Talking about two misunderstandings in the big data industry

before the tiger sniffed an article "Big Data industry two big mistakes", many friends evaluation is good, by this incentive, combined with the recent witnessed, experienced projects, want to write more. After the author summed up, found that large data is really a lot of misunderstanding, especially in the country, many people to the false assertion, resulting in a lot of basic concepts deviation. After an article, and then to talk about a large number of errors in the data, for everyone to shoot bricks.





misunderstanding three: The amount of data is particularly large to call large data





in the "data domain" there is such a wave of people, they think "only the PETA level above the big data, even to the zeta above just called large data, is not yet to the real big data Age!" "Every time I hear that, I know these people are too much affected by the" capacity "of the 4V theory of IoE. In this respect, I would like to say the first sentence is "do not book as much as the letter, as far as the IoE", to IoE not only to start from the hardware, but also from the mind to dare to challenge the Giants, although many it's classic theory is the traditional giants, but with the emergence of the challenger, germination of new ideas and techniques, The traditional giants will be slowly overturned, which is also an important factor in our human forward. If we still stay in the era of superstitious giants, so rigid dogma to pursue a concept, then there will be no current Hadoop, there will be no current spark, there will not be now Tesla, there will be no machine learning AI, and will not have the next nth Industrial Revolution.





first of all, I would like to emphasize big data technology is really not a new word, in the previous article I have said that the nature of large data or data, the industry has been developed for several years, and the volume of data is always beyond the imagination of the times, such as more than 10 years ago, The amount of data on a floppy disk is also 1.44M, and if the data reaches 1T, it will make others raspberry. So by the amount of data, if someone had collected 1T data, would it have entered the age of large data? Obviously not! So I want to say that the size of the data is not a measure of big data, if the amount of data to judge whether large data, then the word "big data" is really a pseudo proposition, just as "tigers, such as the old, the lad must be small, the giant must be head big, the trapeze must be long wings." This is the purely literal meaning of the topic of definition.





So again, what is the concept of big data? First, large data is a complete ecosystem, from the data generation, collection, processing, summary, display, mining, push and so on to form a closed-loop value chain, and through a variety of technology processing each link, for the business scene to provide valuable applications and services. Second, what is the core of big data? On the one hand is open source, on the one hand throttling, the current large data technology is the core goal is to better meet the needs of the data through Low-cost technology (especially to deal with more unstructured data in recent years), and in order to meet the needs of the enterprise as much as possible to save investment. Say 1000 10,000, the core concept of large data or meet the application needs, there is a clear goal of the technology called productivity, no business objectives of the technology called "waste of vitality."





misunderstanding four: Large data for large data





This misunderstanding I think is the most serious. In some enterprises, the pursuit of technology must be the latest, the best, the most dazzling, we must get the international advanced, world-class to do. All enterprises, not divided into the industry and the nature of the region, all shouted "catch bat, Big data help * * * * Enterprise to achieve the target", the next is to go to IoE, and then invest in the cluster, put before a variety of high-performance minicomputer mainframe are not used, before the purchase of the O-kee authorization all stopped, Investment has been set aside overnight for decades, and more resources have been spent chasing "big data".





students, this kind of costly things to believe that everyone will hear every day or see for themselves, many enterprises regardless of cost is to BO leadership a smile, this is how big misunderstanding ah. I would like to say:





first, technically, such as bat or a lot of internet companies to pursue large data, because of business development needs. Any internet company is born to live for traffic and clicks, this means that a large amount of unstructured data needs to be processed quickly, which makes it possible for Internet companies to decompose the underlying data in a number of concurrent ways, and then to quickly process and meet the needs of their service users and markets. The business process and business model of Internet enterprises decide that large data technology must be adopted. Conversely, many enterprises do not need these technologies, some simple one or two Excel files in some of the formula can be used to meet its development, and the data cycle or monthly processing, there is no need to use these technologies.





Second, in terms of investment, Internet enterprises were born civilians, can not afford to buy large equipment, even after a rich, nor a traditional minicomputer mainframe to better meet their development, it can only find a way to create value chains and standards, in the previous low investment, lightweight architecture, Continuous small amount of linear hardware investment to meet business development. Instead, some of the traditional companies, even the Big Mac, its investment plan was clear a year ago, and on the original basis of investment will be more ROI (ROI), but now in order to pursue the slogan of large data, the sacrifice of a large amount of investment before, in addition to "outweigh the gains", the rest is only the moral integrity of the Montreal.





Large data technology even any kind of technology is to meet the specific business objectives of the birth, with a clear business objectives, homeopathy design conforms to its own business structure of the technical framework, is a scientific and healthy development concept. If you are a boss, CEO or investor, be sure to understand that large data technology for enterprises, sometimes like water, and the business goal is the ship, "the water can carry a boat, but also to overturn."





with the continuous adjustment of production relations, there will be a number of rounds of productivity progress, the technology after large data will be the rapid progress, such as the current emergence of "machine learning, in-depth learning" and many other artificial intelligence technology, also appeared such as "Small Data", "micro-data" and more fine direction of technology, in the advent of the torrent of technology, as long as a clear to meet the business-oriented mind, according to their own business needs to design their own technical framework, will not be a variety of schools, various concepts submerged.