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Big data analysis performs mining of useful information from large volumes of datasets. Contrary to analysis, data science makes use of machine learning algorithms and statistical methods to train the computer to learn without much programming to make predictions from big data.

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The global data sphere is believed to reach up to 175 zettabytes by 2025. There will be a massive demand for relevant professionals who interpret and manage data, and the demand for data scientists and analysts is increasing rapidly in the job market.

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Technology disruption is changing the job market faster than we could imagine. Some jobs would be simply wiped out whereas demand for others would start growing. According to the world economic forum report, one of the job that will become more and more important by 2020 is data analyst or data scientist.

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As the big data expands, it is important to know some important ways to protect yourself online. Here's how to stay technologically safe. Big Data is here to stay. From companies to hospitals, all the major actors use. In many ways, collecting big data is a good thing, but it means that personal data is now very vulnerable. Cyber security is constantly adjusted to provide new protection to meet new demands. However, you cannot just rely on software to meet your protection needs; you need to know the ways to protect yourself online. You should also adjust your online habits to protect your online safety. Learn some tips below on ways to stay safe in a big-time world.

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Can you guess how much data is produced every day? 1.145 trillion MB/day. And, it will surpass this number very quickly, considering the growing number of internet users every passing day. A source predicts that by 2025, 463 exabytes of data will be created. Isn't it crazy? It does sound so.

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Join big data online training for beginners to know how big data works. Next comes data science, but know that big data and data science are distinct yet complementary.

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Data is collected from various sources like interviews, sensors, social media, server logs, website analytics and more. This process involves understanding the data sources, obtaining an informative and thorough data set, and ensuring data quality and integrity.

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The data in its primary stage can be transformed into actionable data, which is where Applied Data Science comes into action. The course of action of turning raw data into meaningful insights is known as Applied Data Science. It investigates data to provide functional solutions to business problems through the application of abstract frameworks and algorithms on primary data. It uses scientific methods to develop questions for research and then carry out studies that lead to decoding solutions.

The data in its primary stage can be transformed into actionable data, which is where Applied Data Science comes into action. The course of action of turning raw data into meaningful insights is known as Applied Data Science. It investigates data to provide functional solutions to business problems through the application of abstract frameworks and algorithms on primary data. It uses scientific methods to develop questions for research and then carry out studies that lead to decoding solutions.

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The data in its primary stage can be transformed into actionable data, which is where Applied Data Science comes into action. The course of action of turning raw data into meaningful insights is known as Applied Data Science. It investigates data to provide functional solutions to business problems through the application of abstract frameworks and algorithms on primary data. It uses scientific methods to develop questions for research and then carry out studies that lead to decoding solutions.

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