Managed data
What is Data as a Service (DaaS) and why it matters
A clear definition of Data as a Service (DaaS): what it includes, how it differs from building your own infrastructure and why more companies adopt it.
Read articleKey takeaways
- Groups with several entities suffer fragmented data and differing criteria.
- Unifying enables a consolidated view of profitability and the business.
- The challenge is not only technical: criteria, currencies and charts of accounts must be harmonised.
- A managed data layer consolidates without forcing each company to change systems.
- Normalise before summing, or consolidated figures mislead.
Corporate groups with several entities share a common pain: each company has its own systems, criteria and formats, and consolidating group information becomes a quarterly nightmare. Unifying multi-company data solves this at the root.
Why consolidation is hard
- Different systems: each entity may use its own ERP or CRM.
- Different criteria: what one calls "margin" another calculates differently.
- Heterogeneous formats: currencies, charts of accounts, naming.
- Timing: each company closes on its own schedule.
What unifying really means
It is not just putting data in one place: it is harmonising criteria so figures are comparable. Once normalised, you see profitability, liquidity or debt of the group and each entity in a single, coherent view. Summing without normalising produces figures that look consolidated but mislead.
Entities
Own systems
Data layer
Normalise criteriacurrencies, accounts
Group
Single view
Without breaking the systems
The key is not to force each company to change. A managed data layer connects to each entity’s systems, replicates what is needed, normalises criteria and delivers consolidated reporting, also handling intercompany operations so internal sales are not counted twice.
Each entity keeps its systems; the group gains a single, reliable view of the business.
In summary
Unifying multi-company data is not joining tables but harmonising criteria, currencies and charts of accounts so figures are comparable. A managed data layer does it without forcing system changes — connecting, normalising, consolidating and handling intercompany — to deliver one reliable group view.
Sources & further reading
Frequently asked questions
Do all companies have to use the same ERP?
No. Each entity’s systems are connected as they are and the data is normalised to make it comparable.
How are differing criteria resolved?
By defining common business rules in the data layer, so each metric is calculated consistently across the whole group.
Is it useful for financial consolidation?
Yes, it is one of the most common use cases: consolidated and per-entity profitability, liquidity, debt and margins.
What about different currencies and charts of accounts?
A data layer converts, harmonises and aligns them before summing, and handles intercompany operations to avoid double-counting.
Can each company see only its data?
Yes. Role- and entity-based access control ensures each company sees its own data and the parent the consolidated view.
How long to get the consolidated view?
With a use-case approach, a first consolidated view of key metrics is usually ready in weeks, expanding afterwards.
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.