Data warehouses have long been the default for consolidating and storing business data, but they’re increasingly being replaced by more flexible and cost-efficient data lakes and lakehouses. This shift isn’t just a technology trend—it’s a strategic move that can dramatically accelerate data consolidation and integration, especially for mid-market companies pursuing buy-and-build strategies.
If you’d prefer to explore this topic in more depth, we also recorded a podcast you can watch or listen to here.
Faster Data Access and Integration
The data landscape has changed significantly over the past few years, driven by advances in data lake storage, modern pipeline tooling, and automation. Tools like ChatGPT and large language model (LLM)–assisted development have further reduced the time required to build and deploy data pipelines.
Unlike traditional data warehouse implementations—which often take weeks or months—data lakes can be operational in hours or days. That speed is especially valuable for executives at rapid-growth platform companies and private equity operating partners who need fast visibility into newly acquired portfolio company data.
Cost-Effective Performance for Buy-and-Build Strategies
Historically, companies looking to consolidate acquisition data were forced to choose between three imperfect options:
- Investing months and significant capital in a traditional data warehouse build
- Paying ongoing licensing costs for tools like Fivetran or Talend to accelerate ingestion
- Waiting for full ERP and system migrations at the acquired company
Each approach carried tradeoffs—long timelines, high recurring costs tied to data volume, or operational risk from delayed ERP implementations.
Data lakes change that equation. They enable integration of newly acquired company data in days, often at minimal transfer and storage cost. We explore this in more detail in our episode Demystifying Microsoft Fabric and OneLake, including how modern pricing models make large-scale data consolidation far more economical.
This rapid integration provides leadership teams and boards with immediate visibility—eliminating the need to “fly blind” during critical post-acquisition periods.
By moving away from lengthy, expensive warehouse projects and toward agile, scalable data lakes and lakehouses, mid-market and private equity–backed companies gain a clear competitive advantage: faster insight, lower cost, and the flexibility to scale alongside growth.
To learn more, watch this short overview: What is a data lakehouse?
