A better solution would be to contain all of our inventory items in a single table, and include a column which designates item categories like in Example 2. Initially we might be inclined to create a separate table for each category of item like in Example 1 - but this schema is inefficient as it creates a large number of tables we would need to manage and update individually. Imagine we’re building an app for a grocery store which keeps track of inventory. When grouping your columns into tables, think about what the simplest conceptual grouping would be. The critical data above needs to be captured in a column or table in your Google Sheet. What data is required to perform those functions? Step 1: Use clean table layoutsīefore we begin laying out our Google Sheet, let’s consider a few questions: Here are 4 steps that can help you reduce friction in the no-code app prototyping process, simplify the maintenance and management of your app, and create a more performative and efficient data structure. In this post, we’ll go over the fundamentals of preparing a data source in Google Sheets to effectively build applications using AppSheet. Though no coding is required, great no-code apps still rely on a well-designed data structure. Getting this process started can be as simple as organizing spreadsheets such that a no-code app platform like Google Cloud AppSheet can ingest them and generate useful prototype apps for users to further build on. Likewise, for many enterprises, the ability to empower non-technical workers to build such apps themselves, without significant IT resources, can be transformative, opening entirely new avenues for accelerating innovation. For many line-of-business workers, the power to replace spreadsheet maintenance with an app can lead to powerful efficiency gains. Users would simply input data into the app, which would automatically sync with spreadsheets in the cloud.
Typically, this involves a lot of engineering, but thanks to no-code app development, even those with no coding experience can create apps from the most commonplace data repository of them all: the spreadsheet or Google Sheets.įor example, if employees in the field are recording data by hand and inputting it into Google Sheets later, all of that work could be simplified with a no-code app. Making data accessible, useful and actionable in different contexts is one of the main reasons we build apps.
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