Data-Driven Decision Making

Data science consist of various methods and processes that support and guide the extraction of information and knowledge from raw data. Data Science if used properly has vast applications in business.

A business analyst will work with business administration and take part in EDA which is an approach to analyze datasets, summarize their main characteristics, working with the data and refining the data so that it can be put to use productively. With large amounts of data at our disposal, businesses can make better business, financial and marketing decisions.

If a business has previous data of which product sold well at which time or at which locations, they can work in a way to increase sales. Big Data helps retail outlets and fast-moving consumer goods sellers a lot. With proper data, various important decisions can be made which can improve profits.

Data-driven decision making has many applications. For example, in Finance, it might be figuring out the most cost-effective way to use cloud services, or hire new staff. Or it might be the cheapest way to promote a new product.

In the case of Marketing, with data-driven decision making, we can figure out which promotional media has the best reach and Return on Investment (ROI). In the case of overall company growth, data can be used to track customer loyalty. Past data about customers can be brought and analyzed to find out the demographics of the most loyal customers.