Lumi Docs
  • About Lumi AI
  • Setting Up
    • Quick Start
    • 1. Connect
    • 2. Configure
      • Configuration Tips
      • Add Tables & Fields
      • Add Business Context
      • Advanced Configuration
    • 3. Distribute
  • Using Lumi
    • Getting Started
    • Lumi Use Cases
      • Data Exploration
      • Business Metrics
      • Anomaly Detection
      • Trend Analysis
      • Root Cause Analysis
      • Data Quality
    • Best Practices
      • Prompting Best Practices
      • Boards Best Practices
      • Versioning Best Practices
    • Chat Limitations
    • Knowledge Base Utility
      • Curated Prompts
      • Leveraging Memories
    • Network Configuration
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      • Overview
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      • Deployment
      • Configuring for Boot
    • Source System Integrations
      • PostgreSQL
      • Microsoft SQL Server
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      • Databricks
      • BigQuery
      • Snowflake
      • SAP HANA
      • Oracle
    • Secondary Interfaces
      • Slack
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On this page
  • Data Analytics Playbook
  • Data Exploration
  • Business Metrics
  • Anomaly Detection
  • Trend Analysis
  • Root Cause Analysis
  • Data Quality
  • Predictive Analytics

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  1. Using Lumi

Lumi Use Cases

Data Analytics Playbook

Lumi can be used to perform a wide variety of essential data analysis operations that are critical for any real world application to uncover business insights that translate to measurable outcomes. These categories are an overview to showcase Lumi capabilities.

Data Exploration

  • Data Search & Filtering

  • Basic Aggregations

Business Metrics

  • Advanced KPI Calculation

Anomaly Detection

  • Outlier Detection

  • Exception Reporting

Trend Analysis

  • Time-Series Analysis

  • Comparing Metrics Across Time Periods

Root Cause Analysis

  • Drill-Down Analysis

Data Quality

  1. Missing Data & Duplicate Detection

  2. Data Validation: Logic & Consistency

Predictive Analytics

  • [coming soon]

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Last updated 14 days ago

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