The era of big data has arrived, what are the principles of data dissemination? Scientific progress is increasingly driven by data, and massive amounts of data bring opportunities and new challenges to data analysis. Big data is usually obtained by combining information from multiple sources at different times using multiple technologies and methods. What are the core principles of Big Data technologies? Data as value is a highly respected concept in the field of computing. Data is more or less relegated to Big Data, data analytics is getting hotter and capital is pouring in to companies with Big Data labels. With mobile digital currencies being repeatedly evaluated and pushed. Data can tell us about each customer's propensity to spend, what they want, what they like, how each person's needs differ, and what can be categorized.

In the era of big data, the computing paradigm has also shifted from a "process" core to a "data" core. the distributed computing framework of the Hadoop system has always been a "data" centric paradigm. Unstructured data and analytics requirements will change the way IT systems are upgraded from simple incremental to architectural changes. New Thinking with Big Data - Changing Computing Paradigms. Scientific advances are increasingly data-driven, and massive amounts of data present opportunities and new challenges for data analytics. Big data is often obtained by combining information from multiple sources at different times using multiple technologies and methods. To meet the challenges posed by big data, we need new statistical thinking and computational methods.

What's really interesting about big data is that it becomes online, which is the nature of the Internet. In the non-Internet era, functionality had to be its value, and with today's Internet products, data has to be its value. Data can tell us about each customer's propensity to consume, what they want, what they like, how each person's needs differ, things that can be categorized. Big data is the increase in the amount of data so that we can go from quantitative to qualitative.

There's so much data, so much data, that people feel empowered enough to grasp the future, a sense of uncertainty, to make their own decisions. This all sounds very primitive to us, but the thinking behind it is actually very similar to what we're talking about today with big data.