For a lot of partners building data platforms, the bottleneck isn't ambition or budget. It's how long it takes to turn raw data into something a client can actually trust and use.
That's the pattern Daniel Verbrugge kept running into. As a Timextender Expert on the Wortell Smart team, he builds cloud-based data platforms for clients so they can get the best possible results out of their reporting. Before Timextender, getting to that point meant building the same foundation from scratch every time.
"Before Timextender the biggest challenge we were facing was actually coding everything by hand," Daniel says. He saw the same pattern across most companies: teams kept building their own engines to move data from one place to another, then building metadata around it, then setting up tests to make sure it held up.
None of that groundwork carried over between projects. Every new client meant starting the engine-building process again.
"With Timextender it's so much easier to get the data from A to B, you just click and drag or with slight tweaks, you can get the results so much quicker." - Daniel Verbrugge
The hand-coding itself wasn't what pushed Wortell to change. It was how long that work kept data out of the hands of the people who actually needed it. Daniel points to time to market as the trigger, describing teams that struggled to get data to the people who needed it daily, which turned into multiple sprints just to get there.
With Timextender, that timeline changed. What used to take multiple sprints now takes a few weeks.
"Now with Timextender, within 2 or 3 weeks, we were getting everything out there, getting all the data tested, getting it AI ready." - Daniel Verbrugge
He's also seen agents put to work directly on the data once it's ready, so the people who need it can use it right away.
Wortell evaluated other options before settling on Timextender, and the deciding factor was how much of the process the platform covers on its own.
"We chose Timextender because it's one unified platform from ingestion to delivery, getting it into the MCP server, making sure that all the semantic models for Power BI are ready and good." - Daniel Verbrugge
For Daniel, avoiding tool-switching was as important as any single feature. "Being able to do everything from one tool is so much better and so much easier than having to learn all the different tools, getting tool A ready before it can finally go into tool B," he says. "It's an end-to-end solution for getting the data as quickly for the people who need it as possible."
That shift showed up immediately in Daniel's own work.
"My first win was building my first model within 2 to 3 days instead of 2 to 3 sprints" - Daniel Verbrugge
The bigger change, he says, was what happened after that first model. Facts and dimensions built once became immediately reusable in the models that came next, which changed how his clients were used to working. "I had to rerun all this data, recreate certain views every time we wanted a new Power BI model or a new insight" Daniel says. With Timextender, that rework disappeared as long as the data was modelled correctly the first time.
For Daniel, dimensional modelling is what makes that reusability possible, and it's also what changed how reliable the resulting data is. Instead of scripts branching out in different directions to solve the same problem multiple ways, Wortell now builds toward a single, trusted version of each table.
"We have one script. It delivers one table and all the logic, all the facts are right in this table" - Daniel Verbrugge
That matters most once the data reaches the business. "For the business, they need to know that whatever we put out is correct, is 100% the way it should be, and it should be like that every day, even after releases or after other business units want this data too," Daniel says. Different teams across a client's organization need to be looking at the same numbers, and a single, well-modelled source of truth is what makes that possible.
Waternet, a large water utility in the Netherlands, is a concrete example of that reliability at work. Waternet needed to phase out its legacy environment and replace it with something that fit its existing Azure data infrastructure, built models faster, and kept costs down while leaving room for a future move to SaaS. Working with Wortell Smart, Waternet chose Timextender.
Since then, Wortell has trained 12 people at Waternet on the platform, spreading data platform work that used to sit with only a few people. New requests from the business now come back in days or weeks instead of months, and Waternet has run into fewer scheduling issues while maintaining its data infrastructure.
Floris van der Zwaard, a Solutions Architect at Waternet, describes the practical difference this way:
"With Timextender we now have a single point where we transfer the data to make it report ready. The value was that a functional user can use the tool without too much technical knowledge, programming and scripting to get the data report ready." - Floris van der Zwaard
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Wortell is one of many partners who use Timextender to replace hand-coded data engines with a single platform that takes clients from ingestion to insight in days instead of sprints. If your team is still rebuilding the same data foundation by hand for every new client, find out what it takes to become a Timextender partner. Learn more →