Case Study Details

Data Science Framework and Processes

Focus

Design of a data science, analytics and machine learning governance framework and related processes to maximise the value and capability of data science at a government Agency and ensure its responsible use.

Approach

Kuaba assessed the data science operations the Agency and designed streamlined processes, technology architectures, and practical frameworks. The project culminated in an implementation roadmap, integrating all elements and including training recommendations to enhance capabilities.

Kuaba conducted a thorough review of processes, platforms, architectures, models, code, data and capabilities across all teams, evaluated against both quantifiable metrics and qualitative measures.

The comprehensive framework comprised strategic, tactical, and operational components. Kuaba created detailed documentation of relevant data science processes and architectures for practical application. This included recommendations for technical architecture and technologies to ensure efficient, scalable, and responsible data science practices, along with a clear implementation approach.

Outcome

• Increased efficiencies, consistency and value of data science
• Better decision making through the provision of accurate products
• Reduced siloes between teams, promoting collaboration, transparency and sharing of resources
• Standard, repeatable processes and products that allow for efficient and scalable development
• Increased security and adherence to best practice, privacy, ethical and regulatory principles
• Understanding of capability gaps with and required remmediation