Data has been around for a long time, but big data has only appeared frequently in the media press in the last 1 year. The idea that big data has big value seems to be shared by everyone. People tend to always focus on the good side of things, but tend to ignore the disadvantages that come with big data. Undoubtedly, big data can bring a lot of economic value and benefits to enterprises, institutions and other organizations, directly affecting their future direction. In fact, big data is a double-edged sword, in the enterprise to bring unbeatable forward momentum, often will also bring harm to enterprises and individuals. See the following short story: a former lover who has shown up on your chat tool as someone you may know. The above scenario is a kind of server made available through big data analytics tools, and while it's just a special case, it's embarrassing for both parties and even both families. But it is indeed real. Whether it's on our Twitter feeds, the latter chat tool, this problem occurs, and while it seems like a very convenient feature, it's a hassle for some. Here's a look at the downsides of big data. Personal privacy is threatened: for individuals, its often as a source of data in the era of big data. Whether it's an individual's life situation, or consumption habits, identity characteristics, etc., all become data stored in various forms. Although this is for enterprises to analyze data and get value based on user data, but for individual users, it is undoubtedly a thing that has to be passively accepted, and this data in the process of collecting, analyzing, and transmitting may bring negative impacts on the user. Privacy is threatened enterprises in the transmission of these private data may encounter trouble, it is difficult for enterprises to ensure that the entire transmission process whether someone will view your data, it is very likely that some people on these private data monitoring and other operations, which greatly increases the possibility of its leakage, data leakage, it is likely to bring irreparable losses for the individual, but the individual does not know when their data How to leak out of the individual user's right to privacy is an unlimited challenge. Big data is not equal to big value: only when the amount of stored data reaches a certain value will have value, even if the individual data has a certain value but not the overall reference value. This often gives enterprises an illusion that big data is set to big value. In fact, big data is not equal to big value. Big data analytics storage products and equipment often have higher requirements for enterprise IT equipment, the original enterprise IT equipment is difficult to meet the challenges of the big data era. In this case, the enterprise IT department is faced with such a situation: more and more demand, but the ability to meet these needs is getting weaker and weaker. And the value of enterprise input is inversely proportional to the value of the information obtained. When the data reaches a certain value, the value of inputs even exceeds the value of the resulting data. Big data has a greater challenge to the enterprise: in recent years, due to server failures caused by the failure to provide services from time to time, and with the advent of the era of big data, these failures may be further increased. And these failures often lead directly to a drop in data and disruption of services. Examples include Google's leakage of personal privacy, Shanda Cloud's data loss incident, Amazon's server downtime accident, and so on. When these service interruptions, the user is no solution, can only wait for the service provider's repair, and for data loss, damage and other aspects of data protection, the user is even more helpless, can only wait for the provider. In this way, many users in the event of failure and can not respond in time to minimize the loss. Undoubtedly, big data brings more challenges. Big Data makes enterprises face vendor binding: When we mention big data, we always mention the many advantages of big data, but seldom mention how enterprises will turn big data into practical value. Easily bound by vendorsAt present, many vendors have launched their own solutions for big data. And although these solutions claim to be very compatible with other vendors' equipment, when you actually adopt a provider's equipment (software, hardware), you will find that it is really difficult to change a provider, especially in terms of software. It's easy to get tied down to one provider. This greatly limits the flexibility of an organization's IT infrastructure setup. To summarize: while everything is so beautifully outlined in the era of Big Data, there is still an insurmountable gap between the road to truly delivering value to the enterprise. Big data is not imagined so perfect everywhere gold, enterprises in the next should consider how to deal with the challenges of big data, and not just talk about value.