Infor Data Lake: Analytics Setup and Optimization Guide

Data Ingestion and Quality

Data Lake receives data through ION message flows, typically as BOD replications from connected applications. The quality of your analytics depends entirely on the quality of ingested data. Common issues include incomplete data replication (not all entities are replicated by default), stale data due to failed ION flows, and inconsistent data formats across applications that make cross-system reporting unreliable.

• Audit default data replication settings—many important entities are not replicated out of the box
• Configure ION flow monitoring to detect and alert on replication failures within minutes
• Standardize date formats, currency handling, and unit of measure across all source applications
• Implement data quality rules that flag inconsistencies before they reach analytics consumers

Report Design and Performance

Building effective Data Lake reports requires understanding the underlying data model, which mirrors the BOD structures from source applications. Star schema views are available for common reporting scenarios, but custom reports often require joining across multiple data objects. Query performance degrades rapidly with poorly designed joins and missing indexes—a report that runs in seconds on test data can take minutes on production volumes.

• Use pre-built star schema views for standard KPIs before creating custom data objects
• Design reports with filters that limit data scope—avoid full-table scans on large entities
• Schedule data-intensive reports for off-peak hours to avoid impacting interactive query performance
• Partition historical data by period to improve query performance on time-based analytics

AI-Enhanced Analytics

Netray's AI agents optimize Data Lake configurations by analyzing query patterns, identifying slow-performing reports, and recommending indexing and partitioning strategies. The agents also build predictive models on top of Data Lake data, turning your historical ERP data into forward-looking business intelligence.