On average, some 200 or so tweets are sent each day while Google receives around 2.4 million search requests every minute. Britain’s Department of Health generates some 200GB of data from sequencing 100,000 genomes while Walmart generates some 2.5 petabytes of data due to its 1 million customer transactions each hour. And all this data can go on and on anywhere in the world, but then, with billions of data being stocked or moving back and forth, who will analyze all this data and how will it be done?

It’s done by analytics, or as it is commonly called, data analytics. Analytics is simply the process of examining all data and data sets in order to make conclusions based on the information contained in all this data. Since manual analysis is impossible when shifting and analyzing millions of data, specialized systems and software is used. Large scale techniques for analytics are often widely used by commercial industries to enable organizations and companies to make better-informed business decisions and by researchers and scientists to verify or disprove hypothesis and theories.

Analytics or data analytics may refer to an assortment of applications such as basic business intelligence, reporting and online analytical processing, various forms of advanced analytics, and business analytics.

Data analytics can help businesses and companies increase revenues, improve operational efficiency, optimize marketing campaigns and customer service, respond faster to emerging market trends, boost business performance, and gain a competitive edge over business competitors. Data that is analyzed usually commonly consists of historical records or new information that is real-time, has been processed, or is about to be processed. All this data can also come from either external or internal sources. These data can come from wide range sources such as sensor networks, scientific experiments, social media, or even medicine, and can be diverse such as basic computer data, speeches, videos, text messages, spreadsheets, and other formats.

Thus, data analytics can focus on managing vast amounts of information and transforming it into knowledge so action can be taken. For instance, marketing data about customers can provide business and corporate executives with actionable information on how to sell their products.

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