Data Analytics

Big data analytics is that the use of advanced analytic techniques against terribly giant, various data sets that embody structured, semi-structured and unstructured data, from completely different sources, and in numerous sizes from terabytes to zettabytes.

Big data may be a term applied to data sets whose size or kind is on the far side the flexibility of ancient relative databases to capture, manage and method the info with low latency. massive data has one or a lot of of the subsequent characteristics: high volume, high rate or high selection. computer science (AI), mobile, social, and therefore the web of Things (IoT) area unit driving data complexness through new forms and sources of information. for instance, massive data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media β€” abundant of it is generated in real-time and at a really giant scale.

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Big data analytics in the modern world

Understanding human language by machines

Big data increases constantly – including social media, emails, texts, sensor data and more. With natural language processing, machines can sift through volumes of big data to uncover trends, analyze sentiment and identify correlations.

Big data analytics makes the world a better place

SAS is passionate about using advanced analytics to improve our future – whether addressing problems related to poverty, disease, hunger, illiteracy, climate change or education. See how we do it.

Alternative data: Risky or essential?

Alternative data is often unstructured big data of limited use in raw form. Learn why it’s so important to analyze this data to get a comprehensive and current picture of the changing business world.