Big data, artificial intelligence (AI), and machine learning (ML) are more than buzzwords; they have become powerful technologies in scientific discovery and are drawing interest and investment from all sectors of academia, industry, and government. We have reached an era where massive amounts of data are consistently generated, processed, stored, and exchanged. We have developed both new hardware and software capabilities that support data mining techniques with ever increasing complexity and intelligence to uncover hidden knowledge from the flood of data. It is exciting to witness how big data, AI, and ML are revolutionizing science and technology, yet it is informative to understand the reasons of these technologies success. This chapter introduces these technologies through a lens of science and history, focusing on their evolution in the field of computational biotechnology. We will discuss long-term efforts of organizing and maintaining biological and biomedical databases for data exploration and explain best practices of data management for new data collection and database construction. We will cover some common data analysis techniques, where the roles of AI and ML become inevitable when tackling diverse data structures and large data volumes. With the fast-paced nature of big data, AI, and ML, in this chapter, we emphasize the fundamentals in the hope to instill foundational knowledge and spark creativity for domain applications.