workspace.

Module 8 : Debug and deploy your extension in Dynamics 365 Business Central

  • Learn how to work with the Visual Studio Code debugger.
  • Use Debug and Attach configuration files.
  • Work with the Rapid Application Development (RAD) feature.
  • Deploy your extensions to a production tenant.

Module 9 : Work with pages in Dynamics 365 Business Central

  • Identify the different page types.
  • Discover the different page properties.
  • Learn how to build the layout of new pages.
  • Link pages with page parts.
  • Use snippets to create pages in Visual Studio Code.
  • Enable end users to search for a page.
  • Define actions on a page and set its properties.

Module 10 : Design the data model of a report in Dynamics 365 Business Central

  • Learn about the different report components.
  • Create the data items for a report.
  • Add columns to the dataset of a report.
  • Order, link, and indent data items.

Module 11 : Work with codeunits in Dynamics 365 Business Central

  • Learn about codeunits.
  • Create new codeunits.
  • Access functions within a codeunit.

Module 12 : Work with XMLports in Dynamics 365 Business Central

  • Create new XMLports.
  • Configure the important XMLport properties.
  • Define nodes in an XMLport.
  • Work with the different formats.
  • Use an XMLport in AL code.

Module 13 : Work with entitlements and permission sets in Dynamics 365 Business Central

  • Learn about entitlements and how to use them in Business Central.
  • Learn about permission sets and how they are used.
  • Create or extend entitlement and permission set objects by using AL.

Module 14 : Work with queries in Dynamics 365 Business Central

  • Create a new Query object.
  • Join, filter, and aggregate data in a Query object.
  • Access queries from AL.
  • Publish queries as a web service.

Module 15 : Build control add-in objects in Dynamics 365 Business Central

  • Learn about control add-ins.
  • Build a control add-in.
  • Send data from Business Central to JavaScript.
  • Send data from JavaScript to Business Central.
  • Connect a control add-in with an Azure function.

Module 16 : Customize the UI experience in Dynamics 365 Business Central

  • Add objects to the search dialog.
  • Create page customizations.
  • Define profiles that are linked to a Role Center and page customizations.
  • Create custom views.
  • Extend the application areas in Business Central.

Module 17 : Identify functional table types and characteristics in Dynamics 365 Business Central

  • Learn the difference between all available table types.
  • Discover the correct primary key for each table type.
  • Use the correct naming for tables.
  • Create the associated pages.

Module 18 : Introduction to the basics of AL programming in Dynamics 365 Business Central

  • Work with variables and define them in AL code.
  • Use the different data types.
  • Use options and enums.
  • Work with collections.
  • Use the different types of expressions.

Module 19 : Learn about application performance and monitoring in Business Central

  • Prepare your application for optimal performance
  • Get essential application insights

Module 20 : Work with source control using Git in Visual Studio Code for Business Central

  • Configure Git
  • Know the structure of Git repositories
  • Create a new local Git repository
  • Add and remove files from Git
  • Link and clone a remote Git Repository
  • Work with the .gitignore file

Module 21 : Use Application Lifecycle Management for Business Central

  • Create an Azure DevOps organization
  • Create an Azure DevOps project
  • Know about the different services in Azure DevOps
  • Connect via a Personal Access Token
  • Know the difference between GitHub and Azure DevOps

Module 22 : Introduction to test automation in Business Central

  • Learn how to write test code in AL with Test Codeunits
  • Install and run the Test Toolkit in Docker containers
  • Run standard Business Central tests

Module 23 : Use Power Automate with Business Central

  • Identify what Power Automate is and how it can be used with Business Central.
  • Identify existing Business Central actions and triggers available in Power Automate.
  • See how to create an independent flow in Business Central that automates business processes.
  • Create a flow that runs on a schedule or to create a button flow to send a reminder.

Module 24 : Access REST services from within Dynamics 365 Business Central

  • Use HTTP data types.
  • Connect to external REST services and read data.
  • Connect to external REST services and post data.
  • Read JSON data in Business Central.
  • Get JSON from an external REST service.

Module 25 : Use Azure Functions with Dynamics 365 Business Central

  • Learn about Azure Functions.
  • Create a basic Azure function.
  • Use an existing .NET DLL in an Azure function.
  • Use an Azure function in Business Central.

Module 26 : Work with web services in Dynamics 365 Business Central

  • Learn about the differences between SOAP and OData.
  • Enable access to the different web services.
  • Create your own SOAP and OData web services.
  • Use OData and SOAP to read and update records.
  • Handle UI interaction.

