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Project Number: MAP MXC0577Washburn Shops Lab Management System Major Qualifying Project Report Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements
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Start by collecting the raw data that needs to be manipulated and visualized.
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Organize the data into a structured format, such as a spreadsheet or database.
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Clean the data by removing any errors, duplicates, or inconsistencies.
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Explore the data to identify patterns, trends, and insights.
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Manipulate the data by performing calculations, aggregations, or transformations.
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Choose appropriate visualization techniques based on the nature and purpose of the data.
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Create visualizations using tools like charts, graphs, or maps.
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Customize the visualizations to highlight key findings and make them more understandable.
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Interpret and analyze the visualizations to draw meaningful conclusions.
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Share the results with the intended audience through reports, presentations, or interactive dashboards.

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Data manipulation is the process of modifying data to make it easier to read, interpret, or analyze. Data visualization is the graphical representation of information and data.
Data analysts, researchers, business analysts, and anyone working with data may be required to file data manipulation and visualization.
To fill out data manipulation and visualization, you can use tools like Excel, Tableau, Power BI, or programming languages like Python or R to manipulate and visualize data.
The purpose of data manipulation and visualization is to help identify trends, patterns, and insights in data, making it easier for decision-makers to understand and act upon.
The information reported on data manipulation and visualization may include data sources, data cleaning processes, data transformations, and visualizations used to convey insights.
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