{"id":7223,"date":"2021-09-13T10:44:36","date_gmt":"2021-09-13T10:44:36","guid":{"rendered":"https:\/\/www.webtechmantra.com\/?p=7223"},"modified":"2023-11-28T06:03:43","modified_gmt":"2023-11-28T06:03:43","slug":"big-data-architecture","status":"publish","type":"post","link":"https:\/\/www.webtechmantra.com\/big-data-architecture\/","title":{"rendered":"An Overview of Big Data Architecture"},"content":{"rendered":"<p>As the growth of technology is increasing, most industries are upgrading their service. <strong>Big data architecture<\/strong> is very important for these industries as they can save records by using this system.<\/p>\n<p>The data revolution has changed our digital world. The growth has started in the early 2000s as data scientists are trying to generate more data in a smaller space. This is why they designed DBMS (database management system). It has become cost and time-efficient.<\/p>\n<p>In this article, we are covering what is <strong>big data architecture<\/strong>, layers, best practices, and how to build one. Hence, you will get a complete overview by reading this article. Let\u2019s get started.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_61 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title \" >Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><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><\/span><\/a><\/span><\/div>\n<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:\/\/www.webtechmantra.com\/big-data-architecture\/#What_is_Big_Data_Architecture\" title=\"What is Big Data Architecture?\">What is Big Data Architecture?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Big_Data_Architectures_advantages\" title=\"Big Data Architecture&#8217;s advantages\">Big Data Architecture&#8217;s advantages<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Big_Data_Architecture_Layers\" title=\"Big Data Architecture Layers\">Big Data Architecture Layers<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Sources_Layer\" title=\"Sources Layer\">Sources Layer<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Management_Storage_Layer\" title=\"Management &amp; Storage Layer\">Management &amp; Storage Layer<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Consumption_Layer\" title=\"Consumption Layer\">Consumption Layer<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Analysis_Layer\" title=\"Analysis Layer\">Analysis Layer<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Big_Data_Architecture_Best_Practices\" title=\"Big Data Architecture Best Practices\">Big Data Architecture Best Practices<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Preliminary_Step\" title=\"Preliminary Step\">Preliminary Step<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Big_Data_API\" title=\"Big Data API\">Big Data API<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#User_Interface_Service\" title=\"User Interface Service\">User Interface Service<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Data_Sources\" title=\"Data Sources\">Data Sources<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#How_to_Build_a_Big_Data_Architecture\" title=\"How to Build a Big Data Architecture\">How to Build a Big Data Architecture<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#1_Analyze\" title=\"1. Analyze\">1. Analyze<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#2_Select_a_Vendor\" title=\"2. Select a Vendor\">2. Select a Vendor<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#3_Capacity_Planning\" title=\"3. Capacity Planning\">3. Capacity Planning<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#4_Disaster_Recovery_Planning\" title=\"4. Disaster Recovery Planning\">4. Disaster Recovery Planning<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#Conclusion\" title=\"Conclusion \">Conclusion <\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.webtechmantra.com\/big-data-architecture\/#FAQS\" title=\"FAQ\u2019S\">FAQ\u2019S<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"What_is_Big_Data_Architecture\"><\/span><strong>What is Big Data Architecture?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>In simple words, <strong>big data architecture<\/strong> works as the foundation of big data analytics. Data scientists use this overarching system to manage a large number of data. It can provide an environment where people can store vital business information. The architecture includes four big data layers.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Big_Data_Architectures_advantages\"><\/span><b>Big Data Architecture&#8217;s advantages<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><b>1. Using parallel processing to increase performance<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Big data architectures use parallel computing, in which multiple multiprocessor servers carry out calculations simultaneously, to process enormous data volumes quickly. Large problems are divided into smaller components that can be tackled at the same time.<\/span><\/p>\n<p><b>2. Flexibility in scaling<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Big Data architectures allow the environment to be scaled horizontally to accommodate the magnitude of each application. Big Data solutions are typically operated in the cloud, where you only pay for the computing and storage resources that you really utilise.<\/span><\/p>\n<p><b>3. Individual discretion<\/b><\/p>\n<p><span style=\"font-weight: 400;\">For use in Big Data architectures, the industry offers a variety of platforms and solutions, including Azure managed services, MongoDB Atlas, and Apache technologies. Combining solutions will yield the the most appropriate choice for your diverse workloads, installed systems, and IT skill sets.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">4.<\/span><b> Compatibility with associated systems<\/b><\/p>\n<p><span style=\"font-weight: 400;\">By utilising Big Data architectural components for IoT processing, BI, and analytics processes, you may construct integrated platforms across many types of workloads.<\/span><\/p>\n<p style=\"text-align: right;\"><strong>[Read more: <a href=\"https:\/\/www.webtechmantra.com\/big-data-in-healthcare\/\">Big Data in Healthcare \u2013 Everything You Need to Know<\/a>]<\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Big_Data_Architecture_Layers\"><\/span><strong>Big Data Architecture Layers<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>As we mentioned above, <strong>big data architecture<\/strong> has four logical layers. Let\u2019s find out how these layers work in the following:<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Sources_Layer\"><\/span><strong>Sources Layer<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>This environment manages both real-time and batch processing of big data sources. It can process relational database management systems, IoT devices, and data warehouses.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Management_Storage_Layer\"><\/span><strong>Management &amp; Storage Layer<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>This layer receives data from various sources. Moreover, it converts data to make it compatible with analytics tools. The management and storage layer also store the data as per its format.