Abstract

In today’s world, data science has swept the globe, impacting practically every business. All the industries and sectors have become data-dependent. As a result, data science has turned into a source of energy for industries. Data science is a field that incorporates approaches from a variety of disciplines to collect data, analyze it, develop new perspectives from it, and utilize it in decision-making. The technological disciplines that make up the data science field include data mining, statistics, machine learning, data analytics, and various programming languages like python or R. Building data science end-to-end solutions follow an entire life cycle from understanding the problem and exploring the data to deploying the model. Exploratory Data Analysis (EDA) is a phase that occurs throughout the early stages of the data science life cycle and entails conducting analysis over the data. Individuals become familiar with the source data after running EDA techniques and become aware of any irregularities or anomalies that might be present in the data. Manually evaluating the data and performing all the EDA techniques might be time-consuming and tedious. As a result, in this paper, I have developed QuickViz, an interactive web application tool that simplifies and automates the exploratory data analysis stage and is extremely user-friendly and easy to use. Using this tool will conserve a lot of time and provide a web-based dashboard to present the findings to the stakeholders in a visually appealing manner. This web application tool can also be utilized by those who do not have any prior knowledge of programming as this tool doesn't require any coding to execute EDA procedures. Users just have to upload their dataset and examine the results of descriptive and graphical EDA techniques through the QuickViz tool, aiding them in gaining insights and patterns from the data and presenting their findings directly to the stakeholders through this web application.

Full Text
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