When BI projects start, it usually begins with one question: “How do we get the data in?”. Then come weeks (or months) of talks with system vendors, data specs, API documentation, limited access – and often a consultant report that ends with: “it’s doable, but...”. In Homepal, it’s different. We don’t start with the data source – we start with the business need.
From system integration to ready-to-use logic
To us, an integration isn’t just a connection to a database. It’s a promise:
- that the data comes in
- that it has the right structure
- that it matches our data model
- that it works no matter what system the customer uses
We’ve built ready-made, robust integrations with the most widely used systems in the real estate industry – and we know exactly which fields are needed for every KPI, every table, every filter.
Data is only valuable if it’s ready to use
A traditional BI delivery often gives you “raw data in place.” But having a database is not the same as having a solution.
That’s why we have:
- defined all tables and fields needed for each feature
- ensured mapping across different systems
- built support for adding custom logic (e.g. blocking reasons, contract statuses) – without losing KPI compatibility
We don’t just make data available. We make it usable.
Result: Simple for the customer. Smart behind the scenes.
The customer says: “I want to see how many units were blocked for repairs during Q4.”
Homepal says: “Here you go.”
We’ve already:
- pulled the block data from the correct table
- interpreted the field for block reason
- linked it to the unit entity
- filtered out incorrect or duplicate rows
- counted unique units
- visualized it in the interface
That’s why our customers never have to ask: “Is it possible to get that?”
We’ve already done the work – so you don’t have to
We’ve spent thousands of hours understanding every system, every data source, and every customer’s way of working. We’ve already built, tested, documented, and productized integrations that would otherwise take weeks to get in place.
Next up we’ll share how our data model makes “it’s not possible” almost never the answer:
