Quickstart
Get an overview of the DataLab interface and ask your first questions to the agent.
This guide outlines the steps to upload a CSV file and analyze data using the Alkemi DataLab interface. You can download the CSV we use in this guide from data.gov here or utilize any of the data products that are offered for free with your account.
Key Steps
The steps below outline the quickstart video above with links to where each step is discussed in the video.
Accessing Alkemi DataLab 0:00
Log In to Alkemi DataLab.
Familiarize yourself with the layout:
Left sidebar: Chat history and API endpoints.
Main chat input area for queries and commands.
Right sidebar: Credit balance, integrations, and current data slices.
Preparing to Upload a CSV File 1:11
Ensure you have a CSV file ready for upload (e.g., consumer price index historical data).
Uploading the CSV File 1:22
Use the upload functionality in Alkemi DataLab to upload your CSV file.
Review the columns in your CSV file, noting important attributes.
Creating a New Table from the CSV Data 2:11
Construct a query to filter and group data:
Filter by the attribute column (e.g., midpoint of prediction interval).
Group by consumer price index item.
Calculate a new column for forecast percent change.
Querying Results 2:50
Send the query to the Alkemi agent.
Wait for the results to be assembled and saved as a data asset.
Accessing and Reviewing the Results 3:06
Use the mentioning functionality to reference the new table in chat threads.
Click to expand and view the data, or download it as a CSV.
Cleaning and Sorting the Data 4:00
Remove any irrelevant categories (e.g., 'all food').
Sort the results by total increase in descending order.
Visualizing the Data 4:37
Request a visualization of the data (e.g., as a bar chart or pie chart).
Interact with the chart to view details and download it for presentations.
Next Steps 5:16
Consider connecting integrations like Snowflake for enhanced data analysis.
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