Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from noisy, structured, and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning, and big data.

Data science is a multidisciplinary approach to extracting actionable insights from today’s organizations’ large and ever-increasing volumes of data collected and created. Data science encompasses preparing data for analysis and processing, performing advanced data analysis, and presenting the results to reveal patterns and enable stakeholders to draw informed conclusions.

Data preparation can involve cleansing, aggregating, and manipulating it to be ready for specific types of processing. Analysis requires the development and use of algorithms, analytics, and AI models. It’s driven by software that combs through data to find patterns to transform them into predictions that support business decision-making. The accuracy of these predictions must be validated through scientifically designed tests and experiments. And the results should be shared through the skillful use of data visualization tools that make it possible for anyone to see the patterns and understand trends.

For short, application integration (or app integration) combines and enhances data flows between two separate software applications. Businesses often use application integration software to create a bridge between a new cloud application and an older application hosted on premise, enabling a wide range of independently designed applications to work together