From fragmented BI to a unified, AI-native data foundation

SixValues is a B2B company with a team of over 300 people, helping multiple iGaming brands across markets and products, operating in an environment where speed of decision-making, consistency of KPIs and cross-team alignment directly impact performance.

As the organisation grew, its data stack, built primarily around Tableau, began to show structural limitations that affected not just reporting, but the way teams interacted with data on a daily basis.

The transition to Gamblitude introduced a unified data layer, governed metrics and real-time access to information, fundamentally changing how data is used across the company.

As SixValues expanded its portfolio and internal teams, its Tableau-based setup gradually evolved into a complex reporting environment with multiple layers of logic, duplicated KPI definitions and increasing dependency on the data team.

While dashboards provided visibility, the underlying structure made it difficult to ensure consistency across teams, especially when different stakeholders relied on slightly different versions of the same metrics.

Over time, several key challenges became apparent:

This resulted in a situation where data was available, but not truly usable at scale.

SixValues decided to move away from a Tableau-based reporting model and build its data layer on top of Gamblitude, focusing on three key principles:

The implementation included:

The platform was adopted progressively across departments, starting with core teams and expanding to the wider organisation.

“What we were missing was not more dashboards, but confidence in the numbers and the ability to access them without friction. Once we standardised definitions and removed the dependency on ad-hoc reporting, the entire organisation started to move differently.”

Angeliki Kiakotou HEAD OF BI & ANALYTICS, SIXVALUES

“When access to data and insights is no longer limited to a small group, the entire organisation starts to operate differently. People don’t wait, they explore, validate and act on their own. That’s where you see the real shift in speed and decision quality.”

Wojtek Sznapka CEO, GAMBLITUDE

The impact of the transition was visible both in quantitative improvements and in how teams worked with data day to day.

“The biggest change was not technical, but behavioural. People stopped waiting and started exploring. That alone unlocked a level of speed we hadn’t experienced before.”

Angeliki Kiakotou HEAD OF BI & ANALYTICS, SIXVALUES

“Removing the bottleneck around data access has a double effect: the organisation becomes more independent, and the data team can finally focus on work that compounds over time. That’s when you start to see real acceleration.”

Wojtek Sznapka CEO, GAMBLITUDE

One of the key concerns in any transition away from a familiar BI setup is how quickly teams are able to adapt to a new way of working with data. In the case of SixValues, adoption happened noticeably faster than expected.

Initial onboarding required minimal structured training, with most users able to start exploring data and building their own views within the first days of access. The platform’s no-code interface and consistent metric definitions reduced the learning curve, allowing teams to focus on their use cases rather than on understanding the tool itself.

This rapid adoption significantly reduced the time between platform rollout and tangible business impact, while also increasing confidence in using data independently across the organisation.

Beyond measurable improvements, the most meaningful change was structural. With direct access to governed data and consistent metrics, all teams were able to move from a reporting-driven workflow to a decision-driven one, where data is available at the moment it is needed rather than prepared on request.

At the same time, the data team transitioned from a reactive support function into a high-leverage unit focused on building models, improving data quality and driving long-term value.

This dual shift created a compounding effect across the organisation, increasing speed, alignment and overall efficiency.

One of the more interesting observations during the rollout was how user behaviour evolved in the first weeks.

Initially, many teams approached Gamblitude in the same way they had been using Tableau, relying primarily on dashboards as the main interface for interacting with data. This was a natural starting point, given their previous experience and habits. However, this pattern changed quickly.

As users became more familiar with the platform, they began to understand that the interaction model was fundamentally different, designed not only around static dashboards, but around direct exploration and conversational access to data.

The number of interactions with the AI Agent grew rapidly week over week, with more users moving away from passive consumption of reports towards active, on-demand analysis. Teams that had previously relied on a small number of predefined dashboards started to explore data independently, ask follow-up questions and iterate in real time.

This behavioural shift resulted in a noticeable increase in engagement across the organisation, with a broader group of users becoming active participants in data-driven decision-making rather than consumers of prepared insights.

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