Module 27 : Work with the API in Dynamics 365 Business Central

  • Define the difference between regular OData web services and the API.
  • Work around API limits.
  • Create new APIs.
  • Read, update, and create through the API.
  • Implement OData bound actions.

Course Overview

The amount of data we collect today is endless. To make this data useful for management and other decision makers, we have to process or visualise it first, so that it’s readable. Our human brain is visually oriented, which means that data visualisation is a powerful tool to analyze, interpret and share data more quickly. It enables your organisation to quickly identify and respond to changes in customer behaviour, business processes or markets.

In this training course, you will learn how to visualise data effectively, so that important results don’t escape your notice. You will work with visualisations yourself and learn to apply design principles directly.

Course Objectives

  • This course is also practical, so you will work with data hands-on. You will learn to choose the most appropriate visualisation form, so your organization can easily read the data and draw the right conclusions.
  • This training course is given software-independently and is suitable for any tool you work with (e.g. Cognos, PowerBI, SAS, Tableau or Excel)
  • This course teaches the insight into what makes a user-friendly dashboard and the skills to make it readable and comprehensible, so that the right decisions can be made by leaders and management.

Course Content

The training is divided into four parts. Each consists of both theory and practical assignments.

Part 1: Visual and Quantitative Thinking

  • What is data visualisation and where does it come from?
  • How does our brain process visual information?
  • What type of data do we have and how can we best visualize it?

Part 2: Visualising data effectively

  • How do you make data easy and understandable to read?
  • What are the basic principles and guidelines?
  • What are the main pitfalls in data visualisation?

Part 3: Building blocks of data visualizations

  • Which basic blocks do data visualisations consist of?
  • When is it better to use a table and when a graph?
  • What type of table/graph works best in a given situation?
  • How do you create a composite visualisation, the management dashboard?

Part 4:

  • What is the data visualisation process like?
  • Arguing with data, data storytelling.
  • Making agreements within your organisation, the data visualization style guide.

Course Overview

In this 3-day Data Modeling training you’ll get hands-on practice modeling requirements through entity relationship diagrams, supertypes and subtypes, and attributive and associative entities. You will learn to use logical data modeling to work directly with business users to accurately define requirements.

Since a business analyst needs to accurately elicit, define, and document user requirements, understanding the users’ needs is key to an analyst’s success. By using logical data modeling, a business analyst can convey requirements in a way that can easily be validated, and doing so allows stakeholders to understand the requirements, business rules, and data management methods for any given project.

Course Objectives

How logical data models relate to requirements

Identifying entities and attributes

Determining relationships and business rules

Data integrity through normalization

Course Content

1. Introduction to Logical Data Modeling

  • Importance of logical data modeling in requirements
  • When to use logical data models
  • Relationship between logical and physical data model
  • Elements of a logical data model
  • Read a high-level data model
  • Data model prerequisites
  • Data model sources of information
  • Developing a logical data model

2. Project Context and Drivers

  • Importance of well-defined solution scope
  • Functional decomposition diagram
  • Context-level data flow diagram
  • Sources of requirements
    • Functional decomposition diagrams
    • Data flow diagrams
    • Use case models
    • Workflow models
    • Business rules
    • State diagrams
    • Class diagrams
    • Other documentation
  • Types of modeling projects
    • Transactional business systems
    • Business intelligence and data warehousing systems
    • Integration and consolidation of existing systems
    • Maintenance of existing systems
    • Enterprise analysis
    • Commercial off-the-shelf application

3. Conceptual Data Modeling

  • Discovering entities
  • Defining entities
  • Documenting an entity
  • Identifying attributes
  • Distinguishing between entities and attributes

4. Conceptual Data Modeling-Identifying Relationships and Business Rules

  • Model fundamental relationships
  • Cardinality of relationships
    • One-to-one
    • One-to-many
    • Many-to-many
  • Is the relationship mandatory or optional?
  • Naming the relationships

5. Identifying Attributes

  • Discover attributes for the subject area
  • Assign attributes to the appropriate entity
  • Name attributes using established naming conventions
  • Documenting attributes

6. Advanced Relationships

  • Modeling many-to-many relationships
  • Model multiple relationships between the same two entities
  • Model self-referencing relationships
  • Model ternary relationships
  • Identify redundant relationships

7. Completing the Logical Data Model

  • Use supertypes and subtypes to manage complexity
  • Use supertypes and subtypes to represent rules and constraints

8. Data Integrity Through Normalization

  • Normalize a logical data model
    • First normal form
    • Second normal form
    • Third normal form
  • Reasons for denormalization
  • Transactional vs. business intelligence applications

9. Verification and Validation

  • Verify the technical accuracy of a logical data model
  • Use CASE tools to assist in verification
  • Verify the logical data model using other models
    • Data flow diagram
    • CRUD matrix

Course Overview

Get to know the power and pitfalls of data.

