Is there any difference between Data Science and Data Analytics?
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The difference between data science and analytics data is that, data analytics, focuses on examining raw data to draw conclusions about that information as It involves applying algorithms and statistical tools to perform descriptive and inferential analysis whereas data science is a multidisciplinary field that uses scientific methods, algorithms, processes, and systems to extract knowledge and insights from structured and unstructured data, It encompasses various techniques from statistics, machine learning, data mining, and big data. Data science is like an umbrella term for a group of fields that are used to mine large data sets.
Primary goals are a point of differentiation between data science and data analytics. By putting prediction and inference first, data scientists use cutting-edge algorithms to extract meaningful insights from large, complicated datasets. In contrast, the focus of data analytics is on examining past data to produce useful insights for making decisions.
But Overal both rely on comparable fundamental ideas in programming, statistics, and data visualization.
After classifying the rocks according to size and colour, a data analyst would look into their origins. The rocks would be used by a data scientist to create a weather prediction model.
Its simple, Data Science focuses on creating new models and methods, while Data Analytics focuses on analyzing data to provide actionable insights