{"id":54803,"date":"2020-06-22T13:17:53","date_gmt":"2020-06-22T12:17:53","guid":{"rendered":"https:\/\/www.clickworker.com\/?page_id=54803"},"modified":"2022-11-23T11:52:00","modified_gmt":"2022-11-23T10:52:00","slug":"data-exploration","status":"publish","type":"page","link":"https:\/\/www.clickworker.com\/ai-glossary\/data-exploration\/","title":{"rendered":"Data Exploration"},"content":{"rendered":"<section class=\"white section-space top_grey_separation_sm\">\r\n<div class=\"container\">\r\n<div class=\"row\">\r\n<div class=\"col-lg-6\">\r\n\r\n<span class=\"gl_letter_offcanvas gl_single\">D<\/span>\r\n<h1 class=\"section-headline pt-4 mt-1 mb-4\"><span class=\"gl_single_headline\">Data Exploration<\/span><\/h1>\r\n<ul>\r\n \t<li><a href=\"#explanation\">Data Exploration \u2013 Short Explanation<\/a><\/li>\r\n \t<li><a href=\"#world\">Understanding Data Exploration in the Real World<\/a><\/li>\r\n\t<li><a href=\"#AI\">How Data Exploration Works in the World of AI<\/a><\/li>\r\n\r\n<\/ul>\r\n<\/div>\r\n\t\r\n<div class=\"col-lg-6\">\r\n\t\t\t <img decoding=\"async\" src=\"https:\/\/www.clickworker.com\/wp-content\/uploads\/2020\/06\/Data-Exploration.png\" alt=\"Data Exploration\" class=\"gl_image max-width-100\"\/><\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n\r\n\r\n<section class=\"gray section-space\">\r\n<div class=\"container\">\r\n<div class=\"row\">\r\n<div class=\"col-lg-12\">\r\n<h2 class=\"section-headline mb-4\" id=\"explanation\">Data exploration \u2013 Short Explanation<\/h2>\r\n<p><strong>Data exploration<\/strong> is a critical step in Artificial Intelligence and Machine Learning. With data exploration, analysts attempt to find patterns and details in large pools of data. Data exploration uses a mix of different manual and automated techniques and processes. Its function is not to sort all the data, but rather look specifically for the broad picture strokes that are evident within the data. \r\n<\/p>\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n<section class=\"white section-space bottom_grey_separation_sm\">\r\n\r\n\r\n<div class=\"container\">\r\n<div class=\"row\">\r\n<div class=\"col-lg-12\">\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"world\">Understanding Data Exploration in the Real World<\/h2>\r\n<p>Data exploration tries to make clear that the quality of data matters and the <a href=\"https:\/\/en.wikipedia.org\/wiki\/Garbage_in,_garbage_out\" rel=\"noopener noreferrer\" target=\"_blank\">garbage-in, garbage-out<\/a> (GIGO) rule applies. Within data exploration that is basically a host of different methods used to analyze data, in many cases, the tools are used multiple times to further streamline the information found. For example, within a single set of data, analysts would be looking for:<\/p>\r\n<ul>\r\n<li><strong>Values<\/strong> \u2013 what are the different values present in the data and how can the data be represented to highlight them?<\/li>\r\n<li><strong>Quantity<\/strong> \u2013 how many times is the unique value represented in the data set? What is the overall frequency and count?<\/li>\r\n<li><strong>Statistical Analysis<\/strong> \u2013 tools like the mean, median and mode are used to understand the variance in the data and what the overall spread is.<\/li>\r\n<li><strong>Data Analysis<\/strong> \u2013 tools like Pareto (80\/20 rule) are used to further categorize important information and data. In addition, by using histograms and heat maps, analysts are able to quickly identify relevant and applicable data to find correlations.<\/li>\r\n<li>D<strong>ata Clustering<\/strong> \u2013 the world is full of data and the amount available is only increasing. Data clustering lets us look at data correlations from a high level and thus enables focus on groups of data instead on specific data points.<\/li> \r\n<li><strong>Data Outliers<\/strong> \u2013 at times, some data simply does not match. In this case, it is known as an outlier or an anomaly and generally represents an exception. It is important to understand outliers also however, as, while they may be rare, they could happen and plans should be created to deal with them. A good example of this is an outage in a technical department.<\/li>\r\n<\/ul>\r\n<p>Once all of these techniques were used, they are run again, many times over to verify the initial hypothesis or in some cases disprove it. While it can take a significant amount of time, it is an excellent way of using real information to build a strategic case.<\/p>\r\n\r\n\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"AI\">How Data Exploration Works in the World of AI<\/h2>\r\n<p>When considering AI, it is important to recognize that data input plays a critical role. In the early stages, data is used to teach and educate AI systems. In this case, data that is incorrectly tagged can impact AI systems significantly leading to false positives or worse. However, when it comes to data exploration, AI is instrumental in saving time. AI systems can quickly find patterns in data and identify correlations as well as outliers.   <\/p>\r\n\r\n\r\n\r\n\t<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>","protected":false},"excerpt":{"rendered":"<p>D Data Exploration Data Exploration \u2013 Short Explanation Understanding Data Exploration in the Real World How Data Exploration Works in the World of AI Data exploration \u2013 Short Explanation Data exploration is a critical step in Artificial Intelligence and Machine Learning. With data exploration, analysts attempt to find patterns and details in large pools of [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":0,"parent":54483,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"blank_with_breadcrumb.php","meta":{"footnotes":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data Exploration - Term explanation in the AI glossary<\/title>\n<meta name=\"description\" content=\"Data exploration is a critical step in Artificial Intelligence and Machine Learning. 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