Local AI Agents for Data Analysts
Level
IntermediateDuration
8h / 1 dayDate
Individually arrangedPrice
Individually arrangedLocal AI Agents for Data Analysts
Learn practical applications of local AI agents in data analysis and report automation. The training shows how to collect data, calculate KPIs, detect anomalies, and generate business insights using local AI models and workflows in n8n and Power BI. Participants will learn to create end-to-end workflows for automating reports and alerts, increasing the efficiency of analytical processes and shortening reaction time to data deviations. The workshops allow introducing intelligent automation into the daily work of a data analyst. This training is ideal for data analysts and BI specialists who want to increase productivity and reporting quality.
Participant Requirements
- Basic knowledge of data analysis and reporting
- User-level knowledge of Power BI
- Basic knowledge of APIs and workflow automation
- Ability to run local AI models (e.g., local environment with Ollama or LM Studio)
What You Will Learn
- Automate cyclical reports and generate business narratives using AI
- Detect anomalies in data and KPIs and build alert systems
- Create workflows automating data quality tests and generating result reports
Who is this training for?
Data analysts
BI specialists working with Power BI
Automation and data process engineers
People responsible for data quality and testing
Training Program
Block 1: Automation of cyclical reports and anomaly detection
- Collecting data from sources, calculating KPI metrics
- Generating business narratives using AI (text description of results)
- Automatic anomaly detection and alerting on KPI deviations
- End-to-end workflow in n8n with local Ollama or LM Studio model
Block 2: Power BI – report automation and optimization
- Overview of Power BI API and integration with Python and n8n
- Automatically proposing optimization solutions based on table structure and data (e.g., query and visualization optimization)
- Automatic report refreshing and text insight generation
Block 3: Data test automation based on documentation
- Creating quality and consistency tests for data using AI with documentation and specifications
- Automatic detection of anomalies, gaps, and inconsistencies in data
- Workflow in n8n to automate data tests and generate result reports
Theoretical knowledge (minimum):
- Basics of AI supporting data analysis and reporting
- Mechanisms of local model operation and API integration
- Principles of building workflows with AI agents in the context of data analytics and Power BI