Feather (.feather) Integration with Edilitics
Feather is a binary columnar data storage file format specifically designed for efficient storage and retrieval of data frames. Developed collaboratively by the pandas and Apache Arrow communities, Feather offers high performance for reading and writing data, making it an excellent choice for data interchange between tools like Python and R. Its ability to handle large datasets efficiently makes it a valuable resource for data scientists and analysts.
In Edilitics, Feather files are exclusively used as data sources for advanced analytics. This step-by-step guide provides detailed instructions on configuring and integrating Feather files within Edilitics for seamless data analysis.
Before You Begin
Ensure the following prerequisites are met:
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File Size Limit: Feather files must not exceed 100 MB.
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Recommended Format: Structuring data as a DataFrame ensures optimal performance within Edilitics.
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Usage Constraints:
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Feather files are only supported as data sources, not destinations.
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Workflows using Feather files:
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Allow full loads with "Schedule as Once" in Replicate.
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Support "Schedule as Once" in Transform.
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Do not support auto updates or data refreshes in Visualize.
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AI Column Insights: Feather files are not eligible for AI Column Insights.
Note: If your data is not structured as a DataFrame, consider reshaping it before upload to maximize compatibility and performance within Edilitics.
File Security and Management
Edilitics ensures robust security and management of Feather files:
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Security Scans: All uploaded files are thoroughly scanned for potential risks and data accuracy.
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Encryption: Files are securely encrypted during storage and decrypted only during user access or workflow execution (Replicate, Transform, Visualize).
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Permanent Deletion: Upon deleting an integration, the associated file is permanently removed from Edilitics systems, ensuring data privacy compliance.
Supported Data Structures
Edilitics supports the following Feather data structures, enabling versatile and scalable workflows:
| Data Structure | Description | Example |
|---|---|---|
| DataFrames | Two-dimensional, tabular data structures with labeled axes (rows and columns). | Sales data with columns for Date, Product, Quantity, and Price. |
| Arrays | Sequences of elements of the same type. | Daily temperatures for a month: [30, 32, 31, 29, 28, 27, 26]. |
| Series | One-dimensional labeled arrays capable of holding any data type. | Sales figures for a single product over time: [100, 150, 200, 130, 170]. |
Note: Structuring your Feather data as a DataFrame is recommended to simplify analysis and ensure performance efficiency within Edilitics.
Steps to Integrate Feather Files
Step 1: Add the Feather Connector
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Navigate to the Integrations module in Edilitics.
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Click on New Integration.
- Search for and select the Feather connector.
Step 2: Configure the Integration
Enter the following details on the setup screen:
| Field Name | Details |
|---|---|
| Integration Title | A unique identifier for your integration. |
| Integration Description | A concise summary of the Feather data being integrated. |
| File Upload | Upload the Feather file directly from your local storage (must be ≤ 100 MB). |
Step 3: Validate and Save
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Click Test & Save Connection to validate the uploaded file.
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Edilitics scans the file for schema compliance and security validation.
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Upon successful validation, the file is securely encrypted and saved for use in workflows.
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