With the increasing complexity, variability, and volume of data, it is becoming increasingly necessary to develop data access approaches that are interoperable and scalable. Traditional data infrastructure based on batch ETL processes lacks the adaptability necessary to meet modern demands, resulting in organizations not achieving optimal business intelligence results. The focus has shifted from collecting data in a centralized environment to connecting with distributed sources in real time. By using technologies such as data virtualization, diverse data types can be accessed, governed and integrated seamlessly across a variety of platforms. Using APIs, Semantic models, and Container technologies can simplify energy research data management and allow us to navigate today's dynamic ecosystems effectively.