Analytics is the systemic computational analysis of data or statistics.[1] It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns towards effective decision making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
Data analytics is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.
Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.
Source: https://www.investopedia.com/terms/d/data-analytics.asp
Data science provides meaningful information based on large amounts of complex data or big data. Data science, or data-driven science, combines different fields of work in statistics and computation to interpret data for decision-making purposes.
Data is drawn from different sectors, channels, and platforms including cell phones, social media, e-commerce sites, healthcare surveys, and Internet searches.
Source: https://www.investopedia.com/terms/d/data-science.asp