


Essentials of Data Visualization and Data Scraping
There’s data, there’s information, and then there’s knowledge. Knowledge, or insight, is where we make sense out of and organize information that we have pieced together from what was just random, unstructured and otherwise useless data. Data visualization is how we describe this process by presenting data in a visual representation somewhat more advanced than simple spreadsheets, such as interactive infographics, maps, graphs and charts, making the data analysis process considerably easier. This allows for complex data groupings or concepts like patterns and relative connotations to be quickly digested. In this way, decision makers can have easier time pinpointing things which might benefit by an attention aimed at amendment, identify elements impacting consumer behaviors, determine more efficient product positioning strategies, and forecast potential gross sales revenues. The way this process benefits companies is that big data analyses can allow for identification of new avenues for generating revenue, more effective and targeted marketing campaigns, improved customer service, better organizational efficiency, and, potentially, a competitive edge over contenders in the marketplace. The Big Data Analytical Process Data visualization is the step in the big data analysis process wherein data has been gathered, usually a whole lot of it, in a process called data scraping, where web crawler bots scrape data from websites from a large variety of sources for a specific project, filtered, analyzed, and aggregated for interpretation. Once data has been scraped from a website, it is warehoused until it can be sorted through, filtered, and analyzed. At this point the role of quality data management systems becomes critical in the analytical process. Data to be warehoused then needs be...<Previous
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