With years of experience in technical support and a CompTIA A+ certification, I have developed a strong skill set in troubleshooting hardware, software, and networking issues. My roles with the City IT department and a school district have honed my ability to resolve diverse technical challenges efficiently. I am passionate about delivering exceptional service and ensuring seamless technology experiences for users in various environments.
In my data analytics experience, I have worked with data sets from various industries. I have experience with data cleaning, data visualization, and statistical analysis using tools such as Excel, SQL, and Python. I have worked with machine learning algorithms, such as decision trees and regression analysis, to build predictive models. In addition, I have experience with data reporting and presentation, having created dashboards and reports for managers and coworkers. My data analytics experience has allowed me to develop my analytical and problem-solving skills and has prepared me for a career in data science.
Throughout my college courses, I gained experience in programming languages such as Python, C++, and SQL. I took coursework in data structures, algorithms, and software engineering, which helped me develop my problem-solving and collaboration skills. Outside of college, I worked on several personal projects that are listed below, and a website using Visual Studio Code. These projects allowed me to explore my interests and learn new programming languages and tools. Overall, these experiences have built a strong foundation in coding and have prepared me for a career in these fields.
Here is the code that I wrote to explore data I found on the Covid-19 pandemic. I used join functions and converted data types to efficiently query the data. I used aggregate functions to examine the statistical significance in each area of the data. I used window functions and temp tables to present the return data in an significant manner. I finished by examining different contents and got outputs that we could compare data from different areas.
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In this project, I took the data from Covid-19 and created a dashboard included various graphs,charts, and maps to interpret it. I created a bar and pie charge to visualy represent the total death numbers by continent. The map is an interactive heatmap of infections per country, followed by a line graph that is a timeline representation of the percent in population that got infected in each country.
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After downloading raw data about the housing market in Nashville, Tenessee, I used SQL to produce clean and useful data that we could use to find significant information. I standardized certain data like the dates and address fields which included breaking up the address fields for better filtering and querying. I cleaned out some data by removed duplicates and deleted data that was deemed insignificant information.
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This project looks at movies and tests what factors we can find correlation between. We start with cleaning the data by deleting any null values and deleting redundencies. After sorting movies by highest gross earnings, we create a couple plot graph showing the gross earnings with the movie's budgets and critic scores. This follows with a correlation matrix between all fields of our data, and this allows us to look at what fields have the highest correlations. The project ends with code breaking down the highest contributors to those high grossing movies.
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