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 SaaS BI tool visualises data; a DaaS service prepares and delivers it.
- BI needs clean, connected data to be useful.
- DaaS solves the layer BI takes for granted.
- They are often complementary: DaaS feeds the BI tool.
- The question is not "BI or DaaS" but "who prepares the data my BI needs?".
It is a common confusion: "we already have a BI tool, why do we need a data service?". The answer lies in understanding what each solves, because they operate in different layers and, in fact, usually complement each other.
The two layers
A SaaS BI tool visualises and explores data in dashboards. A Data as a Service offering handles the prior layer: connecting, integrating, cleaning and preparing the data the BI consumes.
| Aspect | SaaS BI tool | Data as a Service |
|---|---|---|
| What it does | Visualises data | Connects & prepares data |
| Layer | Consumption (front-end) | Data (back-end) |
| Prerequisite | Clean, connected data | — |
| Team | Used by the analyst | Includes expert team |
| On its own | Limited if data is scattered | Delivers data ready for BI/API/AI |
The common misunderstanding
BI assumes the data is already clean, integrated and available. In practice that assumption rarely holds: that is why many BI projects disappoint — not because of the tool, but because underneath there is scattered, unreliable data. BI shines when it rests on a good data layer.
Sources
ERP, CRMfiles, APIs
DaaS
ConnectClean, govern
BI tool
VisualiseDashboards
Complementary, not exclusive
It is not about choosing one or the other. A DaaS service prepares and delivers reliable data; a BI tool visualises it. In fact, DaaS can feed the BI tool you already use, as well as APIs, datasets or AI.
The question is not "BI or DaaS", but "who prepares the data my BI needs?".
In summary
A SaaS BI tool visualises data; a DaaS service prepares and delivers it. BI disappoints when the data underneath is scattered and unreliable — a data problem, not a tool problem. The two are complementary: DaaS solves the data layer and feeds the BI you already use.
Sources & further reading
Frequently asked questions
Does a DaaS service replace my BI tool?
No. They operate in different layers: DaaS prepares and delivers the data; BI visualises it. DaaS can in fact feed the BI you already use.
Why do some BI projects disappoint?
Usually not because of the tool, but because the data underneath is scattered and unreliable. BI shines on a good data layer.
Do I need both?
Usually that is ideal: DaaS solves the data layer and BI the visualisation. They are complementary.
What does DaaS add that BI lacks?
Connecting, integrating, cleaning and governing the data — the back-end layer BI assumes already exists but rarely does.
Can DaaS feed tools other than BI?
Yes. The same prepared data layer can feed BI dashboards, APIs, datasets and AI models.
Is BI useless without DaaS?
Not useless, but limited if data is scattered. BI delivers its full value when it rests on a reliable, prepared data layer.
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.