Data Science & Advanced Analytics

Data science is the study of data. It involves developing, recording, storing, and analyzing data to extract useful information effectively. Data science aims to gain insights and knowledge from any type of structured and unstructured data. Data science has become an integral part of IT because of the large amounts of data modern companies and organizations maintain. For example, a company with petabytes of user data may use data science to develop effective ways to store, manage, and analyze the data. In addition, the company may use the scientific method to run tests and extract results that can provide meaningful insights about their users.

Data Mining Vs. Data Science

Data science is often confused with data mining. However, data mining is a subset of data science. It involves analyzing large amounts of data (big data) to discover patterns and other helpful information. Data science covers the entire scope of data collection and processing.

A data science and machine learning platform built from the ground up for an AI-powered business helps enterprises simplify the process of experimentation to deployment, speed data exploration, and model development and training, and scale data science operations across the lifecycle.

As the data stored by companies proliferate, how do organizations gain valuable insights from their Data? Business Analytics helps businesses understand their data and adjust their decision-making according to what their data tells them. As a result, organizations can use business intelligence to make smarter decisions and find the edge over their competition.

Business intelligence helps business units, managers, top executives, and other operational workers make better-informed decisions backed up with accurate data. The following illustrates the Business Analytics maturity graph. As organizations grow, they move from descriptive analysis to prescriptive analysis and finally reach decision automation.

Business Analytics helps:

• To understand the customer more deeply and effectively
• To improve the revenue and drive the performance
• To identify the sales trends
• To improve efficiency and transparency within the business
• To deliver an outstanding customer experience