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KPMG Data Analytics Internship

Data has enormous power. It is the most sought after and expensive commodity in the world. To use that data to gain useful insights and develop a strategic business plan is an art in itself that many calls as Data Analytics. Data Science is the umbrella term comprising of different fields that are used to derive insights from big datasets. Their functions are interconnected. Data Analytics refers to a specific field that works upon answering the existing relevant questions by finding valuable actionable insights. It is more focused. Data Science is directed toward finding which questions are to be asked.

I completed the KPMG Data Analytics Virtual Consulting Internship recently. The first thing that surprised me and something that would be important to know by anyone who wants to do this internship in future is that it's not a normal course wherein one is provided with everything but it functions on a self-learning basis. There, you will be required to solve three tasks: Data Quality Assessment, Data Insights and Data Presentation. You will be free to choose any technology and platform to achieve the best results. Proper instructions will be there. Business data set consisting of customer demographics, customer address, transactions and new customer list will be provided, on which the analysis has to be done. After submitting your response, you will be able to access the ideal response submitted by a KPMG consultant so that you can compare both, identify the shortcomings and improve upon those. That is what I loved the most about this experience, the chance to learn on my own by research, making mistakes and correcting them.

Moreover, it felt like a small professional project wherein you have to take care of the communication part as well, that is essential in a corporate setup.

To brief about the tasks in detail, it involved analyzing business data sets and improving their data quality. Then target specific customers through the analysis of customer behaviour trends and patterns. Then representing all of these insights by using a dashboard through Tableau, Power BI and Excel.

Module 1: Data Quality Assessment To analyze data quality issues with the given datasets. It comprised of pointing out the existing discrepancies and suggesting ways to overcome those to prevent future hindrances in the analysis. It needed a good knowledge of Excel, particularly of filter tool and other functions. It was required to convey all this information over the mail to the client.

Module 2: Data Insights To gather insights about potential customers by studying their past behaviour and choosing data analysis strategies for the same. The following factors were considered in this: age distribution, number of purchases in the last three years, job industry category, wealth segment, number of cars owned etc. In this part, a presentation had to be made to display the data analysis strategies and its results to the client to help them choose their target customers.

Module 3: Data Presentation To display the findings of the previous task such as target customers, top 10 goods, customer demographics, their spending habits in the form of a dashboard using Power BI, Tableau to help in data visualization.

I want to thank KPMG and Inside Sherpa for allowing me to be a part of their beautifully designed data analytics virtual consulting experience.

Return to the virtual internship here: https://www.insidesherpa.com/virtual-internships/theme/m7W4GMqeT3bh9Nb2c/KPMG-Data-Analytics-Virtual-Internship

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