{"id":3958,"date":"2014-01-16T07:11:07","date_gmt":"2014-01-16T06:11:07","guid":{"rendered":"http:\/\/visionarymarketing.com\/en\/blog\/?p=3958"},"modified":"2025-05-06T17:45:15","modified_gmt":"2025-05-06T15:45:15","slug":"big-data-back-to-basics","status":"publish","type":"post","link":"https:\/\/visionarymarketing.com\/en\/2014\/01\/16\/big-data-back-to-basics\/","title":{"rendered":"Big Data: there is a dire need to get back to basics"},"content":{"rendered":"

Back to basics! Belgian expert Pierre Nicolas Schwab’s piece on Big Data<\/a> is based on his past assignments with companies trying to launch such initiatives. \u00a0When I discovered Pierre Nicolas’s prose, \u00a0I must admit that I felt better for discovering that the issue of “small data<\/a>” is ubiquitous.<\/p>\n

Big Data: there is a dire need to get back to basics<\/h2>\n
\"Back
Big Data: there is a dire need to get back to basics<\/figcaption><\/figure>\n

Back to basics: according to him there are 3 common mistakes companies make when launching their big data initiatives:<\/p>\n

    \n
  1. They don’t know where the data is (actually; I would add that sometimes they do but they are not allowed to use it. Very often a specific department owns the data and prevents anyone else from using it. This is mostly true of customer data, and I even witnessed that in small and medium firms, it’s not just a big logo issue),<\/li>\n
  2. They don’t know what to do with their data: this too may seem ludicrous, but it’s true that big data requires both business\/marketing and technical acumen, and it’s pretty easy for many to get drowned in data without knowing what to do with them,<\/li>\n
  3. They’ve been told that IT is magical and you don’t need to do anything for systems will do it for you. Well, this is not true, massaging data requires a lot of work and dedication, trial and error, and also the fine tuning of data. In some cases (retail for instance), it is true though that a lot of data comes straight from check-out systems and not much needs to be done… except master data mining and very complex analytics, which often only data scientists can manage.<\/li>\n<\/ol>\n

    One last point I would add is often the poor quality of the data itself, mostly when it has been entered manually and rarely, if not never, updated properly. I have known someone who spent his entire company life updating customer databases for a large IT company, this is a never ending job… even though large databases exist, if you own the data, you need to keep it clean and up to date; this is a hug task.<\/p>\n

    How and why data analysis<\/a> can help increase your profitability and fuel your growth – Marketing<\/a>, customer satisfaction<\/a> and loyalty<\/h3>\n

    We are currently doing several big data-based assignments for very various clients and we\u2019d like to share with you common mistakes that are often made by companies when considering analyzing their data.<\/p>\n

    Mistake #1: where is my data?<\/h4>\n

    First of all what we see is that most companies have a HUGE problem finding<\/a> their data. Either they don\u2019t have collected data at all (which often is the case in retail environments and we know brands with a serious number of stores which, after having opened several sales points, realize they know nothing about their customers<\/a>, the origin of their revenues, etc \u2026 they have no chance to monitor anything. Yet they don\u2019t realize the opportunities they are missing and don\u2019t take action.
    \n…<\/p>\n

    via How and why data analysis can help increase your profitability and fuel your growth – Marketing, customer satisfaction and loyalty<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Back to basics! Belgian expert Pierre Nicolas Schwab’s piece on Big Data is based on his past assignments with companies trying to launch such initiatives. \u00a0When I discovered Pierre Nicolas’s prose, \u00a0I must admit that I felt better for discovering that the issue of “small data” is ubiquitous. Big Data: there is a dire need …<\/p>\n","protected":false},"author":2,"featured_media":70763,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4070],"tags":[4158,4661],"class_list":["post-3958","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-transformation","tag-big-data","tag-mistakes"],"yoast_head":"\nBack to basics: understanding Big Data fundamentals is a must!<\/title>\n<meta name=\"description\" content=\"Back to basics with Big data: there are 3 common mistakes companies make when launching their big data initiatives\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/visionarymarketing.com\/en\/2014\/01\/16\/big-data-back-to-basics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" 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