ETL pipelines, data cleansing, and cross-system integration that unify disparate sources into a single source of truth — accelerated by AI-powered data preparation, intelligent mapping, and Microsoft Fabric.
Start a ProjectFrom messy raw data to clean, connected, analytics-ready pipelines — built for reliability, scalability, and long-term maintainability.
Identify and resolve duplicates, nulls, format inconsistencies, and outliers across structured and semi-structured data — before they reach your analytics layer.
Design and build Extract, Transform, Load pipelines using SSIS, Azure Data Factory, and Power Query for automated, reliable data movement across systems.
Connect and unify data from SQL Server, Excel, SharePoint, REST APIs, flat files, and cloud platforms into a single coherent, analytics-ready dataset.
Architect both scheduled batch loads and near-real-time streaming pipelines — designed around your latency requirements and data volume.
Document and implement field-level mappings, business rule transformations, and data type conversions between source and target systems.
Build automated validation rules, reconciliation checks, and audit logging to ensure data integrity end-to-end — with full traceability for compliance.
Every engagement incorporates Microsoft's AI layer — reducing manual effort, surfacing data quality issues automatically, and accelerating pipeline delivery.
Generate pipeline activities, transformations, and expressions using natural language prompts in Azure Data Factory — cutting pipeline authoring time dramatically.
Automatically profile datasets with Azure Purview to detect anomalies, distribution patterns, and quality issues before transformation begins — eliminating surprises mid-project.
Intelligent column type detection, example-based transformations, and fuzzy matching for messy data cleanup — resolving SKU mismatches and naming inconsistencies automatically.
Next-generation cloud-scale dataflows with AI-assisted authoring, OneLake integration, and unified analytics — the modern foundation for enterprise data integration.
See how AI-enhanced Data Wrangling & Integration delivers measurable results across industries.
A multi-location retailer unified inventory, POS, and e-commerce data from three siloed systems into one analytics warehouse — eliminating 15 hours of weekly manual reconciliation.
Three merged hospitals with incompatible EMR systems achieved a unified patient data store in 90 days — with 94% AI-assisted patient match accuracy and zero historical records lost.
A financial institution's two-week quarterly compliance process was reduced to two days using AI-assisted ADF pipelines — with a 100% audit trail for every transformed record.
3,200 production floor sensors were generating data that was being discarded. A real-time Azure pipeline captured and landed it in Fabric — enabling an ML model with 87% failure prediction accuracy.