Toby Geeson | Data Analyst
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As a data analyst, my objective is to leverage my skills and knowledge to solve complex real-world problems. By utilizing SQL, I can help my organization make informed decisions and streamline internal processes by collecting, interpreting, and drawing conclusions from data. This SQL project focuses on Covid-19 data and provides insights into various aspects of the pandemic. The code showcases a range of data analysis techniques, including selecting columns, performing calculations, ordering results, grouping by columns, joining tables, and creating views.
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To begin the project, I obtained the Covid-19 dataset from https://ourworldindata.org/covid-deaths in CSV format. I then reformatted the file to include information on cases, deaths, vaccinations, population, and other relevant variables. After cleaning and removing unnecessary data, I saved the information on deaths and vaccinations as two separate tables. This process involved breaking the worksheet into multiple tables and saving each as a separate Excel Workbook file.
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Next, I imported the data into Microsoft SQL Server Management Studio and created a new database named 'PortfolioProject.' Using the SQL Server Import and Export Wizard, I imported the data into the local SQL Server DB, specifically into the PortfolioProject database.
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Data cleaning
I performed several data-cleaning techniques. Initially, I identified and handled null values by either removing them or using calculated columns to impute missing values. Additionally, the 'movie time' column was represented as '2h 43m', which required transformation into numerical data by splitting the column and replacing textual values. After converting this into minutes via a measure, I created measures to calculate the average runtime of movies.
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To further refine the data, I applied filtering and conversion of columns to the correct data types in the power query editor before adding visuals in PowerBI. Finally, this was published and optimised for mobile phone.
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Steps
