We sat down for a quick chat with Yucel Yuksel, a Chief Data and AI Executive with 20 years of data and digital transformation experience, to find out how he approaches cloud migrations to drive technology sustainability.

With a knack for driving transformation through two global cloud migrations, a passion for data governance, and proven success in articulating the value of data management, Yucel is a key player in the field.

What Are the Key Drivers for Migrating to the Cloud from a Data Perspective?

In the past, data strategy was often overlooked even in large companies because data teams were perceived as a support function. That is why many organisations failed to generate high ROI from these investments.

There was also another root cause: the focus areas of data leaders such as infrastructure, delivery and data modelling. There is a chicken and egg relationship between the positioning of data leaders and their focus.

Without strong governance, self-service analytics resulted in hundreds of similar and inconsistent reports throughout the organisation.

Another improvement area was enterprise data modelling. Because data teams were often perceived as a cost centre and lacked business value focused prioritisation, they delivered requests as quickly as possible without seeing the bigger picture.

In one of my previous companies, I discovered that the objective of some reports was simply to support the bonus calculation of an employee who had a good relationship with the data team.

Communication between technical teams and stakeholders also needs improvement in many organisations. Often there are no clearly defined processes or roles for data ownership and responsibility.

To overcome this rigidity, companies were forced to develop or hand-code user business intelligence. Over time these reports become inaccurate as internal systems change, and it becomes unsustainable for data teams to manually update potentially thousands of reports.

It is the unpicking of these thousands, if not millions, of lines of custom code that can make cloud migrations daunting.

For example, if a newly onboarded executive introduces new KPIs, there is no guarantee that an existing custom-coded report will support those metrics. Creating a new report could take days or weeks depending on the complexity of the business logic and the data model built across multiple source systems.

Multiply that by hundreds of stakeholders across departments and geographies, and it becomes clear why this approach cannot be sustained without an overarching strategy.

To resolve these issues, companies need experienced and visionary data leaders who can:

What Were the Main Benefits of the Two Global Azure Migrations You Led?

Future expandability is one of the biggest advantages.

In principle, the modern data stack can be supplemented at any time with services from Azure. It provides the interfaces needed to integrate new data sources easily, including standard connectors for third-party technologies.

Another major benefit, which many people overlook, is increased security.

Establishing key user groups, communities, and a dedicated portal for end users were also significant milestones for enabling self-service analytics.

From a business perspective, the company-wide analytics platform generated very positive feedback. A reliable, integrated database was created that allows stakeholders to make fact-based decisions across the organisation and strengthen customer relationships.

It also became clear that we could implement data-driven requirements faster and more efficiently.

The next step was implementing real-time monitoring of machine data to further optimise production processes and capacity planning.

What Is the Biggest Challenge in Cloud Migration?

Although the people side of the story is pivotal, the technical architecture must also ensure scalability and easy connection of new data sources.

The goal of cloud migration was not only to create a foundation for consistent and high-performance analytics across subsidiaries, but also to enable digital use cases involving different types, formats and velocities of data.

The biggest challenge in these projects is managing:

Can It Really Take Days or Weeks to Create a Single Report?

Yes.

Imagine being asked to produce a report for a new C-level executive. You open an existing report that was poorly designed due to inefficient request management and time pressure.

There may be thousands of lines of code with no documentation or comments. The only person who understood the system may have already left the company.

This can easily turn into a nightmare for new team members and create significant frustration.

Given that data engineers often move roles every two years, it becomes difficult for newcomers to navigate complex codebases.

That is why data leaders must prioritise sustainability in talent management. This includes:

How Well Do You Sleep at Night?

Thanks to medicines, lol 😊

Despite the challenges, there are opportunities for improvement.

Establishing effective monitoring mechanisms and SLAs can be very helpful. Root cause analysis and transparent communication with stakeholders also make a significant difference.

Migrating to the cloud offers an opportunity not only to fix existing issues but also to modernise processes and systems for long-term sustainability.

As an optimist, I believe that while the departure of a key team member can be disruptive, it can also act as a catalyst for innovation and strategic planning.

What Challenges Appear After Moving from Legacy Systems to a Modern Data Stack?

When I joined one of my employers, we were using a BI tool that frequently produced inaccurate reports. After due diligence, the company decided to migrate to Power BI to resolve multiple issues.

This brought us to a position that was good, but not great.

You might think that adding more data resources would solve the problem. However, it is never that simple.

Without:

it does not matter how many data resources you have. You will still be fighting against an error-prone dataset that is costly and difficult to maintain.

The Three Foundations of Successful Business Intelligence

True and trusted business intelligence must start with Ownership.

Ownership of systems, processes and reporting standards. Only with clear ownership can BI be configured in a future-facing and commercially meaningful way.

However, when multiple stakeholders all have different ways of working and little appetite for change, progress becomes extremely difficult.

After ownership comes Awareness.

This is the “why”. Without awareness it is difficult to win the hearts and minds of stakeholders. If a company wants to become data-driven, stakeholders must understand that data structures must evolve.

Therefore data leaders must also have strong business communication skills, not just technical expertise.

The final element is Data Literacy.

Data literacy is the ability to explore, understand and communicate using data. This is fundamentally a change management task rather than simply a Power BI training exercise.

The objective is to expand user groups and enable employees across the organisation to work confidently with data.

Finding data champions who can spread the data strategy internally is often a good starting point.

Ultimately, the success of any data initiative depends on a holistic approach built on:

Without senior leadership support, initiatives to improve business intelligence and adopt new technologies may struggle to gain traction.

Advice for Data Leaders Navigating Cloud Migrations

Change management is a crucial element that should never be overlooked.

Employees must be supported in adapting to new processes and technologies. However, many data teams lack dedicated resources for change management.

Collaboration with HR and internal communications can help, but these teams are often focused on other priorities.

Without structured change management, even well-designed cloud migration initiatives can struggle to succeed.

Important activities include:

Cloud migration is not only about technology. It is about shifting mindsets and behaviours to unlock the value of modern data platforms.

Summary

Yucel Yuksel’s experience highlights both the complexity and the opportunity involved in moving from legacy systems to cloud-based data environments.

Legacy systems often create rigid structures, fragmented reporting and unsustainable maintenance requirements. Migrating to the cloud offers a chance to modernise infrastructure and improve long-term sustainability.

However, the success of these initiatives depends on more than technology. Ownership, awareness and data literacy are critical foundations for any data-driven organisation.

With strong leadership, effective change management and clear communication across the business, organisations can maximise the value of cloud migration and build more resilient, insight-driven operations.