Difference between Data Science and Data Analytics in tabular form
Data Science is one of the recent fields combining big data, unstructured data, and a combination of statistics and analytics, and business intelligence. It is a new field that has emerged within the field of data management providing an understanding of the correlation between structured and unstructured data.
Data analytics are used to describe the field and a comprehensive collection of associated methods. All these terms tend to be used for the application of analytics methods to data that large organizations generate. Data analysts collect, process, and perform statistical analyses of data.
Difference between Data Science and Data Analytics:
|1. The scope is macro.||1. The scope is micro|
|2. It provides strategic actionable insights into the world.||2. It provides operational observation into issues.|
|3. It deals with Big Data.||3. It doesn't necessarily deal with big data.|
|4. Mathematical, technical and strategic knowledge are mandatory.||4. Data analysis and visualization skills required.|
|5. It includes Machine Learning, Artificial Intelligence, and engine exploration.||5. It includes analytical methods and techniques using statistical tools.|
|6. It is used into the Internet research, speech recognition, image recognition, recommender systems, digital marketing, and more.||6. It is dominantly used in the industries of travel and tourism, finance, healthcare, gaming, and more.|