{"id":156634,"date":"2023-12-12T06:01:00","date_gmt":"2023-12-12T06:01:00","guid":{"rendered":"https:\/\/www.henryharvin.com\/blog\/?p=156634"},"modified":"2025-12-23T06:55:32","modified_gmt":"2025-12-23T06:55:32","slug":"big-data-technologies-that-you-need-to-know","status":"publish","type":"post","link":"https:\/\/www.henryharvin.com\/blog\/big-data-technologies-that-you-need-to-know\/","title":{"rendered":"Top Big Data Technologies that You Need to Know in 2026"},"content":{"rendered":"\n

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Do you post Instagram reels? Like your friend\u2019s Facebook post? If so, you just created data on the internet. Now and then, an infinite quantity of data is generated worldwide. We know tape drives to cloud storage numerous methods are used for handling the data. But what is Big data<\/a>? In recent years many of us may hear the word big data and Top big data technologies are depicted as a demanding future. The data which cannot be stored, processed, and analysed by the traditional system in a given time is called big data. Dealing with complex and massive amounts of data requires the use of big data technologies and tools.<\/span><\/h2>\n\n\n\n

           The scale of big data differs from organisation to organisation, time to time, and system to system. This means a particular figure cannot be fixed to call it big data. For instance, if a pen drive only has 1 GB of storage space and 1.5 GB of data must be kept there, the remaining 0.5 GB is considered big data for that specific device. Here, Big data technologies enter as a saviour and manage an infinite number of databases. From maintaining an organization’s database to disaster management, the role of big data technologies is inevitable.<\/span><\/p>\n\n\n\n

\"Big<\/figure><\/div>\n\n\n\n

Big data technologies are designed to handle all types of data. The types of data include<\/span><\/p>\n\n\n\n

  1. Structured data<\/span><\/li>
  2. Semi-structured data<\/span><\/li>
  3. Unstructured data<\/span><\/li><\/ol>\n\n\n\n

     <\/span>Structured data<\/b><\/h4>\n\n\n\n

    The data in which information is predefined, organized, and easy to access and the process is Structured data. A few examples are<\/span><\/p>\n\n\n\n

    • Phone numbers (10 digits)<\/span><\/li>
    • Name of an individual (First name, middle name, last name)<\/span><\/li>
    • Banking information, etc.,<\/span><\/li><\/ul>\n\n\n\n

      Semi-structured data<\/b><\/h4>\n\n\n\n

      The data which has the properties of both structured data and unstructured data is semi-structured. This does not require a predefined, fixed schema but it is more flexible. It is often described as a self-describing structure that evolves when new attributes are added and have nested information. <\/span><\/p>\n\n\n\n

      • HTML code, graphs and tables, e-mails, Zipped files<\/span><\/li>
      • JSON, CSV, XML<\/span><\/li>
      • Electronic data interchange (EDI), etc.,<\/span><\/li><\/ul>\n\n\n\n

        Unstructured data<\/b><\/h4>\n\n\n\n

         <\/span>The textual or un-textual data created by either humans or machines contributes to unstructured data. The majority of big data is unstructured data that does not have a predefined data model or a particular format. For example,<\/span><\/p>\n\n\n\n

        • Web pages<\/span><\/li>
        • Text files<\/span><\/li>
        • Audio files<\/span><\/li>
        • Videos<\/span><\/li>
        • PowerPoint presentations<\/span><\/li>
        • Images (GIF, JPEG, etc.,) <\/span><\/li>
        • Online data created by customers and many more<\/span><\/li><\/ul>\n\n\n\n

          Top Big Data technologies<\/span><\/h2>\n\n\n\n