Successfully Implement Cloud MDM
Generate Business Value in 90 Days
Realize Business Value with Cloud MDM
The expectations for cloud MDM are sky high. Immediate deployment. Easy to use. Self-service. Fast time to value.
The reality isn’t so rosy. Cloud MDM can be deployed rapidly, it is easier to use. But it isn’t a self-service solution. And business value doesn’t just happen – it needs to be created.
Without a focus on business requirements, MDM can easily become an IT-driven implementation – gathering more and more data, but not solving more and more business problems.
Q Spark Group has a unique approach. Business leads technology. WE always focus on the business requirements, then map them to the technology required.
We understand MDM very, very well. We started the customer MDM market in the late 1990s. We’ve seen the highs and lows. And we know how to successfully implement cloud MDM.
Why You Should Modernize to Cloud MDM
Webinar - You're Not Stuck with IBM MDM
How to Move Forward, Modernize and Realize Value from it in 2025
December 5, 2024 2 PM ET / 1 PM CT / 11 AM PT

Learn from the experts that originally built and implemented IBM MDM on how to augment it with an eye to modernization down the road.
Q Spark Group are experts in implementing MDM solutions. We've been doing it for 25 years.
We're always happy to chat, learn and offer our advice.

Our Customers Benefit from Cloud MDM
Luxury Hotel Chain

We implemented modern data governance, catalog and reference MDM technologies to delivery trusted data for finance analysts.
US Insurance Company

We implemented a customer MDM/CDP hybrid to deliver a customer 360 for analytics/AI users generating insights in sales, marketing, & service.
Global Technology Firm

We implemented a CDP/MDM with AI entity resolution to match billions of customer & prospect records to execute micro targeted marketing campaigns.
Modernize to Cloud MDM - On-demand Webinar

Cloud MDM Solutions are not self-service apps.
Learn how to implement MDM successfully.
Best Practices in Implementing Cloud MDM

We've compiled our best practices gained from years of cloud MDM implementations. These practical recommendations will help you avoid pitfalls and create business value from your MDM deployment.
The Q Spark Difference
The Q stands for quick. We believe in sparking innovation, and doing it quickly.
We are focused on the customer domain. It's more than just customer 360. Knowing your customer's requires a tight integration between data, analytics and AI technologies.
Execution is our calling card. Our Quick Spark methodology is designed for relentless execution on aggressive timelines, and we meet them every time.
Q Spark is known for our expertise. Our team are comprised of 25+ year veterans in data management and analytics, and experts in AI.


Customer DNA

You have to go beyond data and beyond a 360 to truly understand your customers. You have to know their DNA – Data, aNalytics and AI.
Customer data is everywhere. MDM. CDP. Data Warehouses. Applications. CRM. Despite significant investment in many technologies, customer data is still fragmented.
Customer DNA is delivered by multiple technologies. It requires a solution.
Q Spark Group are experts in customer data solutions. We can modernize your Customer 360 strategy and understand customers down to their DNA.
Is Your Customer 360 Feeling a Little Flat?
Resources to Help You Implement Cloud MDM
Cloud MDM Blogs

The Current State of MDM – Part 4 – How Integrated, and Integral, is MDM?
Modern MDM solutions have impressive Data Quality functionality. But do they have impressive data quality? Maybe it’s time for their relationship to evolve.

The Current State of MDM – Part 3 – MDM & Data Quality Have Had a Long Relationship. Is it Time to Renew Their Vows?
Modern MDM solutions have impressive Data Quality functionality. But do they have impressive data quality? Maybe it’s time for their relationship to evolve.

The Current State of MDM – Part 2 – The Curious Relationship Between MDM and Data Governance
Twenty plus years after the emergence of MDM and data governance, their relationship remains unfulfilled. Both have reached a stage of maturity. So why aren’t there more proof points of them working together?