It is easy to talk these days about the significance of business intelligence practices. Many contemporary businesses function under a data-informed status quo, primarily using various mechanisms and modes to partly explain their operational foundations. An integral aspect of the legitimization of data processing and transparency, the role of data visualization is an accompanying field testing and affirming models. Unlike common automatic operations, data visualization connects closely to human cognition and conveys significant implications in the process of interpretation and perceptive comprehension of the observations by business participants. However, the importance of business intelligence, or its relationship with visualization practices, has not been comprehensively evaluated. Key questions that align with this paper relate to the extent to which business intelligence shapes the operational behavior of visualization practices in business, and consequently, the validity of these practices as a part of everyday business research. In the past, business intelligence systems were designed to extract patterns abstracted from data that were collected. With many advancements in computing power and data storage, companies are utilizing these large platforms for powering several business intelligence applications. Most of these applications are data speech engines, bringing the information to the C-suite. Decisions are increasingly becoming data-centric, and these applications are deeply interwoven in business strategy and make/buy/hold decisions. Business intelligence and data visualization are both sections of sophisticated data analytics. As such, they transport useful data from large groups in a visual layout that businesses can acknowledge and exploit.