Connect your disparate systems into a unified data ecosystem with reliable data integration and ETL pipelines.

When your data is scattered across dozens of systems that do not talk to each other, reporting becomes manual, error-prone, and slow. Our data integration service builds the pipes that connect your systems together, transforming raw data from multiple sources into a clean, consistent dataset that is ready for analysis.
We design and implement ETL (Extract, Transform, Load) pipelines that run automatically, pulling data from your CRM, accounting software, e-commerce platform, and operational systems into a centralised data warehouse where it can be queried, reported on, and analysed.
Our integration approach is designed for reliability. Every pipeline includes error handling, logging, and alerting so you know immediately if something goes wrong. We build idempotent processes that can be safely re-run without duplicating data, and we implement incremental loading so only new or changed records are processed each time.
We work with both modern cloud-based integration tools like Azure Data Factory, AWS Glue, and Google Dataflow, and traditional ETL platforms depending on your environment. For simpler integrations, we also build lightweight solutions using APIs, webhooks, and tools like n8n or Zapier.
Data quality is built into every pipeline. We implement validation rules, deduplication logic, and standardisation routines that catch and correct common issues before they reach your reporting layer. Clean data in means accurate insights out.
We integrate virtually any system that exposes data through an API, database connection, file export, or webhook. Common examples include Xero, MYOB, Salesforce, HubSpot, Shopify, custom databases, and spreadsheets. If the data exists, we can usually get to it.
Typically in a cloud data warehouse such as Google BigQuery, Snowflake, or Azure Synapse. For smaller-scale projects, we also use PostgreSQL or SQL Server databases. We recommend the platform that best balances your performance needs, budget, and existing tooling.
That depends on your needs. Most clients run daily or hourly syncs, but we can configure near-real-time streaming for time-sensitive data. We design the pipeline frequency around how quickly you need the data and the load your source systems can handle.