Ensure the reliability and validity of data, data sources, data analysis methods, and inferences derived.Ensure the presence of legitimate and unbiased inference.Ensure appropriate implementation of data collection methods and analysis.Ensure availability of the necessary analytical skills.There are various examples where data analysis is used, ranging from transportation, risk and fraud detection, customer interaction, city planning healthcare, web search, digital advertisement, and more.Ĭonsidering the example of healthcare, as we have noticed recently that with the outbreak of the pandemic, Coronavirus hospitals are facing the challenge of coping up with the pressure in treating as many patients as possible, considering data analysis allows to monitor machine and data usage in such scenarios to achieve efficiency gain.īefore diving any more in-depth, make the following pre-requisites for proper Data Analysis: Ensuring data integrity is one of the essential components of data analysis. Data generation is a continual process this makes data analysis a continuous, iterative process where the collection and performing data analysis simultaneously. These analytical procedures enable us to induce the underlying inference from data by eliminating the unnecessary chaos created by its rest. The systematic application of statistical and logical techniques to describe the data scope, modularize the data structure, condense the data representation, illustrate via images, tables, and graphs, and evaluate statistical inclinations, probability data, and derive meaningful conclusions known as Data Analysis. Conclusion What is Data Analysis? Definition & Example.Techniques based on Visualization and Graphs

Techniques based on Artificial Intelligence and Machine Learning Techniques based on Mathematics and Statistics Data Requirement Specification - define your scope: What is Data Analysis? Definition & Example.

Research tools for data analysis