Big data requires a replacement processing mode so as to possess stronger decision-making,
insight, and process optimization capabilities to adapt to massive, high rate of growth and diversification of data assets.
This concept expressed a really important meaning. Big data has now become an information asset. within the era of massive data, we’d like new processing models to process these information assets. Because the first processing mode cannot affect these data within the specified time or accuracy requirements.
Within the era of massive data, the magnitude of the info to be processed is extremely large. Currently, this magnitude is typically used for data analytics and mining on the terabyte level.
The second characteristic is named fast processing speed. It wont to take weeks, months, or maybe longer to process the info to urge the results, but now we’d like to urge the leads to a shorter time, like minutes or maybe seconds.
The third characteristic is named multiple sorts of data. the info that we could process before was usually structured, that is, two-dimensional tables. But within the era of massive data, more diverse data types got to be processed, there are structured, unstructured, and semi-structured data. These data must be processed separately or maybe mixed by big data technology.
The fourth characteristic is named a coffee data value density. the quantity of knowledge is extremely large, but there’s not much data that’s valuable to us. These data are submerged within the vast ocean of knowledge, therefore the value density of its data is comparatively low, which suggests that I want to filter and mine in many many data, but I’ll only get dozens or many useful data.
The fifth characteristic is relative to the fourth characteristic. What veracity said is that the worth of economic value is high or more real, that is, the worth of the info that’s mined is extremely high, whether it’s directly decisive for our decision-making, insight, or process optimization. So it’s more straightforward.
These 5V characteristics of massive data tell us that today’s big data refers not only to data but to data plus a series of processing techniques. we’d like to seek out and mine the a part of data that’s valuable to our add a really short time from an outsized amount of knowledge in order that we will make decisions or optimize for the work. the entire process is named big data.
What is Artificial Intelligence?
Artificial intelligence may be a unique technical system that researches technologies, develop theories, methods, and application systems for simulating the extension and expansion of human intelligence. The goal of AI research is to let machines perform some complex tasks that need intelligent humans to finish. That is, we hope that the machine can replace us to unravel some complicated tasks, not just repetitive mechanical activity but some that need human wisdom to participate in it.
Image recognition is now widely utilized in our lives. for instance, the identity of an individual is often identified supported photos or when a person’s face is captured with a camera. In many train stations in cities of China, you’ll swipe an ID card, the machine collects a face image of you with a camera, then identify and verify your identity. Some building access control uses image recognition for identification, you did not need an access card or a key.
Autonomous driving or self-driving car is additionally very fashionable within the field of AI. Google’s Waymo has already started commercial self-driving car service called “Waymo One”. Chinese Internet companies also successfully tested autonomous driving on the Fourth bypass in Beijing. Now there also are some advanced cars with modules for autonomous driving.
Big data and AI are two important branches of computing today. In recent years, research within the fields of massive data and AI has never stopped. Big data is inextricably linked with AI. First, the event of massive data technology depends on AI, because it uses many AI theories and methods. Secondly, the event of AI must also believe in big data technology, it requires plenty of data for support. Technology innovation has just begun, and there are more new technologies that we’d like to stay learning.
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