Clear insight into a data-driven world.

We are overloaded with data every day. One of the main challenges organisations face nowadays is a lack of data literacy. Do your employees have enough knowledge to read data properly, interpret it and turn it into valuable insights? This is crucial to be able to make the right decisions. Only then will your organisation be able to respond to the needs of your customers and opportunities in the market.

Are you curious enough?

Data literacy is the most important competence for people who work with data. It enables you to constantly look for new or existing data, question it and ask critical questions. It is therefore the skill that allows us to draw the right conclusions in today’s data-driven reality. This will not only lead to faster decisions, but also to better results for your organisation.

From manipulation to information

In this training you will learn, on the basis of practical examples and exercises, not only about the power of data, but also about its pitfalls. You will get an answer to the question of how to read and interpret information correctly and which steps you should take to thoroughly analyse data. After completing this training Data Literacy, you will have several tools at your disposal to distinguish information from manipulation, based on your curiosity.

Course Objectives

In this training you will learn:

  • How to get more value out of your data;
  • interpret data correctly;
  • recognise the pitfalls of data;
  • Improve and maintain the quality of your data;
  • the most important steps to take in order to analyse data in depth;
  • convince others with data-based arguments.

Course Content

Block 1: Reading data

  • Reading data presented to us in the media, company reports, political claims and advertisements
  • How to distinguish information from manipulation
  • Preventing misinterpretation

Practical assignment: applying the data checklist to a number of practical situations to promote our Data Literacy.

Block 2: Working with data

  • Improving the quality of your data
  • How do you ensure that you retain this quality?
  • Discussing the most important data processing steps.
  • Identifying the consequences of data processing

Practical assignment: estimating the consequences of the different processing steps on the results on the basis of a number of cases.

Block 3: Analysing data

  • What are the most important steps to analyse data thoroughly?
  • How do you prevent deception?
  • What can we learn from the “scientific method” when it comes to data analysis?

Practical assignment: performing the most important analytical steps on a practical example.

Block 4: Arguing with and communicating data

  • Being right is one thing, but being right is quite another.
  • Transition and difference from analysis to explanation of data
  • How do you convince others with data-based arguments?
  • What can we learn from storytelling to better communicate our data?
  • The 7 essential principles of good data storytelling

Practical assignment: Applying the 7 principles to a real-life example

Course Overview

Data is an important tool in the control of our processes and organisations. To do this effectively and efficiently, we use all kinds of approaches and software tools. This training course familiarises you with the most important concepts so that you can place things in the right context.

Course Objectives

  • Analysis on the basis of supply structured data (e.g. Data Lake)
  • Analysis on the basis of demand-structured data (e.g. Star Schemas)
  • Decoupling point between supply and demand data structures for flexibility (e.g. Data Vault)

Course Content

  • Is data a liability or an asset?
  • Identifying the most important data analysis architectures and the differences between them;
  • Data modelling, what is it good for?
  • Differences and similarities between star schema and Data Vault models. Which one works best in which situation?
  • What is a Data Vault and what can you do with it?
  • Is a Data Vault the same as a data warehouse?
  • In what ways can we collect data from different sources and make this data available in an integrated way for analysis purposes. (data logistics)
  • How do we translate source data to a form that is usable for analysis?

Course Overview

Data Analysis is a process of applying statistical and mathematical techniques systematically to understand, explore, and analyze data to find patterns, and draw inferences that help businesses make data-driven decisions. This typically involves multiple activities such as data collection, exploration, cleaning, pre-processing, and organizing data. Many times, data analysis is an iterative ongoing process where the data is continuously collected and analyzed simultaneously. There are two primary methods for data analysis.

Qualitative techniques and quantitative techniques. Quantitative data analysis techniques involve working with quantitative/numerical data including statistics, percentages, and calculations. These techniques also include working with algorithms, mathematical analysis tools, and software to manipulate data and uncover hidden business value. For example, quantitative data analysis used to assess market data helps a company decide a price for its new product.
Qualitative data analysis involves, working with non-numerical data i.e categorical variables. Qualitative data analysis is also used in many business processes, such as identifying themes and patterns, answering research questions, etc to improve a product.

