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Xiao Ming is here again

Xiao Ming took the examination paper given by Daming:

Want to switch to big data? Have you figured out the 66 questions? (juejin.cn)

Look at the first question:

1. Can you talk about your understanding of big data? What is big Data?Copy the code

“If I knew what big data was, WHY would I worry about changing careers? Just do it!”

“Never mind, guess.”

“I just thought of a lyric. Grass, wandering again.”

Xiao Ming replied:

Big data should be big data.

Daming sees here:

“This?”

Xiao Ming smiled bitterly:

“What else? I do Java backend, big data is also from the mobile phone TV know, can only guess.

Daming looked at Xiao Ming for a while and sighed:

“Well, I wouldn’t even talk to you if your mom and mine weren’t close friends and my mom hadn’t been nagging me for days.”

“Let me give you a brief summary of big data, you listen to, of course, ugly words to say in front of me, I have not done big data for a few years, I will simply talk to you about my understanding of big data.

The body of the

  1. Big data is a technology ecosystem built around huge data
  2. Big data is essentially a technology
  3. At the heart of big data is data
  4. The core value of big data is the use of cheap machines to process and analyze large-scale data

Daming went on to explain:

Big data, in essence, is a technology ecosystem built around massive data (Volumn), including data collection, transmission, calculation, analysis, scheduling, storage, etc.

In the early stage, this data level was only GB level, but with the development of technology, it has gradually risen to TB and PB level.

What’s more, the data comes from a Variety of sources.

In general, big data comes from four sources:

  1. Internet, including mobile phones, computers and so on
  2. The enterprise data
  3. The Internet of Things, one of the core technologies of the future
  4. Scientific research

There are also a variety of forms, such as text, audio, video and so on.

So large amount of data, using the traditional stand-alone cannot store down, but the super computer is too expensive ($one hundred million) for the unit, not conducive to the development and popularization of big data, therefore, the tide of history pushing towards “more nodes” big data, only the more cheap machine (ten thousand yuan) for the unit to store such huge amount of data, To meet the needs of most companies, but it is not easy to unify such a large number of machines into a comprehensive service cluster.

In addition, people are gradually aware of the infinite Value contained in big data. As a simple example, you’ve used Toutiao, right? Big data was instrumental in the development of Toutiao, because Toutiao was one of the first companies to realize that there was infinite value in big data, so it worked. The headlines also applied what they learned to Douyin, so douyin also worked.

In addition, as more and more enterprises invest in the development of big data, and more and more scenarios need to be supported by big data, the speed and timeliness of data processing will also be higher. Because a lot of data is time-limited, for example, you walk, walk to a place, if the data is not processed in time, you walk to another place to push the nearby stores, it will be too late. Another example is a more typical time requirement of the higher scene – real-time fraud prevention, the payment time is so long, the user waits for a few seconds at most, you in a few seconds in addition to complete the basic payment logic, can not real-time fraud detection, such as the user to send the money in the past is too late.

As it turns out, the value of much data decreases over time, and the storage cost of storing historical data is higher, so real-time streaming technologies that support faster processing speeds are increasingly favored by enterprises.

In fact, the four V’s I mentioned above:

  1. Volume
  2. Variety
  3. Value
  4. Velocity

Are the four most typical characteristics of big data.

At this point, you basically have a basic understanding of big data.

Xiao Ming:

Daming:

“Great! I got it! Hey hey, suddenly a little like Xiao Ming.”