Basics of Data analysis¶
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Who is involved: Data analysis can involve various stakeholders, including data analysts, data scientists, domain experts, and decision-makers. Each plays a different role in understanding and utilizing the data insights.
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How to collect data: Data can be collected from different sources, such as surveys, databases, APIs, web scraping, sensors, or logs. It's essential to ensure data quality, accuracy, and privacy during the collection process.
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Understanding the context: Before diving into analysis, it's crucial to understand the context and the problem you're trying to solve. This involves collaborating with domain experts to gain insights into the data's significance.
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Metrics for analysis: Metrics are the quantitative measures used to evaluate performance and draw conclusions. They can be simple, like counts and averages, or more complex, like conversion rates and predictive accuracy.
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Representing data and KPIs: To present data effectively, you can use various visualizations, such as bar charts, line graphs, scatter plots, pie charts, heatmaps, etc. Key Performance Indicators (KPIs) are specific metrics used to track progress toward goals and can be displayed on dashboards or reports.
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Correct way of representation: When representing data, it's essential to choose the appropriate visualization that conveys the information clearly and accurately. Avoid cluttered or misleading graphs and charts, and provide context and labels for easy understanding.