{"id":4244,"date":"2013-10-29T18:06:04","date_gmt":"2013-10-29T12:36:04","guid":{"rendered":"http:\/\/blog.fusioncharts.com\/?p=4244"},"modified":"2026-01-20T14:37:16","modified_gmt":"2026-01-20T09:07:16","slug":"like-it-or-not-real-time-analytics-is-here-to-stay","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/like-it-or-not-real-time-analytics-is-here-to-stay\/","title":{"rendered":"Like It or Not, Real-Time Analytics is Here to Stay 2026"},"content":{"rendered":"Over the past two months we\u2019ve been discussing predictive analytics in detail, which has generated a lot of interest from readers. Building on that start, we\u2019re now moving to another series on a related topic &#8211; Real-time data visualization.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"alignright size-medium wp-image-4251\" title=\"Real-time Clock\" alt=\"Real-time Clock\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/2013\/10\/Now-Clock-304x143.jpg\" height=\"143\" width=\"304\" \/>\u2018Real-time\u2019 has become a buzzword in recent times. Every other product we come across touts its real-time capabilities. When evaluating a new tool for your marketing, sales, or operational needs, you may have considered real-time as a necessary requirement. When reading articles on popular tech blogs, you\u2019ve probably come across the term every other day. Yet, for many, the phrase \u2018real-time\u2019 is like a popular stranger that everyone talks about, but a stranger nonetheless. They wish they knew what all the buzz is about, but don\u2019t know where to start. If that\u2019s you, this series will serve as a great starting point in your understanding of what real-time data is all about.\r\n\r\nIn this series of blog posts, we discuss how businesses are approaching real-time business intelligence in a way that empowers their decisions. We\u2019ll take a look at the various components of a real-time business intelligence system, with an emphasis on the data visualization aspect.\r\n\r\nWe begin by assessing where we are today, the role big data plays in the functioning of our businesses, and how we got here.\r\n\r\n<!--more-->\r\n<h2>The Three V\u2019s of Big Data<\/h2>\r\nWith the explosive growth of data creation in recent years, and the opportunities afforded by big data, the need for real-time business intelligence is growing by the day. IBM estimates that 90% of all the world\u2019s data has been created in the past two years alone. However, while this firehose of data hits us at ever increasing speeds, IDC observes that less than 1% of all available data is analyzed. Businesses face the problem of data, data everywhere, not a second to think.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"size-medium wp-image-4246 aligncenter\" title=\"Big Data - Volume, Velocity, and Variety\" alt=\"Big Data - Volume, Velocity, and Variety\" src=\"https:\/\/www.fusioncharts.com\/blog\/wp-content\/uploads\/2013\/10\/Big-Data-Volume-Velocity-and-Variety-304x127.jpg\" height=\"127\" width=\"304\" \/>\r\n\r\nAbout a decade ago, Gartner ushered in a new era of business intelligence when they drew a contrast between data as we knew it back then, and the way data was headed. They suggested three prominent characteristics of this new type of data called big data &#8211; volume, velocity, and variety. Since then, many have tried to add many more V\u2019s like value, veracity, and viability. We\u2019ve also seen some backlash against this \u2018wanna V\u2019 syndrome. For our purposes, we\u2019ll stick to the original definition.\r\n\r\nWhen discussing real-time analytics, while none of the three V\u2019s can be left out, velocity is of prime importance. This is because of the speed with which data is captured, stored, processed, and visualized. This velocity is what differentiates real-time analytics from traditional BI systems. The entire cycle from data capture to final action taken on it can happen in a matter of seconds, or even milliseconds.\r\n<h2>From Relational Databases to Big Data<\/h2>\r\nReal-time analytics wasn\u2019t possible a decade back. It was enough for a store owner to know how many items of a product were sold each day, and which were the fastest selling. This information aggregated over a quarter would assist with making strategic decisions, for example, about which product lines demonstrated the most growth potential. Businesses were happy to store data in relational databases, which accepted data only in a pre-defined structure. The storage and processing was heavily restricted by the ever-increasing number of physical servers. The stored data was queried weekly or monthly using SQL queries that were processed in a sequential order, making it impossible to run complex, large-scale queries. Also, these queries would return results successfully only if all databases involved were functional, and the data was stored in a consistent manner. This was never going to hold up in a world that was about to get much more complex with the advent of e-commerce, web analytics, social media, and mobile devices.\r\n\r\nFast forward to today, and the same store owner is not satisfied with getting just the history of last quarter\u2019s sales. On an operational level, they want a real-time BI system that knows what a particular customer purchased just now, what they\u2019re most likely to buy next, and which add-ons to suggest right now, before the customer\u2019s attention fades. This sort of real-time, predictive analytics wasn\u2019t possible back in the days of traditional data warehousing. But today, with vastly reduced storage prices, increased RAM capabilities, powerful querying tools, and capable visualization components, real-time analytics is becoming a reality in more and more business scenarios. It is now not only possible, but imperative that enterprises master the art of real-time business intelligence for both strategic and tactical purposes.\r\n\r\nBelow is a video that illustrates the impact of big data and real-time analytics on retailers. We\u2019ll, of course, be talking beyond just the retail industry, but this example from retail is a great starting point.\r\n\r\n\r\n\r\nWith that we conclude our introduction to this series, and will pick it up from here next week. In the upcoming posts, we\u2019ll go behind the scenes to understand what goes into the making of a real-time business intelligence system. We\u2019ll then look at some applications of real-time analytics, and scan the technological landscape to understand what makes these innovations possible. Finally, we\u2019ll put together a broad list of requirements that you can keep handy when choosing a real-time data visualization component. If any aspect of your product or business depends on real-time data, this series is a 101 in real-time analytics that you can\u2019t afford to miss.\r\n\r\nIf you can\u2019t wait for the rest of the posts, you can always get our free white paper titled \u2018<a title=\"The Ultimate Guide to Real-time Data Visualization\" href=\"https:\/\/www.fusioncharts.com\/whitepapers\/real-time-data-visuaization-guide\/\" target=\"_blank\" rel=\"noopener\">The Ultimate Guide to Real-time Data Visualization<\/a>\u2019 which covers this topic in great detail. Of course, in this blog post series we\u2019ll be including lots of practical examples, extending the thought in the white paper. So, you may want to go through the white paper to get an overview of the topic, but do stay tuned to the blog posts for in-depth treatment of each section of the white paper.","protected":false},"excerpt":{"rendered":"<p>\u2018Real-time\u2019 has become a buzzword in recent times. Every other product we come across touts its real-time capabilities. When evaluating a new tool for your marketing, sales, or operational needs, you may have considered real-time as a necessary requirement. When reading articles on popular tech blogs, you\u2019ve probably come across the term every other day. Yet, for many, the phrase \u2018real-time\u2019 is like a popular stranger that everyone talks about, but a stranger nonetheless. They wish they knew what all the buzz is about, but don\u2019t know where to start. If that\u2019s you, this series will serve as a great starting point in your understanding of what real-time data is all about.<\/p>\n","protected":false},"author":12,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[47,105,106,303,304,380],"coauthors":[696],"class_list":["post-4244","post","type-post","status-publish","format-standard","hentry","category-thoughts","tag-big-data","tag-data-visualization","tag-data-warehousing","tag-real-time","tag-real-time-analytics","tag-volume-velocity-variety"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Like It or Not, Real-Time Analytics is Here to Stay 2026<\/title>\n<meta name=\"description\" content=\"Dive into the future of real-time analytics. Explore the trends and significance of instant data analysis in our 2026 modern overview. 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