Building Tables with Copilot and Data Management

Creating tables with Copilot

The Copilot conversation flow

Here is how Tom at Summit Realty uses Copilot to create a property listings table:

Step 1 — Describe what you need

Tom opens Power Apps, clicks “Start with data”, and selects “Describe the new table”. He types:

“I need a table to track real estate property listings with the address, listing price, number of bedrooms, number of bathrooms, square footage, listing date, status, and the assigned agent.”

Step 2 — Review the suggestion

Copilot generates a table called “Property Listing” with columns:

Column	Data Type	Notes
Property Name	Text	Primary name column (auto-generated)
Address	Text (single line)	Street address
Listing Price	Currency	Dollar amount
Bedrooms	Whole number	Integer count
Bathrooms	Whole number	Integer count
Square Footage	Whole number	Area in sq ft
Listing Date	Date only	When the property was listed
Status	Choice	Active, Pending, Sold, Withdrawn
Assigned Agent	Text	Agent name

Copilot also generates five sample rows with realistic data.

Step 3 — Refine with follow-up conversation

Tom notices the Assigned Agent column is plain text — he wants it to link to a Users table instead. He types:

“Change Assigned Agent to a lookup to the User table.”

Copilot updates the column. Tom also adds:

“Add a Yes/No column called Featured Listing.”

The table updates instantly.

Step 4 — Create the table

Tom clicks “Create” and the Dataverse table is provisioned. He can now build a Power App on top of it.

💡 What Copilot can and cannot do

Copilot CAN: Create tables, suggest columns and data types, generate sample data, add/remove/rename columns through conversation, and create a canvas app from the table.

Copilot CANNOT: Create relationships between tables automatically (you can ask it to change a column to a lookup, but complex relationship chains require manual setup). It also cannot create business rules, security roles, or virtual tables through conversation.

Think of Copilot as an accelerator for the initial table design. Fine-tuning still happens in the table designer.

Modifying tables through conversation

You can also modify existing tables using Copilot. From the table editor in Power Apps:

• “Add a column called Priority with values High, Medium, and Low” — creates a Choice column
• “Remove the Fax Number column” — deletes the column (if it is a custom column)
• “Rename Listing Price to Asking Price” — updates the display name
• “Change Square Footage to a decimal number” — updates the data type

Each change is previewed before it is applied, so you always review before committing.

Importing data into Dataverse

Getting data INTO Dataverse is a common task. The exam expects you to know these methods:

Import Method	Best For	How It Works
Excel import	Small datasets, one-time loads	Upload an Excel file directly from the table view. Dataverse maps columns automatically.
CSV import	Flat data files	Upload a CSV file. Similar to Excel import but for comma-separated data.
Dataflows	Recurring imports from multiple sources	Visual ETL (Extract, Transform, Load) tool. Connect to 30+ sources, transform data, schedule refreshes.
Power Automate	Event-driven or conditional imports	Build a flow that writes data to Dataverse when triggered (e.g., when a form is submitted).
Power Query Online	Complex data shaping before import	Used within dataflows. Merge, filter, rename, and transform data before it lands in Dataverse.
Azure Data Factory	Enterprise-scale data pipelines	For large volumes and complex orchestration. Connects to hundreds of data sources.

Priya imports her marketing contacts

Priya at Spark & Co has a spreadsheet of 500 marketing contacts from a trade show. She opens the Contact table in Dataverse, clicks “Import data from Excel”, uploads the file, and maps the columns. Five minutes later, all 500 contacts are in Dataverse and ready for her Power Apps campaign tracker.

ℹ️ What are dataflows?

Dataflows are a Power Platform feature that lets you connect to external data sources, transform the data using Power Query, and load it into Dataverse on a schedule.

Think of it as a pipeline: data flows from the source (SQL database, SharePoint, web API) through transformations (filter rows, rename columns, merge tables) and into a Dataverse table.

Dataflows are ideal when you need to import data regularly — daily, weekly, or hourly — without manual effort.

Exporting data from Dataverse

Sometimes you need to get data OUT of Dataverse:

Export Method	Best For	How It Works
Export to Excel	Quick data extraction for analysis	Click “Export to Excel” from any table view. Opens in Excel Online or desktop.
Export to CSV	Flat file export for external systems	Similar to Excel export but produces a CSV file.
Power Automate	Automated data distribution	Build a flow that reads Dataverse rows and sends them to another system, email, or file.
Azure Data Factory	Enterprise data pipelines	Pull data from Dataverse into Azure SQL, data lakes, or data warehouses.
Dataverse Web API	Programmatic access	Use REST API calls to read data from any Dataverse table. Available to developers and external applications.

💡 Exam tip: Import vs export

The exam may describe a scenario and ask you to pick the right method. Key decision points:

• One-time, small dataset: Excel or CSV import/export
• Recurring, scheduled: Dataflows (import) or Power Automate (either direction)
• Complex transformation needed: Dataflows with Power Query
• Enterprise scale, many sources: Azure Data Factory
• Event-driven: Power Automate (when something happens, move data)

🎬 Video walkthrough

🎬 Video coming soon

Building Tables with Copilot — PL-900 Domain 2

Building Tables with Copilot — PL-900 Domain 2

~9 min

Flashcards

Question

How does Copilot help you create Dataverse tables?

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Answer

You describe what you need in natural language. Copilot suggests a table name, columns with appropriate data types, and sample data. You review, refine through follow-up conversation, and create the table.

Click to flip back

💡 Show hint

Question

What is a dataflow in Power Platform?

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Answer

A visual ETL (Extract, Transform, Load) tool that connects to external data sources, transforms data using Power Query, and loads it into Dataverse on a schedule. Ideal for recurring imports from multiple sources.

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💡 Show hint

Question

What are three ways to import data into Dataverse?

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Answer

Excel import (upload spreadsheet), CSV import (upload flat file), and Dataflows (scheduled ETL from external sources). Also Power Automate (event-driven) and Azure Data Factory (enterprise scale).

Click to flip back

💡 Show hint

Knowledge Check

Knowledge Check

Tom wants to quickly create a Dataverse table for property listings by describing what he needs in plain English. Which feature should he use?

AImport data from Excel to auto-generate a tableBCopilot in Power Apps to describe the table in natural languageCPower Automate to create the table schema automaticallyDAzure Data Factory to provision the table

Check Answer

Knowledge Check

Priya needs to import marketing contacts from a trade show spreadsheet into Dataverse. This is a one-time import. What is the simplest method?

ACreate a dataflow with Power QueryBBuild a Power Automate flowCImport directly from Excel in the table viewDUse Azure Data Factory

Check Answer

Knowledge Check

Aisha needs to automatically import shipping data from an external SQL database into Dataverse every night. Which method is most appropriate?

AManual Excel import each morningBDataflows with a scheduled refreshCCopilot table creationDExport to CSV from SQL and email it

Check Answer

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Next up: Environments and the Power Platform security model — how Aisha controls who can access what.