“Data is a precious thing and will last longer than the systems themselves.” – Tim Berners-Lee
Raw data, at its core, contains information that is too broad or "broken". As a data analyst, one should be prepared to clean a dataset by inspecting, reducing, and replacing Null/missing values when needed. A "cleaned" dataset should be relevant and impactful to solving companies' questions.
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This project does this and solves the following questions:
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Compute "Daily Excess Return" based on comparisons to risk-free (3 Month Treasury Bill) for the period 12/31/2019 - 12/31/2020
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Compute "Log Cumulative Excess Return" over the same period
The goal of a dashboard is to portray data seamlessly and coherently. A data analyst needs to uses these dashboards to tell a story and make insightful decisions for a company.
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This tableau dashboard project shows the following:
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Income v. Expense
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Expense Allocation
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Earnings
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Earnings Trend
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The goal is to determine the earnings of the dataset and what can be done to improve it.
Risk management is important in all aspects of life; deciding on a new house or in finance. Managing risk is all about evaluating and weighing peril for the best long-term outcome for an individual or organization.
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The purpose of this project is to assess and understand mortgage loan data by providing four stratification reports:
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Lender Institution Type
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Loan to Value (LTV) Cohorts
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Loan Age Cohort
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Crosstab report using Loan Age Cohort and FICO Score Cohort (Includes visualization)
During Covid 2020, I decided to embark on a financial literacy journey. My goal was to improve my understanding of finance by changing my financial lifestyle and developing a budget that I could follow. After a year, I have increased my savings and investment accounts and have eliminated my debts.
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The purpose of this project is to help others understand their finances better the same way I did by:
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Categorizing Income and Expenses
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Generating Earnings
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Visualizing finances