{"id":49176,"date":"2017-07-07T00:00:00","date_gmt":"2017-07-07T00:00:00","guid":{"rendered":"https:\/\/www.techopedia.com\/weighing-the-pros-and-cons-of-real-time-big-data-analytics\/"},"modified":"2018-04-30T17:04:59","modified_gmt":"2018-04-30T17:04:59","slug":"weighing-the-pros-and-cons-of-real-time-big-data-analytics","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/2\/31245\/technology-trends\/big-data\/weighing-the-pros-and-cons-of-real-time-big-data-analytics","title":{"rendered":"Weighing the Pros and Cons of Real-Time Big Data Analytics"},"content":{"rendered":"

In this age of data explosion, organizations are collecting and storing data at ever-increasing rates. However, simply collecting that data for your organization doesn't have any business value. Real-time analysis<\/a> and visualization<\/a> of this big data<\/a> turn this mass of data into valuable statistics. While this real-time insight can be of great value to your organization, it does have both pros and cons.<\/p>\n

What Is Big Data, and How Is It Different From Real-Time Big Data Analytics?<\/span><\/h2>\n

Before moving further, let's discuss big data – what exactly is it? Traditionally, data was stored much more easily since there was so much less of it. Big data came into existence when there became a need to store data sets<\/a> in much larger quantities. It is not only data or a data set, but a combination of tools, techniques, methods and frameworks.<\/p>\n

Big data can come from nearly anything that generates data, including search engines<\/a> and social media<\/a>, as well as some less obvious sources, like power grids and transportation infrastructure. This data can be categorized into three types: structured<\/a>, semi-structured<\/a> and unstructured<\/a>.<\/p>\n

Big data is usually collected and analyzed at predefined intervals. However, with real-time big data analytics<\/a>, the collection and analysis is continuous, giving a business up-to-the-minute insight. (For more on big data analytics, see How Big Data Analytics Can Optimize IT Performance<\/a>.)<\/p>\n

Hadoop<\/a> is the most well-known tool for analyzing big data, but it isn't well suited for handling real-time big data analytics. Some real-time big data tools include:<\/p>\n