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boltQuickstart

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 herearrow-up-right or utilize any of the data products that are offered for free with your account.

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Key Steps

The steps below outline the quickstart video above with links to where each step is discussed in the video.

1

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Accessing Alkemi DataLab 0:00arrow-up-right

  • Log In to Alkemi DataLab.arrow-up-right

  • 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.

2

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Preparing to Upload a CSV File 1:11arrow-up-right

  • Ensure you have a CSV file ready for upload (e.g., consumer price index historical data).

3

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Uploading the CSV File 1:22arrow-up-right

  • Use the upload functionality in Alkemi DataLab to upload your CSV file.

  • Review the columns in your CSV file, noting important attributes.

4

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Creating a New Table from the CSV Data 2:11arrow-up-right

  • 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.

5

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Querying Results 2:50arrow-up-right

  • Send the query to the Alkemi agent.

  • Wait for the results to be assembled and saved as a data asset.

6

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Accessing and Reviewing the Results 3:06arrow-up-right

  • 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.

7

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Cleaning and Sorting the Data 4:00arrow-up-right

  • Remove any irrelevant categories (e.g., 'all food').

  • Sort the results by total increase in descending order.

8

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Visualizing the Data 4:37arrow-up-right

  • 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.

9

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Next Steps 5:16arrow-up-right

  • Consider connecting integrations like Snowflake for enhanced data analysis.

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