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Consumption_Layer\"><\/span><strong>Consumption Layer<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The consumption layer can receive results from the analytics tools. Plus, it will present the result to the pertinent output layer.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Analysis_Layer\"><\/span><strong>Analysis Layer<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>This layer is also essential for extracting business intelligence from the storage layer.<\/p>\n<p style=\"text-align: right;\"><strong>[ Read more:\u00a0<a href=\"https:\/\/www.webtechmantra.com\/big-data-for-small-businesses\/\">How Can Small Businesses Leverage Big Data?<\/a>]<\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Big_Data_Architecture_Best_Practices\"><\/span><strong>Big Data Architecture Best Practices<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Before you design database architecture, you need to understand the value of this system. Moreover, you also need to understand how to use the data for your business. This is why you need to implement the following <strong>big data architecture<\/strong> principles:<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Preliminary_Step\"><\/span><strong>Preliminary Step<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Your company\u2019s big data project should understand the value and vision of your business. On the other hand, it needs to understand architecture principles, framework, and work requirements. In some cases, big data reference architecture should have a good understanding of the business landscapes.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Big_Data_API\"><\/span><strong>Big Data API<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Checking data service API is also essential to practice before choosing a database solution. Make sure you are checking if the database solution has standard query language. Also, understand how to connect the database, the scalability, and security mechanisms.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"User_Interface_Service\"><\/span><strong>User Interface Service<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>An ideal <strong>big data architecture<\/strong> should be customizable. This means the database should be accessible for the cloud and people can use the dashboards. So, before you are choosing a database, make sure you are checking the user interface service.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Data_Sources\"><\/span><strong>Data Sources<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Before a database is designed, you need to consider the data sources. It\u2019s essential because the database can normalize the data to a common format. Moreover, you need to consider this practice as it can take care of both structured and unstructured data.<\/p>\n<p style=\"text-align: right;\"><strong>[Read more:\u00a0<a href=\"https:\/\/www.webtechmantra.com\/big-data-security\/\">What is Big Data Security? Top Challenges and Solutions<\/a>]<\/strong><\/p>\n<h2><span class=\"ez-toc-section\" id=\"How_to_Build_a_Big_Data_Architecture\"><\/span><strong>How to Build a Big Data Architecture<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>To design big data reference architecture, you need to follow some crucial steps. Let\u2019s find out how to design an architecture:<\/p>\n<h3><span class=\"ez-toc-section\" id=\"1_Analyze\"><\/span><strong>1. Analyze<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The foremost thing you need to do is analyze the problem. A business can have various big data problems such as data velocity, variety, and challenges. Moreover, your business can face other problems with the current system including data warehouse modernization, data lake implementation, data archival, and unstructured data processing.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"2_Select_a_Vendor\"><\/span><strong>2. Select a Vendor<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The next step of building a <strong>big data architecture<\/strong> is very crucial. If you are a beginner, it would be good if you are choosing Hadoop. This is one of the best big data reference architecture tools. So, you can easily manage your company\u2019s big data. Hadoop manages data of some popular companies such as Hortonworks, Microsoft, Amazon Web Services, and Mapr.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"3_Capacity_Planning\"><\/span><strong>3. Capacity Planning<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Capacity planning is another crucial step when you are designing architecture. Before designing, make sure you are considering data volume and daily ingestion volume. Moreover, you need to consider multi-data center deployment and data retention period as well. Plus, make sure you are also considering the time period.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"4_Disaster_Recovery_Planning\"><\/span><strong>4. Disaster Recovery Planning<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Last but not least, disaster recovery planning is essential for every database. Your company needs a backup plan for critical data storage. On the other hand, you need to consider some other things such as multi-datacenter deployment, backup interval, and more.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion <\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Finally, you know about how to build a <strong>big data architecture<\/strong>, layers, and best practices. You see, this architecture could be very helpful, especially for business information. If you want this system for your company, make sure you are contacting top data scientists. For more information, you can start your research.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"FAQS\"><\/span><b>FAQ\u2019S<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><b>What three categories of big data exist?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Structured data, unstructured data, and semi-structured data are the three categories into which big data is separated.<\/span><\/p>\n<p><b>What are big data&#8217;s four characteristics?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Volume, velocity, diversity, and veracity are the four traits that most commonly characterise big data today.<\/span><\/p>\n<p><b>What is a big data example?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Big data is derived from a variety of sources, including customer databases, transaction processing systems, documents, emails, medical records, clickstream logs on the internet, mobile apps, and social networks.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>As the growth of technology is increasing, most industries are upgrading their service. Big data<\/p>\n","protected":false},"author":1,"featured_media":7224,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1187,11],"tags":[54,1397,1394,1395,1396],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>An Overview of Big Data Architecture<\/title>\n<meta name=\"description\" content=\"Big data architecture is very important for the industries that are upgrading for the data revolution in the digital world. 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