{"id":109,"date":"2020-09-01T05:08:04","date_gmt":"2020-09-01T05:08:04","guid":{"rendered":"https:\/\/www.sagaratechnology.com\/blog\/?p=109"},"modified":"2023-03-27T04:10:48","modified_gmt":"2023-03-27T04:10:48","slug":"an-introduction-to-big-data-concepts","status":"publish","type":"post","link":"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/","title":{"rendered":"An Introduction to Big Data Concepts"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" loading=\"lazy\" width=\"1170\" height=\"540\" src=\"https:\/\/sagaratechnology.com\/blog\/wp-content\/uploads\/2023\/03\/image-20.png\" alt=\"\" class=\"wp-image-3852\"\/><\/figure>\n\n\n\n<p id=\"f566\"><a href=\"https:\/\/www.guru99.com\/what-is-big-data.html\" target=\"_blank\" rel=\"noreferrer noopener\">Big data<\/a>\u00a0is a blanket term for the non-traditional strategies and technologies needed to gather, organize, process, and gather insights from large datasets. While the problem of working with data that exceeds the computing power or storage of a single computer is not new, the pervasiveness, scale, and value of this type of computing have greatly expanded in recent years.<\/p>\n\n\n\n<p id=\"87bd\">In this article, we will talk about big data on a fundamental level and define common concepts. We will also take a high-level look at some of the processes and technologies currently being use in this space.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_76 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69ff8bd9b84cb\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69ff8bd9b84cb\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/#What_Is_Big_Data\" >What Is Big Data?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/#Why_Are_Big_Data_Systems_Different\" >Why Are Big Data Systems Different?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/#Other_Characteristics\" >Other Characteristics<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/#Why_It_Is_Important\" >Why It Is Important?<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"0996\"><span class=\"ez-toc-section\" id=\"What_Is_Big_Data\"><\/span><strong>What Is Big Data?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"4fd5\">An exact definition of <strong>big data<\/strong> is difficult to nail down because projects, vendors, practitioners, and business professionals use it quite differently. With that in mind, generally speaking, that\u00a0is:<\/p>\n\n\n\n<ul>\n<li>large datasets<\/li>\n\n\n\n<li>the category of computing strategies and technologies that are used to handle large datasets<\/li>\n<\/ul>\n\n\n\n<p id=\"606b\">In this context, <strong>a large dataset<\/strong> means a dataset too large to reasonably process or store with traditional tooling or on a single computer. This means that the common scale of big datasets is constantly shifting and may vary significantly from organization to organization.<\/p>\n\n\n\n<h2 id=\"59ae\"><span class=\"ez-toc-section\" id=\"Why_Are_Big_Data_Systems_Different\"><\/span><strong>Why Are Big Data Systems Different?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"d574\">The basic requirements for working with big data are the same as the requirements for working with datasets of any size. However, the massive scale, the speed of ingesting and processing, and the characteristics of the data that must be dealt with at each stage of the process present significant new challenges when designing solutions. The goal of most that systems is to surface insights and connections from large volumes of heterogeneous that would not be possible using conventional methods.<\/p>\n\n\n\n<p id=\"86ed\">In 2001, Gartner\u2019s Doug Laney first presented what became known as the \u201c<strong>three Vs of big data<\/strong>\u201d to describe some of the characteristics that make different from other data processing:<\/p>\n\n\n\n<p id=\"673b\"><strong>Volume<\/strong>: Organizations collect data from a variety of sources, including business transactions, smart (IoT) devices, industrial equipment, videos, social media and more. In the past, storing it would have been a problem \u2014 but cheaper storage on platforms like data lakes and Hadoop have eased the burden.<\/p>\n\n\n\n<p id=\"aa6e\"><strong>Velocity<\/strong>: With the growth in the Internet of Things, data streams into businesses at an unprecedent speed and must be handle in a timely manner. RFID tags, sensors, and smart meters are driving the need to deal with these torrents of data in near-real-time.<\/p>\n\n\n\n<p id=\"3dc3\"><strong>Variety<\/strong>: Data comes in all types of formats \u2014 from structured, numeric, in traditional databases to unstructured text documents, emails, videos, audios, stock ticker, and financial transactions.<\/p>\n\n\n\n<h2 id=\"d58a\"><span class=\"ez-toc-section\" id=\"Other_Characteristics\"><\/span><strong>Other Characteristics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"3acb\">Various individuals and organizations have suggested expanding the original three Vs, though these proposals have tended to describe challenges rather than qualities. Some common additions are:<\/p>\n\n\n\n<p id=\"0ef4\"><strong>Veracity<\/strong>: The variety of sources and the complexity of the processing can lead to challenges in evaluating the quality of the database (and consequently, the quality of the resulting analysis)<\/p>\n\n\n\n<p id=\"7e0b\"><strong>Variability<\/strong>: Variation in the data leads to a wide variation in quality. Additional resources may be need to identify, process or filter low-quality to make it more useful.<\/p>\n\n\n\n<p id=\"c0a1\"><strong>Value<\/strong>: The ultimate challenge of big data is delivering value. Sometimes, the systems and processes in place are complex enough that using the database and extracting actual value can become difficult.<\/p>\n\n\n\n<h2 id=\"9914\"><span class=\"ez-toc-section\" id=\"Why_It_Is_Important\"><\/span><strong>Why It Is Important?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"2f16\">The importance of that doesn\u2019t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine with high-powered analytics, you can accomplish business-related tasks such as:<\/p>\n\n\n\n<ul>\n<li>Determining root causes of failures, issues, and defects in near-real-time.<\/li>\n\n\n\n<li>Generating coupons at the point of sale based on the customer\u2019s buying habits.<\/li>\n\n\n\n<li>Recalculating entire risk portfolios in minutes.<\/li>\n\n\n\n<li>Detecting fraudulent behavior before it affects your organization.<\/li>\n<\/ul>\n\n\n\n<p id=\"26d9\">Big data\u00a0is a broad, rapidly evolving topic. While it is not well-suited for all types of computing, many organizations are turning to that for certain types of workloads and using it to supplement their existing analysis and business tools. This is a systems are uniquely suited for surfacing difficult-to-detect patterns and providing insight into behaviors that are impossible to find through conventional means. By correctly implementing systems that deal, organizations can gain incredible value from data that is already available.<\/p>\n\n\n\n<p>Read also <a href=\"https:\/\/sagaratechnology.com\/blog\/\" target=\"_blank\" rel=\"noreferrer noopener\">more Sagara&#8217;s Article here. <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big data\u00a0is a blanket term for the non-traditional strategies and technologies needed to gather, organize, process, and gather insights from large datasets. While the problem of working with data that exceeds the computing power or storage of a single computer is not new, the pervasiveness, scale, and value of this type of computing have greatly&#8230;<\/p>\n","protected":false},"author":14,"featured_media":115,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[32,34,35,36,33],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>An Introduction to Big Data Concepts - Sagara Asia Blog<\/title>\n<meta name=\"description\" content=\"Big data\u00a0is a blanket term for the non-traditional technologies needed to gather, organize, process, and gather insights from large datasets.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sagaratechnology.com\/blog\/an-introduction-to-big-data-concepts\/\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"An Introduction to Big Data Concepts - 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