Because Data Analytics is a specific and precise application of Data Science $($Read the class material entitled $$The Core Differences between Data Analytics vs Data Science$$ on Moodle$),$ there are major differences between these two fields. Which of the following INCORRECTLY states the differences?

a$.$

Data analytics is a concept that continues to expand and evolve, but this particular field of digital information expertise or technology is often used within the healthcare, retail, gaming, and travel industries for immediate responses to challenges and business goals, whereas Data Science is used in major fields of corporate analytics, search engine engineering, and autonomous fields such as artificial intelligence $($AI$)$ and machine learning $($ML$).$

b$.$

In the field of Data Science, a comprehensive understanding of SQL database and coding is required, in addition to a firm grasp of working with large sets of unstructured metrics, and insights; On the other hand, in the field of Data Analytics, a solid understanding of mathematics and statistical skills is essential, as well as programming skills and a working knowledge of online data visualization tools, and intermediate statistics.

c$.$

The primary goal of Data Science is to use the wealth of available digital metrics and insights to discover the questions that we need to ask to drive innovation, growth, progress, and evolution. With the main aim of using existing information to uncover patterns and visualize insights in specific areas, Data Analytics is geared toward sourcing actionable data based on specific aims, operations, and KPIs by using existing information to uncover patterns and visualize insights in specific areas.

d$.$

All of the above are correct.

e$.$

Data Science is a MACRO field of multidisciplinary, covering a wider field of data exploration, working with enormous sets of structured and unstructured data. On the other hand, Data Analytics is a MICRO field, drilling down into specific elements of business operations with a view to documenting departmental trends and streamlining processes either over specific time periods or in real time, therefore, concentrating mostly on structured data.