A data science lab setup is vital in the current business environment to support organizations’ need for data analysis. It essentially entails developing an environment hyperspecialized for data, furnishing equipment, facilities and human resource that directly draw value from data. This involves the process of purchasing, clearing, and formatting big data that at times occupies a large amount of space and resources. The operations on the data and the training of machine learning models require high-performance computing resources such as high-performance CPUs and GPUs. The software environment must be solid, and involves data handling tools, statistical packages, and machine learning libraries. However, the presence of a data science lab requires the presence of a competent team to conduct the data exploration, modeling, and analysis. Integration, communication, and, mainly, using innovations as a reference model and framing an experimentation culture are fundamental elements that can help a company to pursue innovation successfully.