Monday starts with manual exports
Before any analysis happens, someone spends half a day pulling CSVs from five different systems.
Data & Analytics
Reporting takes days of spreadsheet wrangling
Your weekly or monthly numbers mean pulling exports from five systems, patching them together by hand, and hoping the formulas didn't break since last time.
Sound familiar?
The signs usually show up in day-to-day work long before anyone names the problem.
One person is the only one who can build it
The output depends on a spreadsheet only one analyst fully understands.
The numbers are already stale by delivery
By the time the figures reach leadership, the underlying data has moved on.
A new question means starting over
Someone asks for the numbers cut a different way, and the whole spreadsheet gets rebuilt from scratch.
Manual extraction
The work hasn't started, and the day already has
Each source system needs its own export, its own cleanup, and its own quirks remembered from last time. None of it is analysis, it's just getting the data into one place, and it happens again next cycle.
The root cause
Why it happens
This usually starts as a reasonable shortcut: a spreadsheet gets the first set of numbers out the door fast. But as the business adds systems and the cadence tightens, that spreadsheet never gets replaced, it just gets more formulas bolted on. There's no pipeline moving data automatically, no shared model to build from, and no one has had the time to step back and fix the root cause while the next cycle is already due. Left alone, the cost compounds:
01
Skilled analysts spend most of their week on data entry instead of analysis.
02
Delivery cadence is capped by how fast one person can manually rebuild a workbook.
03
Finance and ops can't move to faster decision cycles because the process itself is the bottleneck.
How Airodevs solves it
From the problem to working software.
Automate the pipeline
We replace manual exports with ETL/ELT pipelines that pull, transform, and load your data on a schedule, handling schema changes and failures without someone babysitting it.
Build a shared data model
Instead of one spreadsheet per question, we architect a warehouse modelled around the questions your business actually asks.
Stand up self-serve dashboards
Dashboards replace rebuilt spreadsheets, so a new cut of the data is a filter, not a week of work.
Free your analysts for analysis
With extraction and modelling automated, your team's time shifts from data wrangling to the decisions the data is actually for.
What changes
Before and after.
What day-to-day work looks like once the fix is in place.
Before
After
01
- Days spent manually pulling and patching exports each cycle
- Pipelines run on a schedule with no manual intervention
02
- One analyst is the single point of failure for every cycle
- A shared model anyone on the team can build from
03
- Numbers are stale by the time they ship
- Output reflects data on a reliable, automated refresh
04
- A new question means rebuilding the spreadsheet
- A new question means a new view on existing, modelled data
FAQ
Questions teams ask before they commit.
Ready to stop rebuilding the same workbook every week?
Tell us what goes into your current process, and we'll show you what automating it would look like.