Realizing the Infrastructure
IN THIS CHAPTER
Understanding what it means to realize a data infrastructure
Identifying the key infrastructure elements for success
Utilizing automation to drive speed and efficiency
Creating a collaborative workspace to increase data science productivity
Data plays a key role in every use case of data science, although the type of data used can vary. For example, innovation can be fueled by having machine learning models find insights in the large amounts of data being generated by businesses. In fact, it’s possible for a business to cultivate an entirely new way of thinking inside the organization, based on data science alone, if management pushes in that direction. The key is understanding the role that data plays at every step in the data science workflow and how the infrastructure must be designed and operated to maximize utilization of the data as well as enable high data science productivity. In this chapter, I help you focus on how all the pieces need to come together to realize a productive data infrastructure supporting your data ...