{"id":1101,"date":"2015-11-20T15:24:23","date_gmt":"2015-11-20T21:24:23","guid":{"rendered":"http:\/\/www.designandexecute.com\/designs\/?p=1101"},"modified":"2022-10-11T13:53:02","modified_gmt":"2022-10-11T19:53:02","slug":"data-analysis-visualization","status":"publish","type":"post","link":"https:\/\/www.designandexecute.com\/designs\/data-analysis-visualization\/","title":{"rendered":"Data Analysis & Visualization Development Cycle"},"content":{"rendered":"

The critical steps in the Visual Analysis Cycle are<\/span><\/h1>\n
    \n
  1. Data Acquisition<\/span><\/li>\n
  2. Enhancement<\/span><\/li>\n
  3. Filtering<\/span><\/li>\n
  4. Tune<\/span><\/li>\n
  5. Delivery<\/span><\/li>\n<\/ol>\n

    The process’s longest and most challenging step is preparing the data in step2. The hardest part of the process is enhancing the data to get the data in the format to create the dashboard, analytics, or report.<\/span><\/p>\n

    It is primarily the power users that get past this hurdle to continue and derive the final product. Many users get stuck because they either do not have a vision of the final output or they do not have the data engineering skill before they hit this first obstacle.<\/span><\/p>\n

    It is a cycle, and the faster and more often you can iterate over this, the more value you will deliver with the changing data.<\/span><\/p>\n\n\n

    \n
    What is the difference between a data engineer, an analytic engineer, and a BI engineer? How does the Data Scientist compare?<\/a><\/blockquote>