Data analytics and data science are related fields, but they have some key differences.
Data analytics is the process of examining, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analytics is focused on the use of statistical techniques and tools to extract insights from data. It typically involves descriptive and diagnostic analysis of past performance and trends.
Data science is a broader field that encompasses data analytics, but also includes the development of new algorithms and models, and the use of advanced techniques such as machine learning and artificial intelligence. Data science is focused on discovering hidden patterns and knowledge from data, and making predictions about future events. It typically involves a combination of descriptive, diagnostic, predictive, and prescriptive analysis.
In summary, data analytics is a subset of data science, focused mainly on the analysis of data, while data science is a broader field that involves not only analysis but also the development of models and predictions using advanced techniques.