10 Questions to Ask Before Building Your Own Data Platform

This Insider Insights post was written by DataFreedom’s Senior Business Development Consultant Josh Millin and originally appeared on his LinkedIn profile.

In DataFreedom’s last blog, we examined whether firms should build their own in-house real estate data platforms and the challenges that approach can present. To dive deeper into the build vs. buy decision-making process, it’s critical to assess how well firms understand what that path entails. 

Building your own data platform can indeed be transformational. But it can also be one of the largest technology investments an organization ever makes — and one of the easiest to get wrong for the right-sounding reasons.

Sure, cloud platforms such as Microsoft Fabric, Snowflake, and Databricks have made infrastructure more accessible than ever, and that accessibility makes building feel straightforward. But the infrastructure was never the hard part. The hard part is the knowledge: understanding your source systems deeply enough to model them and knowing which parts of the platform are genuinely worth building yourself.

For some organizations, building is exactly right, and for others it quietly consumes the very capacity it was meant to create. The questions below are designed to help you decide whether building your own data platform honestly makes sense.

1. What problem are we actually trying to solve? 

Better reporting, self-service analytics, system consolidation, AI readiness, and less manual effort are all legitimate goals, but they lead to very different platforms. Be specific before you build. Technology should serve a business objective, not quietly become one.

2. Is this a strategic differentiator? 

Would building your own data platform create a genuine competitive advantage, or are you recreating capabilities that already exist elsewhere? Invest engineering effort where your business is genuinely unique and buy the rest.

3. Do we truly understand our source systems? 

For ERP platforms like Yardi, the schema, relationships, business rules, and historical quirks represent years of accumulated knowledge. This is where most build projects underestimate the effort — not in the pipelines, but in knowing what the data actually means. A pipeline that moves misunderstood data faster is not progress.

4. Have we weighed the lifetime cost? 

Initial development is a fraction of the story. Building carries ongoing maintenance, upgrades, security, monitoring, documentation, testing, governance and support. But buying is not cost-free either. There are license fees that compound annually, dependence on a vendor’s roadmap, potential ceilings on customization, and switching costs if the relationship doesn’t deliver. A fair comparison puts both ledgers side by side. Whichever route you choose will be with you for years.

5. Who will own the platform? 

Successful platforms need clear ownership across architecture, data quality, security, change management, support, and business engagement. This matters whether you build or buy. A purchased platform with no internal owner drifts just as badly as a bespoke one. Decide who is accountable before anything goes live.

6. What happens when the person who built it leaves? 

Many internally built platforms rest on one or two individuals who hold the whole design in their heads. When they leave, the knowledge leaves with them. Institutional knowledge belongs in documentation, not in people. If your platform can’t survive a resignation, it isn’t finished.

7. How quickly do we need value?

If the board needs credible executive reporting in weeks, then a multi-year build program answers a different question. Speed to value is a legitimate driver in its own right, and it often points toward buying a foundation now and building selectively later.

8. How much customization do we actually need?

Every organization believes it’s different, and in some respects every organization is. But the difference isn’t uniform. Most platforms are 90% standard and 10% genuinely distinctive. Knowing where standardization is acceptable is one of the highest-leverage cost decisions you can make.

9. How will we integrate what comes next? 

Today’s platform will need to absorb tomorrow’s systems: CRM, market data, ESG, AI, external benchmarking, and more. Design for the systems you don’t have yet, not just the ones you do. Extensibility is worth more than any single feature you build on day one.

10. Will this accelerate innovation or absorb it? 

This is the question running beneath all the others. The honest answer isn’t build vs. buy; it’s where your best engineers should be spending their time. Buying doesn’t make data ownership, integration, or governance disappear. Rather, it relocates that work so your team can focus its energy on the problems only your business can solve.

Key Takeaways for Building Your Own Data Platform

For most organizations, the real answer isn’t build or buy — it’s both. Buy the foundation that is already done well and allows you to add the thin layer that’s genuinely yours on top of it. Building isn’t inherently good or bad. The best decision is the one that matches your capabilities, your priorities and your long-term strategy, and that is honest about the costs on both sides of the line.

Ready to learn more about build vs. buy? Check out Modern Data, Old Debate: Build vs. Buy Your Data Stack.