Data Science
Data science is an interdisciplinary field that combines techniques from statistics, mathematics, and computer science to analyze, interpret, and extract meaningful knowledge from large datasets. It utilizes various tools and methods, such as machine learning, data mining, and visualization, to gain insights and make evidence-based decisions in diverse areas, from business and research to social and natural sciences. The main goal of data science is to uncover patterns, trends, and correlations in data to generate value and better understand complex phenomena.
Exploratiry Analysis
Its goal is to discover patterns, trends, relationships, and potential anomalies in data by using statistical techniques and visual tools.
Clustering
Clustering in data science is a process that involves grouping similar data together into sets called “clusters,” with the aim of identifying patterns and hidden structures in the dataset.
Predictive analysis
Predictive analytics in data science refers to the use of statistical techniques and machine learning algorithms to predict future events or trends based on historical data and patterns identified in datasets.
Prioriry Analysis
Priority analysis in data science is the process of assigning levels of importance or relevance to specific elements within a dataset to make informed decisions and focus efforts on more significant areas.