Analytics is all about interpreting raw data and transforming it into actionable insight. Data analysts use computational tools such as mathematics, statistics, and predictive modeling to find meaningful patterns in data in order to get a clearer picture of how to solve a business challenge. Given these future predicters, prescriptive analytics is used to identify the best course of action. Essentially, they are scientists who use data to make hypothesis and analytical tools to validate them.
Data analysis is organized into three phases—descriptive, predictive, and prescriptive. Descriptive analytics takes historical data and analyzes it to understand changes that occur in a business over a defined period of time. Predictive analytics builds on this analysis and uses it along with algorithms and machine learning to predict future business outcomes based on past experience.
To stay competitive and accelerate innovation, businesses are turning to data analytics and business intelligence to obtain actionable insights from big data in key areas including sales, marketing, production, quality and training. Thought leaders in analytics and insights are also looking to applications such as Amazon Elastic Map (EMR) to scale data analytics capabilities to respond to changes in data traffic, realizing greater operational efficiencies and differentiating themselves from key competitors.
From the office to the shop floor, analytics are helping businesses: