Episode 7: Enterprise Data Management Trends – Part 2: Modernization – Andy Crago

Summary

Data warehousing and governance go hand in hand, yet many companies struggle to integrate them effectively. In this episode, we break down how to align data governance with warehousing strategies, why metadata is key to AI readiness, and how to get started with minimal disruption. If you’re looking to improve data accessibility, security, and compliance while preparing for future AI-driven initiatives, this episode is a must-listen. Tune in now to learn the first steps toward building a scalable, governed data ecosystem!

Transcript

Jocelyn 00:02:
You’re listening to Infoverity’s Trust Us podcast, where you can gear up for your data management journey with bite-sized discussions on industry trends and thought leadership. On each episode, we feature industry experts to help you navigate your path to mastering your enterprise data.

Jocelyn 00:18:
Today, we’ll be talking again about trends in enterprise data management. To begin, I’d like to revisit what enterprise data management is. At its core, enterprise data management is the practice of mastering, centralizing, and integrating data across an organization to maximize its business value.

This can include:

• Mastering customer data to ensure targeted messaging and engagement.
• Managing product data for accurate and trustworthy consumer information.
• Ensuring organizational data integrity to maintain transparency and traceability.

This episode is the second of two that focus on trends in the industry, specifically on data management modernization—where to start and how to build a business-specific blueprint. To discuss this, we welcome Andy Crago, Vice President of Delivery Services at Infoverity, who has been with the firm since its inception in 2011.

Welcome, Andy! We’re so glad to have you here.

Andy Crago 01:32:
Thanks, Jocelyn! Happy to be here.

A bit about me—I’ve been with Infoverity since 2011 and have worked in data management consulting for over 17 years. I’m passionate about ensuring technology delivers real business value while fostering adoption and longevity. Excited to discuss data trends today!

Jocelyn 02:12:
That’s fantastic, Andy! Let’s start by defining data management modernization.

Andy Crago 02:35:
At a high level, data management modernization means upgrading databases, applications, and business processes to improve efficiency and competitiveness.

Key drivers include:

• Reducing technical debt– Moving from legacy, on-premise systems to modern architectures.
• Enhancing scalability– Leveraging cloud-based environments for flexibility and long-term growth.
• Optimizing workforce efforts– Allowing employees to focus on strategic business tasks instead of system maintenance.
• Enabling advanced analytics– Preparing data foundations for AI, ML, and predictive insights.

Organizations vary in their modernization needs. Long-established companies may face complex migration challenges, while newer enterprises build on modern cloud-native systems from the start.

Taylor Beckt 05:22:
That provides great context, Andy! Now that we understand modernization, how should organizations get started?

Andy Crago 05:40:
The key to success is understanding where you are in the data maturity spectrum and identifying a clear business use case.

Steps to get started:

1. Identify pain points– What inefficiencies or gaps exist in your current system?
2. Define business objectives– What value will modernization bring? How will ROI be measured?
3. Develop a phased roadmap– Avoid an all-at-once approach; instead, prioritize critical areas.
4. Consider hybrid solutions– Not everything needs to move to the cloud—some on-premise systems may remain beneficial.
5. Adopt an iterative approach– Implement changes gradually to minimize disruption and maximize adoption.

Jocelyn 07:37:
That makes a lot of sense! Breaking modernization into phases ensures incremental business value and smooth adoption.

Can you expand on what an effective roadmap looks like?

Andy Crago 08:21:
Most strategic roadmaps take a 16-24 month view, aligning with enterprise objectives. Key components include:

• Understanding business priorities– Is your focus on M&A growth, operational efficiency, or customer experience?
• Aligning IT and business stakeholders– Successful modernization requires buy-in from leadership and end-users.
• Emphasizing a hybrid approach– Identify what should move to the cloud and what remains on-prem.
• Prioritizing use cases– Start with initiatives that provide quick wins and long-term strategic value.

Jocelyn 10:23:
I love that these roadmaps are living documents that evolve alongside the business! Do you have any real-world examples of successful modernization?

Andy Crago 10:57:
Yes! One standout example is a global hotel chain that modernized its guest experience platform. Their goals were:

• Unifying customer loyalty data– Creating a centralized guest profile across multiple acquired brands.
• Enhancing customer engagement– Personalizing offerings based on purchasing behaviors.
• Streamlining operations– Reducing manual processes and increasing automation.

They prioritized data centralization, enabling a seamless customer experience across all brands. This was a multi-phased approach, avoiding disruption while delivering measurable business value.

Taylor Beckt 13:56:
That’s a great example! Now, how can Infoverity support organizations on this journey?

Andy Crago 14:12:
Infoverity provides strategic guidance and execution support through:

1. Modernization Roadmapping– Assessing current systems and defining an actionable, value-driven roadmap.
2. Technology Implementation– Assisting with cloud migration, data governance, and AI-readiness initiatives.
3. Industry Insights & Best Practices– Helping clients navigate trends like AI adoption, real-time analytics, and interoperability.
4. Iterative Change Management– Ensuring smooth adoption through phased implementation and ongoing stakeholder engagement.

Jocelyn 15:05:
That’s fantastic! Infoverity serves as an advisor and execution partner, making the overwhelming process of modernization manageable and impactful.

To summarize today’s discussion:

1. Data management modernization is about optimizing data systems for efficiency, scalability, and innovation.
2. Organizations should assess their data maturity, define clear objectives, and adopt a phased approach.
3. A strong roadmap aligns IT with business goals, ensuring strategic investment.
4. Infoverity provides expertise in planning, implementation, and long-term support.

Andy, would you say that’s an accurate summary?

Andy Crago 17:19:
Absolutely! Just to reiterate—modernization must be rooted in business needs, not just technology trends. Companies should prioritize challenges that impact their business most and ensure modernization delivers tangible value.

Jocelyn 19:14:
Thank you so much, Andy! Your insights have been incredibly valuable.

Andy Crago 19:18:
Thanks for having me!

Taylor Beckt 19:21:
Thank you, Andy!

Jocelyn 19:23:
For over a decade, Infoverity has been a trusted leader in enterprise data management consulting, with experts worldwide and headquarters in Columbus, Ohio, and Valencia, Spain.

To learn more, visit infoverity.com. Additional contact details are in the show notes.