– What are the purposes of adopting GenAI in your organisations?
– How important is data quality & preparation to AI transformation for data analytics?
– Strategy on adopting GenAI on data strategy. Examples about AI integration with existing tools.

– What are the different types of migration?
– Cycle for data migration – How do we plan, design and execute?
– Setting expectations with stakeholders – How do we deal with changes and resistance?

– Showcase examples of how data technology, including AI, machine learning, and advanced analytics, is driving innovation and efficiency.
– How to build scalable data architectures capable of handling large volumes of structured and unstructured data, leveraging cloud computing and big data technologies?

– How Ipsos is leveraging AI/GenAI to redefine the Insights function, driving innovation and delivering actionable insights.
– How to use technology as an accelerator of innovation, a catalyst for transformation that can elevate the Insights function with combined Human Intelligence and Artificial Intelligence?

– How are your organisations working on data governance? How do you drive the policies under the framework?
– Practical examples on how to start building the data governance framework.
– How to future proof data governance policy in today’s digital landscape? (AI, machine learning, etc.) What are the common pitfalls to avoid?

– How do we monetise data to drive revenue?
– How we leverage data in creating a positive impact on business growth.

– How to choose the use the right BI tools that cater to their unique business and growth needs?
– How to create a BI framework that works smartly for your organisation / team?
– How to get inputs to make your BI strategy more robust and ready for future?

– What are the main challenges on effective implementing AI & analytics? How do we overcome these challenges?
– How to improve the customer experience / decision making process through AI & analytics?

– How Agoda Workflow Editor enables efficient workflow management and clearer visualisation of complex data flows.
– How to utilise GitLab for collaboration and ensure seamless deployment to production?

– Why do we need ethical data collection?
– How to ethically collect and maintain the personal data to ensure compliance to the local regulations?

– What is the key element in turning complex data into insights?
– What are the difficulties when trying to implement the Big Data Visualisation framework in daily life?
– How to implement Interactive and Real-Time Data Visualisation?
– How real-time data feeds benefit us to keep visualisations up-to-date?