What are the requirements for big data learning? What are the requirements for learning big data

To learn big data, the minimum requirement is to recruit a junior college, which is also the minimum educational requirement for enterprise employment. Due to the scarcity of talents in the big data industry, enterprises mainly rely on the technical strength of individuals, so there are fewer restrictions on academic qualifications. Of course, a bachelor's degree or a graduate degree will be more advantageous.

1. At present, many big data courses are developed according to the zero foundation.

2. At present, more than 70% of the students who learn big data have 0 foundation.

3. Learning big data requires hard work and perseverance!

In addition, it is best to change careers to learn big data, and it is best to be 20-32 years old, and I hope you will consider it clearly according to your own situation.

To learn big data, we should be prepared in three aspects, one is to prepare the entry point of learning, the second is to build an effective learning and communication channel for ourselves, and the third is to have a certain scenario support, mainly experimental scenarios. At present, the technical architecture of big data has become mature, and because the demand for talents in the field of big data is relatively diversified, beginners with different knowledge structures can find their own learning entry points.

Interest is the best teacher, and it will support you to have fun and motivation in learning. It is recommended to choose to learn professional skills from your own situation, consider the trend of social development, and cater to the development of the times, so that the future development will be more and more broad.

A background in computer science is preferable in big data.

There is a programming foundation, a data structure foundation.

Big data is equivalent to a computer science professional course, which is more cutting-edge, and there is a compilation principle in the computer professional course, and big data is equivalent to that difficulty.

Big data is a general term for a series of technical problems, including distributed technology, analysis technology, development technology, etc., so big data needs your foundation to be more comprehensive.

High degree is generally required for graduate degree or above. Good math, good English, and some programming experience are required. In general, it is very demanding.

The most important thing is to be interested in this major, only if you are interested, you will learn well, and many professional schools implement zero-based teaching.

Educational requirements: The starting point requirements of the big data industry are relatively high, and it is recommended to have a bachelor's degree for current students.

Interest requirements: Skills are still based on various programming languages, so you should be interested in this aspect.

Learning requirements: The big data course involves a lot of knowledge points, the course is difficult, and it is not easy to understand, students must insist on learning and practicing, and if they don't understand anything, they should put it forward in time, be responsible for their own future, and they can't fish for three days and give up halfway.

The first is the big data platform itself, which is generally based on the deployment of certain Hadoop products such as CDH. There are many components in the deployed product, such as Hive, HBase, Spark, ZooKeeper, etc.

The second is ETL, that is, the data extraction process, the original data in the big data platform is generally the best in other business systems in the company, such as credit in the bank, core, etc., the data of these business systems will be extracted from the business system to the big data platform every day, and then carry out a series of standardization, cleaning and other operations, and then generate some models for downstream systems after some modeling.

The third is data analysis, after the data collection is completed, what kind of processing should be done based on these data, such as report applications, which may be written every day SQL development reports; There are also some platforms, such as risk monitoring, that are processed based on the data collected by the big data platform. Stuffy.