Book Image

Microsoft Power Platform Functional Consultant: PL-200 Exam Guide

By : Julian Sharp
Book Image

Microsoft Power Platform Functional Consultant: PL-200 Exam Guide

By: Julian Sharp

Overview of this book

The Power Platform Functional Consultant Associate (PL-200) exam tests and validates the practical skills of Power Platform users who are proficient in developing solutions by combining the tools in Power Platform and the Microsoft 365 ecosystem based on business needs. This certification guide offers complete, up-to-date coverage of the PL-200 exam so you can prepare effectively for the exam. Written in a clear, succinct way with self-assessment questions, exam tips, and mock exams with detailed explanations of solutions, this book covers common day-to-day activities involved in configuring Power Platform, such as managing entities, creating apps, implementing security, and managing system change. You'll also explore the role of a functional consultant in creating a data model in the Microsoft Dataverse (formerly Common Data Service). Moving ahead, you'll learn how to design the user experience and even build model-driven and canvas apps. As you progress, the book will show you how to manage automation and create chatbots. Finally, you'll understand how to display your data with Power BI and integrate Power Platform with Microsoft 365 and Microsoft Teams. By the end of this book, you'll be well-versed with the essential concepts and techniques required to prepare for the PL-200 certification exam.
Table of Contents (34 chapters)
Section 1: Introduction
Section 2: Microsoft Dataverse
Section 3: Power Apps
Section 4: Automation
Section 5: Power Virtual Agents
Section 6: Integrations

Identifying AI Builder model types

AI Builder addresses some of the common requirements for AI in business applications. You don't need to choose the correct algorithm when using AI Builder; AI Builder uses its own ML functionality to find the best algorithm for your data. You simply choose the type of model and AI Builder then creates an AI model for you.

AI Builder has five model types for prediction, vision, and language:

  • Category classification: Performs Natural Language Processing (NLP) on text data. Category classification can be used to identify sentiment or meaning within the text. For instance, you can use category classification to determine the importance of an email message, or whether an email message is a request for action, a complaint, or just an acknowledgment.
  • Entity extraction: Recognizes specific data in text data. Entity extraction transforms unstructured text into structured data that can be used in apps and flows. You can use entity extraction to identify...