Comparisons
Data Layer vs. building your own data lake (2026)
An honest comparison of building your own data lake versus using Data Layer: cost, time, risk and outcome for leadership. Data Layer comes out on top.
Read articleKey takeaways
- A BI consultancy delivers projects; a managed service delivers results and maintains them.
- The hourly model makes cost hard to predict.
- After the project, the solution is often left without maintenance.
- Data Layer combines platform, team and continuous maintenance with pay-per-use.
- For a living data capability, a managed service fits better.
When a company wants to exploit its data, a common option is to hire a BI consultancy. It is a valid route, but it helps to understand how it differs from a managed data service, because the model shapes cost and long-term sustainability.
The two models
A BI consultancy executes a project with a defined scope and timeline. A managed service like Data Layer delivers data results and operates and evolves them continuously, with platform and team included.
| Criterion | BI consultancy | Data Layer |
|---|---|---|
| Model | One-off project | Continuous service |
| Cost | ✗ Hourly, hard to predict | ✓ Consumption, predictable |
| Maintenance | ✗ Ends with the project | ✓ Included |
| Time to result | Medium | ✓ Weeks |
| Infrastructure | You provide it | ✓ Managed, in Europe |
| Evolution | New project each time | ✓ Continuous improvement |
The problem of the project that ends
The biggest risk of the consultancy model is not cost, but what happens afterwards: when the project ends, the solution is left without maintenance. Sources change, pipelines break, and without a team to care for them, the investment degrades. Reactivating it usually means a new project and a new invoice.
A consultancy delivers a project; a managed service delivers a capability that lives, is maintained and grows.
Where each fits
A consultancy can suit a one-off analysis or a tightly scoped project. For a living data capability — one that evolves, is maintained and grows with the business — a managed service fits better: it combines platform, European infrastructure and an expert team with predictable cost, without the "day after" gap.
In summary
A BI consultancy bills hours for a one-off project that often ends without maintenance. Data Layer delivers data results as a continuous service, with platform, team and maintenance included and predictable consumption-based cost. For a data capability that must live and grow, the managed model wins.
Sources & further reading
Frequently asked questions
Is a BI consultancy useless?
It suits one-off analyses or tightly scoped projects. For a continuous data capability that evolves and is maintained, a managed service usually fits better.
What is the biggest risk of the consultancy model?
The "day after": when the project ends, the solution is left without maintenance and degrades, forcing new projects to reactivate it.
Why is Data Layer’s cost more predictable?
Because it is based on real consumption and includes platform, team and maintenance, instead of billing hard-to-estimate project hours.
Can I use both?
Yes. A consultancy can handle a one-off strategic analysis while a managed service runs the continuous data capability. They are not mutually exclusive.
What happens to a consultancy solution over time?
Without maintenance it degrades: sources change and pipelines break. A managed service keeps it running and evolving as part of the offering.
Does the managed model lock me in?
No. You keep ownership and portability of your data and results; the value is in continuous delivery, not in trapping the client.
Turn this data into results
Tell us what you want to achieve. Data Layer connects, processes and delivers the result up and running, with no infrastructure for you to manage.