Overview
What data integration covers, and where Great Minds fits
Data integration is the work of moving data between systems reliably: a sale in the CRM becomes an order in the ERP, a product updated in the PIM reaches the online store, a new starter in the HR system gets accounts and a laptop request, and every report reads from data that agrees. It covers the connections themselves (APIs, events, file transfers and pipelines), the rules about which system owns each piece of data, and the monitoring that tells someone when a sync fails.
Great Minds positions itself as the integrator for the gaps between platforms. We connect Salesforce, Microsoft Dynamics 365, Atlassian, Adobe, Akeneo, Shopify Plus, Klaviyo and the line-of-business systems around them, using each platform's own APIs and connectors where they fit, integration platforms such as n8n where they help, and custom code where neither will do. Our Integration Hub has the pre-built patterns we start from.
Most integration work starts from re-keying: staff copying orders, customers or tickets from one system to another, spreadsheets reconciling numbers that should match, or a new platform that is useless until it's connected. Increasingly it starts from AI, because agents can only act on systems and data they can reach.
Capabilities
What a data integration engagement covers
Each integration starts with a decision about ownership: which system is the source for each field, and what happens when two systems disagree. Then we choose the simplest pattern that meets the timing and volume needed, and build monitoring in from the start.
How we deliver
An integration project, from data map to monitored production
We list the systems involved, the data each holds, who owns it and how it moves today, including the manual steps and spreadsheets. The output is an integration map and a field-level decision on which system is the source of truth.
For each flow we choose the pattern (API call, event, scheduled batch or file), set timing and volume requirements, design error handling and retries, and agree security: authentication, least-privilege access and what personal information passes through.
Integrations built in a test environment against realistic data, with automated tests and trial runs of any migration. AI agents do much of the repetitive field mapping, transformation and test-data work; our consultants own the design and sign off every change. Our article on agentic AI in systems integration explains how that works.
Monitoring and alerts for failed or delayed syncs, run-books for your team and documentation of every flow. We can stay on to support the integrations, or hand over to your team with everything needed to run them.
Australian considerations
What Australian organisations need to build in
Integrations move personal information, so they fall under the Australian Privacy Principles as much as the systems at each end. APP 11 requires reasonable steps to protect personal information from misuse and unauthorised access, which for integrations means encrypted connections, least-privilege credentials and logs that don't copy more personal data than they need. If an integration platform processes or stores data offshore, APP 8 on cross-border disclosure applies, so check where each platform runs as well as where the source and target systems are hosted.
Integration maps have become a compliance asset. From 10 December 2026, privacy policies must disclose decisions that computer programs make, or substantially help make, about people. Those decisions rarely sit in one system, so documented integrations are what let you answer which programs use which personal information. Our guide to automated decisions and the Privacy Act covers the inventory.
For APRA-regulated entities, an integration platform that supports critical operations may be a material service provider under CPS 230, and integration credentials and data flows fall within CPS 234 information security controls.
FAQ
Data integration questions
What's the difference between data integration and an integration platform?
Data integration is the outcome: systems sharing data reliably. An integration platform, such as n8n or a vendor's own connector framework, is one tool for building it. Many integrations need no separate platform at all, because the systems' own APIs and connectors are enough.
Should integrations be real-time or batch?
Only as fast as the business needs. Stock levels on an online store or a new lead's first email may need seconds; finance reporting usually doesn't. Real-time integrations cost more to build and run, so we reserve them for flows that pay for it.
Do we need master data management software?
Not always. Many organisations get most of the benefit from agreeing owners, definitions and match rules, then enforcing them in the CRM, ERP or PIM they already run. Dedicated MDM software makes sense when many systems share the same entities at high volume.
How do we stop integrations breaking?
Design for failure: retries, alerts sent to a named person, logs that show what failed and why, and tests that run whenever either system changes. An integration without monitoring fails silently, and someone finds out weeks later from a report that doesn't add up.
Can AI agents use our integrations?
Yes. Agents act through the same APIs and connectors, and increasingly through MCP servers, with the same permissions and logging a person would have. See our agentic AI systems integration service and MCP integration.
Is data integration part of a data strategy?
It's usually where a data strategy turns into work. Our data strategy service decides ownership and priorities; data integration builds the connections that put them into practice.
People
Integration architects and engineers who understand the business
Our integration architects and engineers start with how data moves through your business, then design and build the connections, migrations and monitoring. They stay accountable for every flow in production, with AI agents doing repetitive mapping and testing under their review.
Case studies
Integration in practice
For a Dubai manufacturer, more than 2 million records were migrated from several systems into Microsoft Dynamics 365 with zero downtime at cut-over. For Meriton Suites, we connected the ecommerce environment to Klaviyo for real-time behavioural triggers.
One asset library for APAC, EMEA and North AmericaModernising creative storage and operations for a global retailerEnabling global brand consistency through enterprise Digital Asset Management
4x faster campaign execution, 1M+ contacts migratedSalesforce Marketing Cloud to Klaviyo migration with 1M+ email marketing recipientsUnlocking personalised growth at scale through Klaviyo implementation and data migration
Marketo and Salesforce connected for 2 fund launchesMarketo and Salesforce, connected for a global fund launchMarketo and Salesforce integrated into one marketing automation engine, so Montgomery could launch two global equity funds to the right investors at the right time.Insights
Guides to integration
Atlassian Data Center to Cloud: the Australian migration guideAtlassian Data Center goes read-only on 28 March 2029. Key dates, Australian data residency, CPS 230 and privacy checks, and a migration plan.
Adobe AEM Assets vs Bynder: choosing an enterprise DAMAdobe AEM Assets vs Bynder compared by a team that has delivered both: best fit, strengths, integrations and the questions that decide which DAM suits you.
AI in customer acquisition: what works for Australian marketersWhere AI genuinely improves customer acquisition, why connected first-party data comes first, and the Australian privacy and spam rules CMOs must plan for.