Achieving Excellence in Data Governance

Edita Lukaseviciute has been an instrumental figure in implementing the data governance framework at the Bank of Lithuania. In her daily work, she draws inspiration from data and digitalization and focuses on teamwork.

In an interview with CIOReview, Lukaseviciute shares insights on her professional journey in the data governance space, focusing on skill development, technological advancements and challenges in adopting new data management technologies.

Professional Journey and Key Experiences

My professional journey at the Bank of Lithuania started as a statistician working on unaccredited data and the national credit register transformation project. The main goal was to collect granular data from financial market participants and use it to evaluate creditworthiness and gain economic insights for financial stability.

When the Bank of Lithuania’s data management and data governance program was initiated, I was appointed as the project manager of the data governance transformation project. I eventually became the head of the organization’s data governance division. During my journey, I developed the ability to see the complete picture of the data within the organization and delve deeper into it for analysis. I learned how to use data to create more value and identify best practices for effective data management.

Trends and Technology Advancements in the Banking Sector

Every industry is shifting from old legacy systems to new technologies like data lakes. At the Bank of Lithuania, we have built our data lake and are implementing a data mesh approach with a centralized infrastructure for data management. This highlights centralizing competencies, infrastructure and governance standards while enabling a self-service culture for analytics in business units.

color:#0E101A”>“At the Bank of Lithuania, we have built our data lake and are implementing a data mesh approach with a centralized infrastructure for data management.”
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Another emerging trend is generative AI. We are progressively advancing towards implementing the technology in our daily work, and in the coming years, it will be imperative for all business processes.

Challenges in Adopting Emerging Technologies

The main challenge in adopting new technologies is the human component. Often, people may not be inclined toward new technologies. They can be resistant to change or may fear how it will impact their work. The challenge lies in communicating with them and explaining why changes are necessary. Leaders need to take the initiative and demonstrate how new technologies can make their job easier and more efficient. Holding regular meetings to present ongoing changes and plans is key. We adhere to the data mesh principle and have virtual product teams comprising members from IT, data and business departments who work collaboratively through all the changes. We provide mentors in the data and IT departments who help employees with daily tasks and new tools.

Ensuring Effective Data Governance

My division focuses on defining standards and processes for data management at the Bank of Lithuania. We monitor processes and analyze how they work in reality. We use dashboards to track key performance indicators (KPI) annually and conduct surveys to gather feedback from data users. This helps us improve our processes and data governance functions.

We follow different methodologies, such as the Capability Maturity Model Integration (CMMI), for data management maturity assessment. Leveraging the Data Management Body of Knowledge (DMBoK) includes essential areas with defined standards, processes and KPIs. These areas are identified before the initiation, followed by an evaluation of their performance.

Data Governance Tools

Data governance tools, which are in a budding stage, are implemented by us and include a data catalog and quality dashboards. These tools are essential for data governance, quality measurements and data comparison across different domains, allowing us to know how healthy the data is within our organization.

In our data transformation journey, we concentrated on data analytics and the entire data value chain, from data collection to dissemination. The project is for an external data portal that publishes data. This holistic approach helps us structure our data management goals.

Advice to Peers in the Data Governance Space

My advice to peers in the banking sector’s data governance space is to share your knowledge and experiences within and outside your organization. Collaboration with others is essential as you can have a better understanding of the conventions. Share as much as you can to serve the best interests of the community.