This course provides an overview of data concepts and what data analysis is and then deep dives into the fundamentals of Data Analysis such as statistics and probability. This course also focuses on widely used data analysis methods such as regression along with detailed steps to perform the same.

*Must have Microsoft Excel in order to complete class activities.

Course Objectives

  • Data Analysis process, benefits and use cases
  • Basic of Probability and Statistics
  • Measure of data spread and distributions
  • Inferential Statistics and Hypothesis Testing
  • Applications of Statistics and Probability theory
  • Forecast trends using linear regression analysis

Course Content

  • 1. All about Data 
      
    Data in the real world
  • A brief on various formats and sources of data
  • 7 V’s of Data
  • Structured vs Unstructured vs Semi-Structured data
  • Data processing types

Introduction to Data Analysis 

  • Need for Data Analysis
  • Applications and Use Cases of Data Analysis
  • Data Analysis Methodology
  • Types of variables
  • Numerical vs Categorial Variables

Descriptive Statistics 

  • Measures of Central Tendency
  • Measures of Dispersion
  • Data Skewness and Kurtosis
  • Understanding Outliers
  • Understanding missing values
  • Role of Descriptive Statistics in Data Analysis

Inferential Statistics 

  • Population and Sample
  • Statistics vs Parameters

Introduction to Probability 

  • Basics of Probability
  • Axioms of Probability
  • Conditional Probability and Bayes theorem
  • 2. Applications of Conditional Probability 
      
    Understanding Probability Distributions 
  • Discrete Probability Distributions
  • Continuous Probability Distributions
  • Performing Distributions in Excel
  • Why understanding Data Distributions is important for Data Analysis

Data Analysis Process 

  • Understanding Covariance and Correlation
  • Understanding univariate vs Bivariate vs Multi variate data analysis
  • Understanding Regression
  • Simple Linear Regression
  • Multiple Linear Regression
  • Exercise

Introduction to Predictive Analytics 

  • Exercise

Course Overview

This 1-day DAMA DMBoK Data Management Specialist course addresses all disciplines as identified Data Modeling specialist exam by the international standard, DAMA Body of Knowledge (DMBOK2) and is aimed to individuals interested in developing concrete professionalism in the field of Data Management with a specialisation in Data Modelling And Design

This course provides a solid foundation of the different information disciplines across the complete Data Modeling, Data Management spectrum and introduces students to the different levels of Industry professional certification the DAMA Certified Data Modelling And Design Professional (CDMP).

The data modeling specialist course explores different data modeling methodologies. It helps understand how to select, implement, and interpret suitable statistical analyses and designs for practical data scenarios and problems. In addition, it explores various features of data modeling including Data Models, Data Implementation, Design Quality Management, Data Designs, Modeling Styles, and System Development Lifecycle among others.

Course Objectives

  • To help understand data modeling methodologies.
  • To help comprehend how statistical designs and analyses work.
  • To help teach the application of data models.
  • To help comprehend different data model styles.
  • To explain how different data designs and models may be utilized for business problems and scenarios.
  • To explain how System Development Lifecycle works.

Course Content

  • Database Design and Data Modeling
  • CDMP Breakdown
  • Explanation of Data Design and Modeling
  • Comprehension of SDLC and Lifecycle
  • Understanding the Development of Data
  • Explanation of a Data Model
  • Representations of Data Models
  • Significance of Data Modeling
  • Reasons for the Production of a Data Model
  • Data Model Levels
  • Symbols of Entity Relationships
  • Notations and Cardinality
  • Enterprise Data Model
  • Physical Data Model
  • Logical Data Models
  • Conceptual Data Models
  • Subject Area Models
  • Independent and Dependent Entities
  • Significance of Comprehending Entities
  • Types of Relationships
  • Recursive Relationships
  • Many to Many Relationships
  • Entity Subtypes
  • Role Name Usage
  • Physical and Conceptual Terms
  • Primary Keys
  • Entity Keys
  • Alternate Keys
  • Benefits and Drawbacks of Natural versus Surrogate Keys
  • Data Model and Process Relationships
  • Components of a Logical Data Model
  • Normalization Rules
  • Normalization Approaches
  • Normalization Definition
  • Principles of Database Design
  • Best Practices of a Physical Database Design
  • Comprehension of Partitioning
  • Transformation of Logical to Physical Data Model
  • ACID Test
  • Classification of Modeling Tools
  • The Alternative to ACID

