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Use Python to build an interactive visualization tool and report that gathers insights on user-chatbot/customer care response interactions
In this Build Project, you’ll wear the hat of Business Intelligence Engineer, by working on Customer Support on Twitter dataset, which is a large, modern corpus of tweets and replies to check, analyze and understand the pattern and conversations, and for study of modern customer support practices and impact.
Get to know the Build Fellow and other students, ask questions about the project requirements, prepare your workspace.
Perform exploratory data analysis on the large dataset.
Execute data cleaning for non-text field.
Write a script to understand text/response and clean the response data using text analysis.
Conduct data analysis on the cleaned data and get a clear idea on how to start a data story.
Perform data visualization to represent the data in a better way.
Create an interactive visualization/dashboard to tell the data story and insights.
Polish your project deliverables and present them to the Build Fellow and other students in the final group session.
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Jainik is a Business Intelligence Build Fellow at Open Avenues, leading student projects in Business Intelligence and Data Reporting. He also serves as a Business Intelligence/Data Engineer at Businessolver, where he collaborates with product managers, data scientists, and business stakeholders to drive decision-making and product innovation. Jainik focuses on developing scalable and automated data processes using AWS Athena and BI tools to enhance customer-facing reporting and streamline operations. With over three years of experience, he has previously automated data processes and supported upper management with business insights using BI tools. Jainik holds a Master's degree in Informatics with a concentration in Data Analytics