PROJECTS

Business Problem: The board of directors of an organization are reviewing 1000 potential startups to invest in. They want to have proper analysis and detailed insights into the following combinations, before deciding on which company to invest in:

• High Revenue
• Low Expenses
• Top Growth

Task: The task is to assist the board in identifying which business represents the best investment opportunities.

Final Solution: A dynamic tableau dashboard will be delivered to the board of directors for best data mining and decision-making techniques.

Dataset Description: Analysis were performed on the following datasets

1. Company Overviews: The dataset contains summary information of companies.
2. Company Financials: The dataset contains detailed financial information of each company for 10 years.

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Business Problem: The Coal Terminal needs an analysis for them to properly assess which of their Coal Reclaimer Machines require maintenance in the upcoming month. These machines run literally round the clock 24/7 for 365 days a year. Every minute of downtime equates to millions of dollars of lost revenue, that is why it is crucial to identify exactly when their machines require maintenance.

Task: The task is to find out which of the 5 machines have exceeded this level, create a report on Tableau and give recommendations to the executive stakeholders.

Final Solution: A Tableau dashboard will be delivered to the executive stakeholders for them to identify which machines need maintenance and give recommendations based on my analysis.

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Business Problem: The Finance Department of a Company maintains the invoice level details of all Payroll vendors and the cost associated with generating payslips for their employees. Invoices are received for each vendor and all the details from each invoice are filled in an excel sheet. These same data are collated in one spreadsheet from various countries. The Global Finance leader and other Country-level Finance leaders seek data to identify the Per Payslip Costs (PPC), which helps them in negotiating with vendors to reduce overall cost for the company.

Dataset Description: Analysis were performed on the following datasets

1. Country-wise Detailed information on Vendor Charges/fees( Regional Table1, Regional Table2)
2. Country-wise Payslip Information (Payslips)
3. Master Mapping table – Country – Region – Vendor Name (Mapping)
4. Summary Table consists of Monthly summary of cost as well as payslip information

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Business Problem: An Australian Retail Chain - operating in the "Clothing Retailing Industry" needs turnover insights into the performance of the Clothing Retailing Industry at the state level, before considering an expansion in other states.
They are operating in New South Wales already, but want to be data-driven in making their next business decision.

These are lists of three states they are considering:

• Queensland
• Victoria
• Western Australia

Task: The task is to assess the business environment for the industry in question in each of these three states and present the findings to the board of directors.

Final Solution: Detailed reports and dashboard will be presented on Tableau, which will depict competitors analysis, industry-level analysis, and forecasting analysis model, for the prediction of the future market value of this industry.

Datasets Description: The datasets used for this project is publicly available on the Australian Bureau of Statistics for reference purpose - (www.abs.gov.au).

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Business Problem: The real estate firm is facing difficulty in determining and predicting the price of houses in their listenings, the organization what to have more insight about the effect of price change on revenue. Compare different independent/predictor variables with the dependent/response variable (price) and find the relationship between these variables to effectively predict the price of houses.

Dataset Description: The dataset contains 16 columns and 506 rows of historical data of the real estate company. Descriptive, correlation, simple regression, and multiple regression analyses were performed to determine the forecast model analysis of the dependent variable.

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Dataset Description: Dataset is about a company's sales made from multiple departmental stores across the world, with details of the sale, discount, profit, product, customer, store, and location data.

Business Problem: To analyze and find the regions and product categories for improvement in business, also locate the best performing products and our top customers on the way. To find our Delivery performance and department level analysis on sales and profits.

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This is the Google Data Analytics Capstone Project, that I did to wrap up the Data Analytics Certificate Program, where I demonstrated what I learned in the course by analyzing Bellabeat Products data in R Studio, this dataset is available on Kaggle it contains a personal fitness tracker from thirty Fitbit users. The datasets were generated by respondents to a distributed survey via Amazon Mechanical Turk between 03.12.2016 - 05.12.2016.

• View Project 7