– How to accelerate data processing and insights generation
– How to utilise Natural Language Processing (NLP) capabilities of LLMs to analyse unstructured data?
– Case studies of companies reducing costs with AI-driven analytics.

– Examples of organisations that have experienced significant improvements in decision-making and operational efficiency by prioritising data quality.
– Techniques for identifying and correcting errors, handling missing values, and standardising data formats.
– Techniques to ensure data quality measures can scale with the growing data needs.

– 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 to conduct a thorough assessment of your current data landscape, identify data sources, and develop a comprehensive migration plan?
– Best practices for maintaining data security and privacy throughout the migration process, including encryption, access controls, and compliance with data protection regulations.

– How to establish clear data governance policies, standards, and procedures that align with your organisation’s objectives and regulatory requirements.
– How to develop and implement an effective incident response plan to address data breaches and security incidents, minimising impact and ensuring timely resolution.

– How to leverage user data to create targeted in-app advertisements that enhance user experience and drive higher ad revenues.
– Understand the types of data that can be most beneficial to external partners or customers.
– How to analyse user data to extract valuable insights that can be sold to third-party companies.

– Delve into the essential criteria for choosing business intelligence tools that cater to your organisation’s unique needs, ensuring scalability, seamless integration, and ease of use.
– Steps to create and implement a solid BI framework, including establishing data governance, providing user training, and promoting continuous improvement.

– Understand how to select and apply the appropriate statistical models and machine learning algorithms for your specific predictive and prescriptive analytics needs.
– Explore the technologies and methodologies required to establish real-time data pipelines
– Understand how to select and apply the appropriate statistical models and machine learning algorithms for your specific predictive and prescriptive analytics needs.

– 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?

– How to ethically collect and maintain the personal data to ensure compliance to the local regulations?
– Discover methods for conducting regular ethical audits to assess compliance.

– How to identify and prioritise the most relevant metrics and key performance indicators (KPIs) to include in your dashboards, ensuring they align with business goals and user needs?
– How to Implement Interactive and Real-Time Data Visualisation?
– Discover the technologies and methods for setting up real-time data feeds to keep visualisations up-to-date.