• Blog
  • Podcast
  • Contact
  • Sign in
CloverDX Logo
Product
  • OVERVIEW
  • Discover CloverDX Data Integration Platform###Automate data pipelines, empower business users.
  • Deploy in Cloud
  • Deploy on Premise
  • Deploy on Docker
  • Plans & Pricing
  • Release Notes
  • Documentation
  • Customer Portal
  • More Resources
  • CAPABILITIES
  • Sources and Targets###Cloud and On-premise storage, Files, APIs, messages, legacy sources…
  • AI-enabled Transformations###Full code or no code, debugging, mapping
  • Automation & Orchestration###Full workflow management and robust operations
  • MDM & Data Stewardship###Reference data management
  • Manual Intervention###Manually review, edit and approve data
  • ROLES
  • Data Engineers###Automated Data Pipelines
  • Business Experts###Self-service & Collaboration
  • Data Stewards###MDM & Data Quality
clip-mini-card

 

Ask us anything!

We're here to walk you through how CloverDX can help you solve your data challenges.

 

Request a demo
Solutions
  • Solutions
  • On-Premise & Hybrid ETL###Flexible deployment & full control
  • Data Onboarding###Accelerate setup time for new data
  • Application Integration###Integrate operational data & systems
  • Replace Legacy Tooling###Modernize slow, unreliable or ad-hoc data processes
  • Self-Service Data Prep###Empower business users to do more
  • MDM & Data Stewardship###Give domain experts more power over data quality
  • Data Migration###Flexible, repeatable migrations - cloud, on-prem or hybrid
  • By Industry
  • SaaS
  • Healthcare & Insurance
  • FinTech
  • Government
  • Consultancy
zywave-3

How Zywave freed up engineer time by a third with automated data onboarding

Read case study
Services
  • Services
  • Onboarding & Training
  • Professional Services
  • Customer Support

More efficient, streamlined data feeds

Discover how Gain Theory automated their data ingestion and improved collaboration, productivity and time-to-delivery thanks to CloverDX.

 

Read case study
Customers
  • By Use Case
  • Analytics and BI
  • Data Ingest
  • Data Integration
  • Data Migration
  • Data Quality
  • Data Warehousing
  • Digital Transformation
  • By Industry
  • App & Platform Providers
  • Banking
  • Capital Markets
  • Consultancy & Advisory
  • E-Commerce
  • FinTech
  • Government
  • Healthcare
  • Logistics
  • Manufacturing
  • Retail
Migrating data to Workday - case study
Case study

Effectively Migrating Legacy Data Into Workday

Read customer story
Company
  • About CloverDX
  • Our Story & Leadership
  • Contact Us
  • Partners
  • CloverDX Partners
  • Become a Partner
Pricing
Demo
Trial

Bringing a human perspective to data integration, mapping and AI

Data Integration
Posted February 17, 2025
4 min read
Bringing a human perspective to data integration, mapping and AI

AI may dominate the headlines, but at its core, data integration remains a deeply human challenge. This was one of the standout themes from our recent conversation with Markus Kolic, Associate Director of Engineering at Sun Life U.S., on the latest episode of our Behind the Data podcast.

Markus shared his insights on making progress in the rapidly changing world of AI, the complexities of integrating legacy systems with modern platforms, and the importance of understanding the human factors behind data systems.

”All of these things are people from the beginning,” said Markus. “All of the systems that we build, all of the software that we have, is here to serve the people."

Here are some of the key takeaways from our discussion.

Experimenting with AI in a world of unpredictability

We’re living in what Markus describes as ‘a moment of incredible possibility’ for AI. Yet, while large language models like ChatGPT are generating immense hype, Markus cautions against rushing to implement AI-driven solutions without fully understanding their potential and their unpredictability.

“The basic challenge in a business that is regulated and profit-driven,” Markus explains, “is that generative AI by definition involves some unpredictability. It’s a non-deterministic system. You could put the same input into it twice and get two different results.”

This unpredictability can be unsettling for enterprises that thrive on consistency and control. Markus stresses that organizations must allow room for experimentation, failure, and rapid iteration if they want to harness AI effectively.

“You need room for experimentation. You need room for iteration. And you need room for failure,” he says. “The way to succeed with AI is going to be to take a few smart people and put them in a room and let them experiment for a year.”

A practical approach to legacy systems

For organizations dealing with legacy systems, Markus advocates for the strangler pattern: a strategy that allows businesses to modernize incrementally, rather than attempting a risky, large-scale replacement.

