As Thailand is moving toward digital transformation, government and private organizations have been increasingly using data for decision-making. However, many organizations still encounter three pain points: (1) many data utilizations are still performed in ad hoc manners, (2) lacking a reliable and sustainable platform for Big Data Analytics and (3) lacking experienced data scientist teams to analyze insights and derive propositions to move the country forward.

The SAI team has been established to gradually and sustainably address these pain points using expertise in data engineering, data integration, data visualization, data analytics, and data sharing.

 Big Data is one of the key issues in many nations including Thailand. Big data is huge in volume but also huge in benefits to many people and organizations when used with predictive analytics. This technology, especially in Geospatial and Social Network can enable government and business to take strategic decision and lead to better societies.

Cloud computing is also another enabling technology that allows users to get the results of their application quickly and conveniently. It can minimize hardware failures and data loss because of automatic networked backups and scalabilities. Using these remote resources save organizations the personnel and infrastructure cost.

We (KEA) believe in the modern IT approach to solve our nation’s problems. We design and develop nation-wide applications, systems and technology for not only government policy makers but also farmers, enterprises, general users and everyone to have access to key analytics information.

Daily life, education, work, and management at individual, organizational, and national levels – across both public and private sectors-rely on data from the past, present, and predicted future to support effective decision-making and planning. This reliance is crucial in this digital age, where large volumes of data are continuously generated.

Our research team thus focuses on developing comprehensive Data-Driven Simulation and Systems by applying diverse technologies. These include multi-source data integration, real-time or near real-time data management, machine learning, big data management, and statistical data analysis. Last but not least, advanced technologies such as mathematical simulation and advanced mathematics are employed to create  highly accurate models for future forecasting.

We hope that our research outcomes will support both organizational and national levels in various applications, including but not limited to strategic decision-making, resource planning, risk management, emergency response, and public policy development.