Go to storiesofdata.com homepage
Open toolbar
Over the past two decades, our client, a Swedish tech company, has been helping multi-location brands and franchises with their digital SaaS tool. The company simplifies operations by effectively managing manuals, checklists, audits, and communication across all franchises for its clients. Recently, they faced a significant challenge that came out as a simple request by their users and was followed by a bigger challenge from their biggest client. This case study explores how Datanauts helped them address the issue and turned it into an opportunity for the platform’s success.
The Users of the platform requested easily accessible insights into their data presented in a visual format. However, the platform's current setup with its API didn't provide the user-friendly visuals they needed.
Complicating matters, their biggest client required insights on data that sits outside the platform
So, we had two challenges:
1. Making data visuals user-friendly within the platform
2. Figuring out a solution to show insights beyond the platform's usual data.
For the client:
For the platform:
In addressing the challenge, we carefully examined the requirements, taking into account both the major client and the various needs of all platform users. Crucially, we didn't go at it alone. We collaborated with one of their engineers to make sure everything was in sync.
To execute the solution, we used these resources:
This collaboration and open talks with both clients and engineers helped us navigate the challenge successfully.
After understanding what both clients and the platform needed, we came up with what we believed to be the best solution for this particular case.
“We decided to create an embedded dashboard distributed through the platform to all the users of the client.”
To make it happen, we used the Extract, Transform, Load (ETL) process with Power BI to create a customized dashboard. It was a simple process that involved understanding API endpoints and data structure.
This method ensured a solution that was easy to use and visually intuitive, meeting the goals of both clients and the platform.
So, those fancy dashboards we thought were a win? Turns out, ensuring the right data reaches the right people among their 100+ users was trickier than expected.
The real challenge? Ensuring each logged-in user sees precisely what they need on the dashboard. And, of course, keeping everything secure.
After lots of digging and trying different things, we solved the problem with these two ways:
First, we used a low-code platform as the bridge connecting the platform to the Power BI dashboard. (A safer approach than using “publish to web” iframe.)
Second, with the help of iframes, we could filter our data in Power BI Embedded and show each user exactly what they needed.
This not only saved us but completed our solution. Now, with one secure and smartly set-up report, our platform lets over 100 users access external data effortlessly.
Wins for the Platform:
Wins for the Client:
By developing this, we proved and tested a solution that could be expanded to all their +100 clients with marginal changes. This means that in a matter of weeks, the platform can offer modern, fast, and secure analytics to all its clients with minimal involvement from their engineering teams.
In this section, we dive into the technical challenges we faced and explain how we solved them. The platform users requested easily accessible insights into their data presented in a visual format. However, the platform's current setup with its API didn't provide the user-friendly visuals they needed.
Complicating matters, their biggest client required insights on data that sits outside the platform.
So, we had two challenges:
1. Making data visuals user-friendly within the platform
2. Figuring out a solution to show insights beyond the platform's usual data.
In addressing the challenge, we carefully examined the requirements and found that the technical implementation of the solution required two main technologies:
In order to provide the solution, we had the following resources:
This collaboration and open talks with both clients and engineers helped us navigate the challenge successfully.
After assessing all the details and requirements, we came up with what we believed to be the best solution for this particular case.
“We decided to create an embedded dashboard distributed through the platform to all the users of the client.”
Access to client data enabled a smooth ETL process to build the needed Power BI dashboard. It wasn't overly complex; we just had to grasp API endpoints and data structure with a helpful nudge from one of the platform's engineers.
With the WYSIWYG editor, embedding a Power BI iframe using the "publish to web" approach was a breeze.
However, there was a risk with the "publish to web" approach.
A “publish to web” iframe can be copied and shared with bad actors, threatening the security of the platform.
So the big question was:
“How do we make sure each of our 100+ users sees exactly what they need on the dashboard while keeping it secure from unwanted eyes?”
In technical language, our challenge was, “How do we bridge the gap between the platform and the BI engine?
Since we couldn't access the platform's code, the usual method of coding to customize the dashboard was off the table. This tricky challenge needed a creative approach to connect the platform and the BI engine smoothly.
Fortunately, we had prior experience with Power BI Embedded – which led us on the right track and showed us the way.
The solution lies in using a low-code platform as the bridge connecting the platform to the Power BI dashboard.
Our strategy involved programmatically embedding the Power BI iframe within the low-code platform and then embedding the iframe from the low-code platform onto the main platform.
This approach granted us the flexibility within the low-code platform to modify the dashboard's behavior easily as needed.
As we moved ahead with our strategy to connect the platform and Power BI dashboard through a low-code platform …a final and crucial hurdle loomed. :(
How do we pass the logged-in user to the dashboard as a filter?
Without this, the bridge had a gaping hole that would keep the platform and dashboard separated, making the entire solution useless.
After some trial and error, we found a crucial method: extracting the logged-in user's information from the platform and seamlessly passing it as a variable from the low-code iframe to the Power BI iframe.
Surprisingly, iframes can do some pretty neat stuff!
This trick was a game-changer. Now, armed with the user's name, we could filter our data in Power BI Embedded and show each user exactly what they needed.
Our solution was a success. We planted a secure, smart report right into the platform, letting over 100 users easily access external data when they needed it.
Check out the full architecture diagram here.
In the end, both the client and the platform are thrilled with the result of using our solution for nearly two years. We accomplished the goals efficiently, requiring minimal support (2-3 hours from one engineer) and significantly lower costs than traditional platforms.
What's even better is that our solution turned out to be more potent than we initially thought, proving its mettle in a live environment.
By developing this, we proved and tested a solution that could be expanded to all their +100 clients with marginal changes. This means that in a matter of weeks, the platform can offer modern, fast, and secure analytics to all its clients with minimal involvement from their engineering teams.
