Data Science and its components — 1
Data Science is without doubt a vast field encompassing many smaller sections related to Data and there is definitely a surge in the kind of roles involved in this field mainly due to the perspective change about Data among people within the industry for the last two decades. I am trying to present it in a simple and crisp way possible covering few buzzwords to avoid the overwhelming confusion around it.
DATA STRATEGY — It helps us make logical choices and informed decisions based on the data available with us by keeping it safe and compliant.
DATA ENGINEERING — It focuses on practical applications of data collection and analysis by maintaining data warehouses and building data infrastructures.
DATA ANALYTICS — It defines the concept and practice of data related activities focusing on historical data in context. It is a systematic, structured and a crucial component of Data Science.
DATA ANALYSIS — It involves providing solutions for problems related to business decision making using existing data to uncover actionable data. It is a subset of Data Analytics.
DATA MINING — It is the process of extracting usable data from a larger set of existing data. It is a subset of Data Analysis.
DATA VISUALISATION — It is an interdisciplinary field that deals with graphical representation of data by translating it into visual context.
DATA SCIENCE — It is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.
