Book Image

Democratizing Application Development with AppSheet

By : Koichi Tsuji, Suvrutt Gurjar, Takuya Miyai
Book Image

Democratizing Application Development with AppSheet

By: Koichi Tsuji, Suvrutt Gurjar, Takuya Miyai

Overview of this book

Many citizen developers regularly use spreadsheets in their business and day-to-day jobs. With AppSheet, you can take your spreadsheets to the next level by enhancing their ease of use. The platform allows you to run your business efficiently and manage it in the field outside of an office or indoor environment. This book enables you to create your own simple or medium to complex hybrid apps for business or personal use. As a beginner to AppSheet, this book will show you how the AppSheet Editor works and how it is used to configure, test, and deploy an app and share it with others as users or co-authors. You’ll learn about widely used features such as how to use data sources, create app views and actions, construct expressions with AppSheet functions, and make your app secure through security and UX options. Next, you’ll create email/attachment templates and develop reports/documents based on templates, store in the cloud, and send files through emails. You’ll also understand how to integrate third-party services and monitor various usage statistics of your app. As you progress, you’ll explore various features with the help of sample apps that you create using the book. By the end of this book, you’ll have learned how to make the most of AppSheet to build powerful and efficient applications.
Table of Contents (20 chapters)
Part 1 – Introduction and Getting Started
Part 2 – App Editor and Main Features
Part 3 – Advanced Features and External Services
Part 4 – App Templates and Tricks for App Building

Building your own predictive models

Predictive models are an analytical feature only provided for users with AppSheet Enterprise licenses. To enable this feature, you need to purchase the appropriate license. However, without purchasing a license, you can still test this feature—as long as the app is not deployed and remains a prototype for testing purposes.

Predictive models evaluate your data and return the most likely value based on your data when a new row is added to a table. Once a predictive model is built from your existing data, then it will create a model or algorithm.

Typically, it is useful when, for example, you have a data table containing prices with given specifications, such as a product catalog. When a new product is added to the table, the predictive model will estimate the value of the new product behind the scenes using the Google Cloud machine learning algorithm. For other possible use cases, we could collect the feedback from customers or employees...