Safely Prototype and Analyze Data

Managed Development Workspaces

Leverage secure, collaborative, and managed environments for Python, R, SQL, and BigQuery without affecting your production datasets.
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Secure, Flexible, and Collaborative Data Workspaces for Python, R, SQL, and BigQuery

What Are Keboola Workspaces?

Keboola Workspaces offer a dedicated, managed, and secure environment where data analysts, engineers, and scientists can safely develop code, prototype new data solutions, or perform exploratory analysis—without ever risking the integrity of your production datasets.

Workspaces are entirely separate from Keboola Storage, which means any action performed within a workspace never directly impacts your main data repository. Accidentally deleted or corrupted data in a workspace? Reload the current data from storage easily, keeping your production environment intact.

Benefits of Keboola Workspaces

  • Security & Isolation: Keep your production data safe by isolating experimental and developmental work.
  • Collaboration: Share workspaces seamlessly with colleagues and improve the efficiency of your team.
  • Flexible Backend Sizes: Easily adjust workspace backend size to match your computational needs.
  • Cost Management: Auto-sleep and auto-timeout features help manage your workspace costs effectively.
  • Easy Integration: Smoothly transition proven prototypes and queries back into your production environment.

Types of Keboola Workspaces

Keboola offers different types of workspaces tailored for specific analytical needs.

1. Python and R Workspaces

Python and R workspaces are provisioned with a fully-featured JupyterLab environment. You can effortlessly perform exploratory data analysis, data modeling, machine learning, and more.

  • Auto-backups: Your work is continually backed up to avoid accidental loss.
  • Auto-sleep: Workspaces automatically pause after a period of inactivity, helping manage workloads and costs.
  • Adjustable Backend Size: Scale up your computational power as needed, depending on your project requirements.

2. SQL Workspaces (Snowflake)

SQL workspaces in Keboola create dedicated schemas and provide secure credentials, enabling you to work with your preferred SQL IDE.

  • Easy Setup: Quickly create a workspace, name it, and map input tables directly from Keboola Storage.
  • Input Mapping: Easily select and load tables into your workspace, allowing you to begin analysis instantly.
  • Collaboration Capabilities: Share your workspace securely with teammates, or set it to read-only mode for safe data exploration.

Example Workflow (SQL Workspace in Snowflake):

  1. Create a new workspace and name it (e.g., "Introduction Workspace 1").
  2. Decide whether to share your workspace for collaboration or keep it private.
  3. Set input mapping to select the tables you wish to analyze.
  4. Load data and obtain credentials to connect to the workspace via your preferred SQL IDE.
  5. Perform queries, transformations, and refine your SQL code.
  6. Once satisfied, copy your tested queries back into your Keboola production transformations.

3. BigQuery Workspaces

Keboola also provides managed BigQuery workspaces, seamlessly integrated with your preferred IDEs, such as DBeaver or DataGrip.

  • Flexible IDE Integration: Use your favorite IDE for querying and developing analysis.
  • Credentials Management: Quickly obtain and download credentials to securely connect your workspace.
  • Collaboration & Sharing: Share your workspace easily with team members, allowing for collaborative development and data review.
  • Read-Only Mode: Allow safe exploration of data without the risk of accidental modifications.

Example Workflow (BigQuery Workspace):

  1. Create a workspace named "Introduction Workshop 1".
  2. Share workspace with colleagues to enhance collaboration.
  3. Choose to set the workspace in read-only or full-access mode depending on your needs.
  4. Connect to your workspace securely via your chosen IDE (e.g., DBeaver).
  5. Perform exploratory queries, analysis, and prototyping.
  6. Finalize your queries and incorporate them into your production environment.

Cost Efficiency with Keboola Workspaces

Keboola Workspaces include features specifically designed to help manage costs effectively:

  • Auto-Sleep & Timeouts: Python and R environments automatically shut down after one hour of inactivity, significantly reducing resource consumption and expenditure.
  • Pay for What You Use: Credits are charged only while workspaces are active, ensuring you only pay for utilized resources.

Why Choose Keboola Workspaces?

Keboola Workspaces empower your team to innovate, collaborate, and experiment freely without compromising data safety. Whether you are prototyping advanced machine learning models, exploring new market segmentation strategies, or conducting rigorous data analysis, Keboola provides the ideal managed environment tailored to your needs.

Start leveraging Keboola Workspaces today and experience a seamless, secure, and collaborative environment optimized for productive data workflows.

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