Platform

2024 Release 1 - Intelligence

Impact AI - AI-powered Data Lineage (Private Beta)

Get the full picture of your data lineage with AI-driven insights.

What

Impact AI empowers users with comprehensive data lineage capabilities and AI-powered insights, enabling them to make informed decisions and maximize data's business value in Keboola.

Who

  • Data Analysts: Discover data, understand lineage, and improve data quality.
  • Data Engineers: Identify performance bottlenecks, optimize costs, and enhance data security.
  • Data Scientists: Gain insights from data, build predictive models, and automate data analysis tasks.
  • Business users: Employ Impact AI to make data-driven decisions, access relevant information, and collaborate effectively.

Example Use Cases

  • Detect and prevent impacts on production:
    • Detect changes that could impact production
    • Detect disabling configurations that could affect downstream processes
    • Pinpoint responsible parties for outages and ensure accountability
  • Cost optimization and efficiency:
    • Identify opportunities for cost optimization
    • Flag duplicate tables
    • Track data lineage and calculate daily costs for running tables
    • Calculate increased costs for hourly computation
    • Identify the actual frequency of data updates
    • Determine bottlenecks to improve efficiency

Clarify AI for Errors & Configuration (General Availability)

Get AI-powered help with documentation and debugging

What

Clarify AI in Keboola helps you to resolve complex errors effortlessly. With just a click of a button, our advanced AI system will analyze any complicated error messages you encounter and provide clear, human-readable explanations. No more confusion or frustration with complicated errors.

Who

  • AI Developers and Data Engineers: Seamless troubleshooting and uninterrupted development.
  • Data Analysts: Focus on analysis, not documentation.
  • Technical Writers: Generate accurate technical content effortlessly.
  • Product Managers: Accelerate project timelines and deliverables with improved productivity and communication.

Example Use Cases

  • Simplicity and convenience: Clarify AI is simple to use, taking just a single click. 
  • Clarity and understandability: AI will translate complex error messages into language that users can easily comprehend, eliminating technical jargon and confusion.
  • Empowerment: AdaptAI empowers users to troubleshoot issues on their own, enabling them to act and resolve problems faster.
  • Efficiency: ‌AI-driven explanations save users time by providing instant insights, avoiding the need for lengthy research or seeking external help.
  • Problem-solving: Clarify AI promotes a smooth problem-solving experience, making users feel more confident and in control of their interactions with the platform.

Self-service Data Apps (Public Beta)

Easily visualize, collect & modify data

What

From data to app in minutes! Data Apps come with visualization front-end that is real-time, modifiable and interactive, and enables you data writeback. Only analyst-level coding skill needed or choose from pre-built gallery of apps.

Who

  • Business users: Deliver results faster with apps that enable immediate insights and rapid collaboration
  • Data and BI Analysts: Build apps without development expertise in minutes, easily visualize data and explore data insights. 
  • Data Engineers: One-click deployment, no maintenance and full governance.

Example Use Cases

  • Predictive analytics and forecasting: Implement AI models to predict future trends based on historical data.
  • Data monitoring and alerts: Developing applications that monitor data metrics in real-time and trigger alerts or notifications based on specific thresholds or anomalies detected in the data.
  • Unlimited use cases: Great flexibility in connecting your data and their usage in new context. Uncover value.
  • Data visualization and exploration: Streamlit apps are widely used to create interactive dashboards that enable users to explore their data through dynamic charts, graphs, and filters.
  • Machine Learning model development: Developers can use Streamlit to prototype and demonstrate training models, visualize model performance, and tweak parameters in real-time.
  • Governed data entry: Error-free user input collection.

Learn more about Self-service Data Apps in documentation.