Module summary

  1. Data analytics is the process of examining raw sets of data with the aim of deriving meaning from it
  2. Profit-driven organizations use data to monitor whether they are making profit or not. Social development organizations use data analytics to check whether they are making an impact or not
  3. Types of data analytics include descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics
  4. Data visualization is translating information into visual contexts
  5. Data visualizations are important because they are easily understood by people of various levels of proficiency in data numeracy, spur people's interest and are a good medium for distributing information. This aids in faster decision making
  6. All data visualizations are made of graphical elements such as lines, dots, circles and volumes
  7. We use graphical properties of these elements such as size, color, orientation, volume and patterns to indicate significance and to compare different values
  8. Data visualizations are used to show relationship (scatter plots, network diagrams), comparison across values (bar/column charts, parts of a whole (pie chart, icon arrays), changes over time (line charts, slopegraph), and to show location (maps)

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