Portfolio - Soumita Bhattacharya

PowerBI Project

Business Insights 360 using Power BI

AtliQ hardware has become one of the fastest growing company in the Electronics Goods Market, While grew substantially in last few years, they had some bitter experience in Latin America. They tried to establish their presence there, to open their new store but they faced a huge loss there.

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Finance View of the project. To create this view and to make it dynamic, I have created all the required measures.

Sales View contains dynamic presentation of Customer Performance, Product Performance, Performance Matrix Region wise.

Project Details

In this project I have imported data from MySQL, connecting with Power BI.
Snowflakes schema has been used in this project to connect the tables and manage the relationship.
This project is a dynamic presentation of Business Insights 360.
Finance View, Sales View, Marketing View, Supply Chain View has been covered here using the use case of AtliQ Hardware.
The Situation :AtliQ hardware has become one of the fastest growing company in the Electronic Goods Market. They tried to establish their presence there, to open their new store but they faced a huge loss there, and this happens because they made all their decisions just based on the survey they conducted and just based on their intuitions. In the annual strategy meeting one of the top item was to onboard Data Analytics in the company to make data driven decision.
Previously they were using Excel files, they were using some analysis in the excel itself but now the company is so big that Excel is not going to work anymore.

Excel Project

Atliq Excel Project

Atliq is a company, sales hardware. Now Atliq Hardware in infested with Excel Files. Now this company wants to get rid of these excel files and want to get a better understanding of their business by analyzing the data.

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Customer Performance Report

Market Performance Report

Project Details

Here I have created a report on Sales Analytics and Finance Analytics for Atliq Company.
The first Report is Customer Performance Report and where I have shown the Net Sales for individual customer for 2019, 2020 and 2021. And then I have compared the performance of last two year.
The next one is a Market Performance Report. Market means country here. So here I found Net sales by countries for individual years. We will also see the target for 2021 and then we will compare what is the difference between the Actual net sales and Target.

SQL Project

Energy plant analysis

Energy Plant Analysis. window function ,constraint these concepts helped to analyze the following Matrics . 1.The transaction summary for each fuel type 2.A general summary report for the plants 3.An advanced summary report on the customers

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Multiple joins being carried out in the same statement

Total Cost

Project Details

Following Matrics To Be Analyzed 1.The transaction summary for each fuel type 2.A general summary report for the plants 3.An advanced summary report on the customers

SQL Project

Maven Movies business analysis with SQL

The Situation: You and your business partner were recently approached by another local business owner who is interested in purchasing Maven Movies .He primarily owns restaurants and bars, so he has lot of questions for your business and the rental business in general. His offer seems very generous,

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Please send over the managers names at each stoe ,with the full address of each property(street address, District, city and country

how many inventory items you have with each rating at each store.

Project Details

All the queries has been solved using SQL in this project

Python Project

Uber Analysis using Python

As part of my ongoing data analysis journey, I recently delved into the vast realm of Uber data. With the ever-growing usage of services like Uber, understanding the patterns within this data can unlock valuable insights for businesses.

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Which month have max. Uber pickups in New York City ?

Hourly Rush in New York city on all days

Project Details

1.Data Retrieval: I began by sourcing Uber data, which was a treasure trove of information waiting to be explored.
2.Data Pre-processing: Cleaning the data was crucial. I meticulously handled data types, missing values, and duplicates to ensure accuracy in my analysis.
3.Insights Unveiled:
a. Peak Months for Pickups: My analysis revealed the month witnessed the highest number of Uber pickups in New York City, shedding light on seasonal trends.
b. Hourly Rush: By dissecting the data on an hourly basis, I identified peak hours of activity in New York City, crucial for optimizing service allocation.
c. Active Vehicles by Base Number: Through my analysis, I pinpointed the base number with the highest number of active vehicles, providing insights into fleet management strategies.
d. Geographical Hotspots: I mapped out the locations within New York City experiencing the most significant rush, aiding in targeted marketing efforts and resource allocation.
e. Hourly and Weekly Patterns:

Hello, I am

Soumita Bhattacharya

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About

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Business Insights 360 using Power BI

Atliq Excel Project

Energy plant analysis

Maven Movies business analysis with SQL

Uber Analysis using Python

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Soumita Bhattacharya

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