That’s what a one-stop shop is, and what this post is about.Īs shown in the bottom part of Figure 1, as opposed to the top part where the managers may easily lose their minds, a “data analyst” comes to help with the one-stop shop and a framework that integrates various kinds of requests made by the managers. How a data analyst comes to help with the one-stop shop The system takes care of itself, and it never sleeps while the back-end databases keep updating themselves.įigure 1. It grabs data from the databases, then processes the extracted data to generate business analytics, and incorporates the outputs in a decorated dashboard and report in the end. Therefore, ideally, there is a system that automates the repetitive queries. These requests are usually allocated to data analysts some of them are repetitive, time-consuming work that really can be automated. To generate business intelligence, decision makers make ad hoc requests from time to time when the need emerges. That’s what we call “business intelligence”. When used effectively, data offer insights into a company’s business and strategies, and ultimately improve the company’s operations. In the course of a business process, a company produces data, collects its own data, and makes use of them. For instance, what is working well? And what calls for attention? Decision makers need the answers delivered to them timely across the departments, and presented to them effectively, better in real time with visual representations of the results. On a daily basis, decision makers sit on these data with untold stories and insights to be discovered.
In the business world, with each transaction, tons of operational data are generated.
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