Data Integration Consulting: Connect Every Source Into a Unified Data Estate
The average enterprise runs 130+ SaaS applications, multiple databases, and legacy systems that don't talk to each other. Integration isn't optional — it's the engineering challenge that determines whether your data platform delivers value or collects dust.
API-Led Integration
REST, GraphQL, SOAP, webhooks — connecting SaaS, databases, and internal systems
ETL/ELT Pipelines
ADF, Fabric pipelines, dbt, Airflow, Fivetran — batch and incremental loads
Real-Time Data Sync
Change data capture, event streaming, near-zero-latency replication
Cross-Platform Connectivity
Salesforce ↔ Fabric, D365 ↔ Snowflake, SAP ↔ Databricks, and everything between
Integration is the unglamorous work that makes data platforms actually work.
Everyone wants the lakehouse, the AI models, the real-time dashboards. Nobody wants to talk about the 47 source systems that need to feed them. But integration is where most data programs stall — not because the target platform lacks features, but because the connectors, pipelines, and sync mechanisms between sources and targets are fragile, poorly documented, or simply missing.
The problem intensifies as enterprises adopt multiple cloud platforms. A typical mid-market company might run Salesforce for CRM, D365 for ERP, Workday for HR, and Fabric or Snowflake for analytics. Each system has its own API patterns, authentication models, rate limits, and data change semantics. Connecting them reliably — with proper error handling, retry logic, and lineage tracking — requires specialized integration engineering.
Xylity matches integration engineers who understand both the source systems and the target platforms. Whether you need MuleSoft developers, Azure Data Factory specialists, or custom API engineers — our consulting-led matching evaluates candidates against your specific integration landscape.
Data integration consulting capabilities
Every integration engagement is staffed by engineers who understand your specific source systems, target platforms, and the connectivity patterns between them.
API Development & Integration
REST API design, GraphQL implementation, webhook handlers, and API gateway configuration. Custom connectors for systems without native integration support. Rate limiting, pagination handling, and error management built for production reliability.
ETL/ELT Pipeline Development
Batch and incremental data pipelines using ADF, Fabric Pipelines, dbt, Airflow, Fivetran, or custom orchestration. Source extraction, transformation logic, data quality gates, and loading into your target warehouse or lakehouse.
See ETL development →Real-Time Data Sync
Change data capture (CDC), event streaming (Kafka, Event Hubs, Eventstreams), and near-real-time replication between operational and analytical systems. For use cases where batch latency is unacceptable — fraud detection, inventory tracking, live dashboards.
See real-time analytics →ERP & CRM Integration
Salesforce, Dynamics 365, SAP, NetSuite, Workday — extracting data from enterprise applications into your data platform. Pre-built connector optimization, custom extraction for complex entities, and incremental sync for high-volume transactional data.
iPaaS & Middleware Implementation
MuleSoft Anypoint, Azure Logic Apps, Boomi, Workato, or Informatica Cloud configuration and development. API-led connectivity architecture, process orchestration, and B2B integration for partner data exchange.
Data Virtualization & Federation
Querying across multiple data sources without physical data movement. Denodo, Azure Synapse serverless, or Databricks lakehouse federation for real-time cross-platform analytics without ETL bottlenecks.
Tools and technologies we work with
Azure Data Factory
150+ connectors, copy activities, mapping data flows, pipeline orchestration
Fabric Pipelines
Dataflows Gen2, data pipelines, Spark notebooks, OneLake shortcuts
MuleSoft
Anypoint Platform, RAML/OAS, DataWeave, CloudHub, API-led connectivity
Fivetran / Airbyte
Pre-built connectors, managed ELT, schema drift handling, normalization
dbt
Transformation-as-code, staging models, marts, testing, documentation
Apache Kafka
Event streaming, CDC, Kafka Connect, Schema Registry, real-time pipelines
Apache Airflow
DAG-based orchestration, sensor patterns, task dependencies, monitoring
Logic Apps / Boomi
Low-code integration, process automation, B2B connectors, triggers
Integration engineers matched to your data landscape
Integration Assessment
We map your source systems, target platforms, data volumes, latency requirements, and current integration gaps. The matching starts from your specific landscape.
Specialist Matching
Engineers matched for your specific sources (Salesforce, D365, SAP) and targets (Fabric, Snowflake, Databricks). Platform-specific evaluation ensures production-ready skills.
Pipeline Development
Connectors, pipelines, and sync mechanisms built with proper error handling, retry logic, data quality gates, and monitoring. Production-grade from the start.
Monitor & Optimize
Pipeline performance monitoring, cost optimization, alerting setup, and runbook creation. Your integration layer is operational and your team owns it.
Integration expertise for enterprises and IT services companies
Data platform ready but sources still disconnected?
You've invested in Fabric, Snowflake, or Databricks — but the platform can only deliver value when it's connected to your operational systems. Xylity matches integration engineers who understand both your source applications (Salesforce, D365, SAP, Workday) and your target platform architecture. Consulting-led solutioning ensures the integration design fits your data strategy.
Start a Consulting Engagement →Client needs integration specialists your bench doesn't have?
Integration projects require a specific combination of source-system knowledge (Salesforce APIs, D365 OData, SAP BAPIs) and target-platform skills (ADF, Fabric Pipelines, dbt). When your bench doesn't cover both sides, Xylity delivers curated integration profiles from our 200+ partner network. First profiles in an average of 4.3 days.
Scale Your Integration Delivery →Data integration consulting — answered
Your data platform needs connected sources
to deliver connected insights.
Tell us about your source systems, target platform, and integration requirements. We'll match engineers who've built the exact connectivity your data estate needs.