Course Overview

This course is ideal for those who have detailed cross-functional configuration knowledge in copying control, text control, and output control to reflect business requirements in SAP S/4HANA Sales

Course Objectives

This course will prepare you to:

  • Understand and consider complex relationships in mapping organizational structures
  • Configure and adapt special functions such as copy control and text control
  • Configure output control (NAST-based and BRFplus-based Output Management)
  • Adjust Material Master Record Field Selection
  • Understand system modification options

Course Content

  • Organizational Structures
    • Creating Organizational Elements
    • Applying Shared Master Data and Cross-Division Sales
  • Copy Control
    • Understanding the Concept of Copy Control
    • Modifying Copy Control for Sales Documents
    • Analyzing Copy Control for Delivery and Billing Documents
  • Text Control
    • Identifying Text Sources
    • Configuring Text Control
  • Output
    • New Output Management
    • Output Determination with Condition Technique
    • Understanding Basic Principles of Processing Printed Output
  • Material Master Record Field Selection
  • Enhancements and Modifications
    • Using Enhancement Technology
    • Performing System Modifications Using Classic Enhancement Technology
    • Performing System Modifications Using the Enhancement Framework
    • Adding New Fields

Course Overview

Create your own data model and canvas app to support a scenario for a fictional company. You’re provided high-level specifications on the custom tables, columns and canvas app needed to complete this project.

Course Content

Get started with Power Apps canvas apps

This module introduces the learner to Power Apps. It starts with an introduction video briefly describing the “why” (case for Power Apps) and the “what” for what users can do with Power Apps. The units then take users through the “how” instilling in them the confidence that they can use Power Apps to interact with their data.

  • Introduction to Power Apps
  • Start Power Apps
  • Exercise – Create your first app in Power Apps
  • Power Apps data sources
  • Exercise – Create an app from Excel using Copilot
  • Use Power Apps with Power Automate and Power BI
  • Designing a Power Apps app
  • Check your knowledge
  • Summary

Customize a canvas app in Power Apps

In this module, we’ll show learners how to customize their app, a necessary skill for taking advantage of the capabilities of Power Apps. This unit builds upon the app produced in the first unit.

  • Improve your app by making basic customizations
  • Explore controls and screens in canvas apps
  • Exercise – Introduction to formulas in canvas apps
  • Exercise – Create basic screen navigation for a canvas app
  • Check your knowledge
  • Summary

How to build the User Interface in a canvas app in Power Apps

In this module, learners will learn how to build UI for their app including theming, icons, images, personalization, form factors and controls. In their learning path, thus far, learners have used basic controls with little to no customization. This unit shows how to make an app more personal and help it fit branding or personal requirements.

  • Use themes to quickly change the appearance of your app5 min
  • Brand a control
  • Icons
  • Images
  • Personalization
  • Build for phones or tablets
  • Exercise – Create and adjust UI for a new canvas app
  • Check your knowledge
  • Summary

Work with external data in a Power Apps canvas app

Do you need to connect an app to access data? Then this module is for you. It focuses on connecting your app to a data source.

  • Introduction
  • Data-source overview
  • Add a data source
  • Add Office 365 users to your application
  • Display and interact with your data in a gallery
  • Move data between collections and data sources by using Collect
  • Exercise – Work with external data in a canvas app
  • Check your knowledge
  • Summary

Write data in a Power Apps canvas app

Forms can be used to view, edit, and create records. This module demonstrates how to use forms to write data to your data source. Topics will include form setup, the different form modes, and how to configure a submit button.

  • Introduction to forms
  • Form modes
  • Adding and customizing an Edit form
  • Submit your form
  • Special properties
  • Exercise- Working with forms
  • Check your knowledge
  • Summary

Publish, share, and maintain a canvas app

You’ve built your first app. Now, it’s time to publish, share it with others, and maintain subsequent versions of the app.

  • Introduction
  • Exercise – Publish your app
  • Exercise – Share your app
  • Exercise – Maintain your app
  • Application lifecycle management
  • Check your knowledge
  • Summary

Guided Project – Create and manage canvas apps with Power Apps

Create your own data model and canvas app to support a scenario for a fictional company. You’re provided high-level specifications on the custom tables, columns and canvas app needed to complete this project.

  • Introduction
  • Prepare
  • Exercise – Create a canvas app that connects to a data source
  • Knowledge check
  • Summary