1. Big data is a new thing for a new era

The truth is that data analytics is not new at all. Since the Age of Enlightenment, hundreds of years ago, scholars have been following the scientific method to dismantle the reasons behind the formation of things, step by step. Scientists first observe, obtain and analyze data, generalize hypotheses, and then, through continuous empirical evidence, gradually form laws. So what we call big data is, at best, an application of the scientific method.

2.100TB or more is called big data

There is in fact no clear line of demarcation between the size of data. More importantly, the size of the data, doesn't necessarily mean anything. Big data doesn't mean you can make accurate predictions -- assuming you have the names, genders, birthdays, heights, weights, skin tones, eyesight, and Internet behaviors of 7 billion people on the planet -- but if you want to predict their income distribution next year, you're afraid that this huge database won't be able to help you much. So it's not the amount of data that counts, it's the task you're trying to accomplish, not the amount you're storing.

3. The data is very objective

The hardware and software that collects the data is human-designed, so it's impossible to be absolutely objective. Does the fact that your phone is stuck on a certain screen mean you're enjoying the content? It's hard to say, maybe you're just chatting with the friend next to you. Does liking a post mean you really like it? It's hard to say. Maybe you just like the person who posted it, or maybe you just accidentally clicked on it.

4. Data can tell you what you don't know

Literally, data can only tell you what you don't know. But what kind of insider knowledge it actually represents has to be interpreted by the imputers themselves. For example, if you analyze your app's user profile and find that women between the ages of 21 and 30 make up the largest portion of your app's users, it could mean that your app is most attractive to such people, but it could also mean that your promotional team is targeting such a group when they send out ads. What are the facts? Often it takes further comprehensive comparisons and experimental analysis to close in.

5. Big data is a problem for the information sector

The collection and storage of big data can indeed be categorized as the business of the information sector. But defining what to collect, how to collect it, and how to apply it after collecting it is definitely something that the business-led department should be responsible for. Asking the IT department to do a good job with big data is like asking the finance department to improve the company's profitability -- it's putting the cart before the horse.

About what misunderstandings exist in big data, Aoto editor will share with you here. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to learn more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.