Data Science vs Data Analytics Last Updated : 13 Aug, 2024 Summarize Suggest changes Share Like Article Like Report In this article, we will discuss the differences between the two most demanded fields in Artificial intelligence that is data science, and data analytics.What is Data Science Data Science is a field that deals with extracting meaningful information and insights by applying various algorithms preprocessing and scientific methods on structured and unstructured data. This field is related to Artificial Intelligence and is currently one of the most demanded skills. Data science comprises mathematics, computations, statistics, programming, etc to gain meaningful insights from the large amount of data provided in various formats. What is Data AnalyticsData Analytics is used to get conclusions by processing the raw data. It is helpful in various businesses as it helps the company to make decisions based on the conclusions from the data. Basically, data analytics helps to convert a Large number of figures in the form of data into Plain English i.e., conclusions which are further helpful in making in-depth decisions. Below is a table of differences between Data Science and Data Analytics: Difference Between Data Science and Data Analytics There is a significant difference between Data Science and Data Analytics. We will see them one by one for each feature.FeatureData ScienceData AnalyticsCoding LanguagePython is the most commonly used language for data science along with the use of other languages such as C++, Java, Perl, etc.The Knowledge of Python and R Language is essential for Data Analytics.Programming SkillsIn-depth knowledge of programming is required for data science. Basic Programming skills is necessary for data analytics.Use of Machine LearningData Science makes use of machine learning algorithms to get insights.Data Analytics does not use machine learning to get the insight of data.Other SkillsData Science makes use of Data mining activities for getting meaningful insights.Hadoop Based analysis is used for getting conclusions from raw data.ScopeThe scope of data science is large.The Scope of data analysis is micro i.e., small.GoalsData science deals with explorations and new innovations.Data Analysis makes use of existing resources.Data TypeData Science mostly deals with unstructured data.Data Analytics deals with structured data.Statistical SkillsStatistical skills are necessary in the field of Data Science..The statistical skills are of minimal or no use in data analytics.Q.1 Which is better data science or data analytics?Answer :It depend on type of career choice we want to pursue Data Analytics is easier for those who wnat to pursue their career in Analytics and Data science is better choice for those who wants to use machine learning to make advanced level models.Q.2 Which pays more data science or data analytics?Answer :Average salary of data scientist is higher than data analyst. However the salary in both positions depends on the skill and knowledge we have in the particular domain. Q.3 What should I learn first data analytics or data science?Answer :For a begginer who does not have knowledge of programming language starting with data analytics tools like Ms-Excel and Power BI can be a good choice. Advertise with us Next Article Uses of Data Analytics P pratiksha6294 Follow Similar Reads Data Analysis (Analytics) Tutorial Data Analytics is a process of examining, cleaning, transforming and interpreting data to discover useful information, draw conclusions and support decision-making. It helps businesses and organizations understand their data better, identify patterns, solve problems and improve overall performance. 4 min read Introduction to Data AnalyticsWhat is Data Analytics?Data Analytics is the process of collecting, organizing and studying data to find useful information understand what’s happening and make better decisions. 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