“The strangler pattern is a model for moving [legacy systems] gradually,” he explains. It is inspired by Martin Fowler’s article on the strangler fig. “Instead of replacing your whole system outright, you go piece by piece. You rewrite one portion in a microservice or in whatever your new system is, and you link them together using APIs.”

This incremental approach helps minimize disruption and allows teams to adapt as they go. However, Markus warns of the risks associated with getting stuck midway.

“If you stop halfway through… you’ve made the problem worse instead of better,” he says. “Inherently, when you’re following this kind of pattern, you are making compromises and temporary workarounds along the way. And there’s the old truism from corporate software development: There is nothing so permanent as a temporary solution.”

Human-first data mapping

Sun Life’s ongoing efforts to integrate and modernize its data systems reflect the importance of a human-centred approach to data mapping. Markus describes his team’s process of creating a domain-driven data model that reflects a shared understanding of key concepts like insurance policies and member records.

“Data is not information until it can be used and understood by a human,” Markus explains. “You need to understand the people that it is from, the people that are handling it, and the people that it is for.”

This process, however, is far from straightforward. Markus likens it to archaeology:

“Older systems… embed their own assumptions about what that data means and how it works. There’s archaeology involved in all of this as well. You’re trying to figure out what those concepts were in the first place.”

To ensure that this work is collaborative and adaptable, Markus’s team has moved its data mappings to GitHub, using YAML files to create a versioned, living document.

“Your data mapping needs to be a living document,” he says. “It needs to be something that can be collaborated on and shared by everybody… We store these mappings in readable YAML, so when anybody working with our teams wants to update this, you edit the YAML and open a pull request and we can see exactly what is changed and when and by whom.”

A flexible partner for integration

CloverDX has been central to Markus’s work, serving as a flexible, scalable platform for data integration at Sun Life. One of its standout benefits, Markus says, is its compatibility with agile development practices.

“Our team using Clover as its platform… can get a request for some new piece of data, and build it almost immediately in Clover. Just drag a couple of components onto a screen, define it, open a pull request, get it reviewed, merge it, test it, deploy it in the space of maybe a couple of hours. In a corporate context, that is astounding.”

This agility has allowed Sun Life to scale its data operations while maintaining flexibility, making CloverDX a powerful tool for tackling both legacy and modern data challenges.

By emphasizing the human element, organizations can ensure that their data initiatives succeed and deliver meaningful value.

To hear our entire conversation with Markus Kolic, check out the full episode.

If you’re ready to see how CloverDX can transform your data operations, get in touch with our team today.

Share

Facebook icon Twitter icon LinkedIn icon Email icon
Behind the Data  Learn how data leaders solve complex problems every day

Newsletter

Subscribe

Join 54,000+ data-minded IT professionals. Get regular updates from the CloverDX blog. No spam. Unsubscribe anytime.

Related articles

Back to all articles
How AI is shaping the future of data integration
Data Integration
4 min read

How AI is shaping the future of data integration

Continue reading
Data visualization with a dashboard on a computer screen
Data Integration
4 min read

Data literacy, visualization and the challenges of data integration

Continue reading
Woman considering what data integration software to choose
Data Integration
11 min read

Choosing the right data integration software: 12 essential questions

Continue reading
CloverDX logo
Book a demo
Get the free trial
  • Company
  • Our Story
  • Contact
  • Partners
  • Our Partners
  • Become a Partner
  • Product
  • Platform Overview
  • Plans & Pricing
  • Customers
  • By Use Case
  • By Industry
  • Deployment
  • AWS
  • Azure
  • Google Cloud
  • Services
  • Onboarding & Training
  • Professional Services
  • Customer Support
  • Resources
  • Customer Portal
  • Documentation
  • Downloads & Licenses
  • Webinars
  • Academy & Training
  • Release Notes
  • CloverDX Forum
  • CloverDX Blog
  • Behind the Data Podcast
  • Tech Blog
  • CloverDX Marketplace
  • Other resources
Blog
The vital importance of data governance in the age of AI
Data Governance
Bringing a human perspective to data integration, mapping and AI
Data Integration
How AI is shaping the future of data integration
Data Integration
How to say ‘yes’ to all types of data and embark on a data-driven transformation journey
Data Ingest
© 2025 CloverDX. All rights reserved.
  • info@cloverdx.com
  • sales@cloverdx.com
  • ●
  • Legal
  • Privacy Policy
  • Cookie Policy
  • EULA
  • Support Policy