Modern clinical decision support based on data analytics requires a framework that incorporates distributed processing platforms, sustainable data models, and inference algorithms. The ultimate objective of this chapter is to identify the common components of a user-centered analytics framework that can reason using different clinical historical Big Data. Those components emerge through two case studies that identify potential analytics to support the decisions of laboratory managers. In the case studies, the outputs are visualizing and estimating of clinical test volumes, which will lead to optimum purchasing and fiscal planning. We particularly focus on the reusable business intelligence (BI) components that can help running similar business processes from a single manager’s perspective, as well as the BI components that can be reused by several managers in a clinical laboratory setting. This is the first attempt at design and implementation of a user-centered framework for clinical laboratory settings as a BI platform.