If we want to 'eat chicken' in the big data industry, we must first understand the future development trend of big data.
In 2018, big data technology has become more and more mature, and in the future, it will be more accurate and detailed in the direction of system research and development, big data application development and big data analysis.
In general big data has 5 parts. Data collection, data storage, data cleaning, data mining, data visualization. Data collection includes hardware collection, such as OBD, and software collection, such as Didi and Taobao. Data storage includes NOSQL, hadoop and so on. Data cleaning includes linguistic analysis, streaming media formatting, and more. Data mining includes association analysis, similarity analysis, distance analysis, cluster analysis and so on. Data visualization is the web.
Big data technology refers to extracting data that is useful to itself from massive amounts of data, analyzing and processing it. The main features at this stage are four V:
Volume - huge data volume;
Variety - data type Numerous ;
Value—low value density;
Velocity—fast processing speed; data is captured by the system or manually, collected, integrated, and counted. These data have a very strong centralized orientation, and have been pointed to in the process of feedback a clear goal.
There are also many examples in this regard. When you are browsing Baidu web pages, when you follow the news of a certain star a few times, the news of this star will appear in the subsequent browsing process. When shopping on Taobao, when you pay attention to a certain type of product for more than a certain number of times, the page will focus on pushing the relevant types of this product and surrounding areas to users.
2018 is a year when the demand for big data applications and talents is very high. As a strategic emerging industry supported by China's official government, the big data industry has gradually moved from a concept to the two hot topics of ''big data' and ''virtualization''. The field has received extensive attention and attention, and 90% of enterprises are using big data.
Then we need a good equipment to be invincible on the battlefield, so how do we turn big data into a sharp blade and open up a road for our glorious life. Next,
I will bring you popular occupations in the era of big data. A career that suits you is like having a good weapon;
1. Before a product is designed, a
data planner
provides key data support for various decisions of the enterprise, maximizes the value of enterprise data, and better implements differentiation Competition, to help enterprises gain the upper hand in the competition.
2
Data Engineer
Designers, builders, and managers of big data infrastructure who develop architectures that can analyze and deliver data according to business needs. At the same time, their architecture also ensures that the system can run smoothly.
3
Data architects are
good at dealing with scattered data and all kinds of irrelevant data, proficient in statistical methods, able to obtain raw data through monitoring systems, and interpret data from a statistical perspective.
4 A
data analyst
is responsible for transforming data into information that the business can use through analysis. They find problems through data, accurately find the cause of the problem, and find the key points for the next improvement.
5 The
data applicator
restores the data to the product for use by the product. They can express the information contained in the data in a language that ordinary people can understand, and promote the internal adjustment of the enterprise according to the conclusions of the data analysis.
6
Data Scientists
Leaders in big data, with a variety of cross-scientific and business skills, able to translate data and technology into business value for the enterprise.
With direction, then we need big data training institutions. At present, there are too many big data training institutions. How to choose a reliable training institution?
How to choose a big data training institution
to see high-paying employment data
If there are many students participating in the study, if there is a high employment
data , it is a reliable institution. If you only promote the number of lecturers and do not promote employment information, then you need to seriously consider it. The lecturers are very good, which does not mean that the graduates will be equally good.
Look at the number of full-time lecturers
. The salary of the big data industry is very high. The annual salary of front-line
engineers least 200,000 yuan. If you are hired as full-time lecturers, the annual salary of the lecturer must not be less than 200,000 yuan. For training institutions, the cost The pressure is very high. Many training institutions only have part-time lecturers, so the cost is minimal. Because if there is no class, the training institution does not pay wages and there is no cost. However, part-time lecturers do not have so much time to prepare lessons, and the level of lectures is very different from that of full-time lecturers.
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IT industry technology updates very fast. We work overtime in the unit, we are exhausted, and we have no time to learn new technologies. If training institutions only focus on training a technology and collect a sum of money, it will be detrimental to our long-term development. It would be great if you paid a fee to learn this technology in a training institution, and all future updates of this technology can be learned for free.
See if there are many leather bag companies in the training institutions that are allowed to visit on the spot . They
do not have teachers themselves, but are just an organization that connects the trainees who want to participate in the training and the front-line personnel who want to give lectures part-time. This is irresponsible to the students. If you go on a field trip and chat with the staff, it is easy to identify.
Well, today's sharing is here. If you are interested in big data, you are welcome to join the big data technology exchange group QQ; 719301411