Data Science vs. Data Analytics
Data Scientists and Data Analysts utilize data in different ways. Data Scientists use a combination of Mathematical, Statistical, and Machine Learning techniques to clean, process, and interpret data to extract insights from it. They design advanced data modelling processes using prototypes, ML algorithms, predictive models, and custom analysis.
While data analysts examine data sets to identify trends and draw conclusions, Data Analysts collect large volumes of data, organize it, and analyze it to identify relevant patterns. After the analysis part is done, they strive to present their findings through data visualization methods like charts, graphs, etc. Thus, Data Analysts transform complex insights into business-savvy language that both technical and non-technical members of an organization can understand.
Both the roles perform varying degrees of data collection, cleaning, and analysis to gain actionable insights for data-driven decision-making. Hence, the responsibilities of Data Scientists and Data Analysts often overlap.
Responsibilities of Data Scientists
To process, clean, and validate the integrity of data.
To perform Exploratory Data Analysis on large datasets.
To perform data mining by creating ETL pipelines.
To perform statistical analysis using ML algorithms like logistic regression, KNN, Random Forest, Decision Trees, etc.
To write code for automation and build resourceful Machine Learning libraries.
To glean business insights using Machine Learning and algorithms.
To identify new trends in data for making business predictions.
Responsibilities of Data Analysts
To collect and interpret data.
To identify relevant patterns in a dataset.
To perform data querying using SQL.
To experiment with different analytical tools like predictive analytics, prescriptive analytics, descriptive analytics, and diagnostic analytics.
To use data visualization tools like Tableau, IBM Cognos Analytics, etc., for presenting the extracted information.
Career Perspective
The career pathway for Data Science and Data Analytics is quite similar. Data Science aspirants must have a strong educational foundation in Computer Science, or Software Engineering, or Data Science. Similarly, Data Analysts can pursue an undergraduate degree in Computer Science, or Information Technology, or Mathematics, or Statistics.
