I believe there are a lot of people after a certain period of time in an industry have had the idea want reorientation, perhaps less than the salary of psychological expectations, or technical bottleneck and so much more. After Let's sort out what a person working for a period of time, it may be the reason why the reorientation want it, reorientation from the former work and wanted to turn to the post two angles we briefly summarize:
Reorientation before work
Poor industry outlook, either too upset, either saturated
Work content repetitive or boring, skills upgrading is not obvious
Small salary increase
Contrary to the current work and personal character, such as introverted people engaged in industry sales
Currently working too hard, looking for a light-hearted work
Currently work is no challenge, no meaning
Access to the industry more interested in their own work or
I would like to turn to the job situation
Popular, industry promising
High salary treatment
New post better play individual strengths
Interested
The new jobs in line with their career planning is expected, for example want to look relaxed, so reorientation of civil servants;
We are considering reorientation little friends, right?
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/ Reorientation before some tips /
Reorientation is by no means an easy task, is really about the job transfer out of "self-selection" or "forced" or "impulse"?
Whether job transfer out of "self-selection", it can be detected by compliance with the following conditions from me:
The current work performed well, due diligence, to make progress, get along well with colleagues and bosses;
After objective and rational analysis and understanding, very clear we need to make a new career planning of causes, including industry outlook and other objective reasons and subjective reasons of character, points of interest such as the self-analysis;
Would like to turn to the post to go to do a detailed investigation, there is a certain understanding and preparing for new career;
Some job as product manager, data analysis, and so is the threshold is not high, but want to learn it is not easy job, just because it was decided reorientation good entry, then a little impulsive.
So, like a personal career choice such an important thing, or I hope you think twice Oh.
/ Industry status job transfer large data /
Big data, data mining, machine learning, artificial intelligence, and now many programmers eager for these hot technologies, know the peace [deep learning how to get started? ] [Ordinary programmers how to move closer to artificial intelligence? ] And other issues have a high degree of concern.
More and more technical candidates will be thinking when to quit, whether in big data work-related positions. So why are so many people willing to invest Kong data industry? Here we take a chat with job transfer large data current status of the industry now.
1) Why are so many people willing to transformation of big data industry?
Big data trends
2019 - 2021, 20 years will be the next big data and artificial intelligence, the best industrial capital merger integration window period, just as in 2003 - the same window period in 2006 the Internet industry consolidation.
Big data and artificial intelligence rely on each other, at the policy level has risen to a national strategy, and quickly started to enter the implementation phase; the technical level, big data technology has matured, and promote artificial intelligence technology advances at an alarming rate; industry level, intelligent security, autopilot, medical imaging and so accelerating the floor.
Big talent market demand
According to the US Bureau of Labor predicts that in 2022 the US market will require about 850,000 large data aspects of professional and technical personnel; domestic statistics "big data talent report" shows that predicting the future 3-5 years talent gap will reach 150 million and more.
Jobs pay levels were generally higher
According to statistics, in the United States big data analysts average annual salary of about $ 175,000; and domestic first-tier Internet companies, pay levels of large data analysts generally 20-30% higher than other jobs at the same level, which has become reorientation of domestic staff data transformation to the big one very important reason.
Colleges and universities to increase the establishment of large data relevant professional
Currently, there are nearly 170 universities around the world opened a big data related fields. In recent years, the domestic Ministry of Education also take active measures to strengthen the cultivation of big data talent, the creation of new professions, such as "Data Science and Big Data technology".
Army has entered, all the people began to move. 2019 major domestic colleges and universities will have to set up large data, Artificial Intelligence, the real competition will come soon, has joined the Big Data industry students are fortunate, we must seize the opportunity to seize everything you can, threw himself investment.
2) most of which posts job transfer large data come from?
From a technical perspective, programming languages (Java, python, R, Go language, Andrews / c ++ development and other post ...) for large data development terms is merely a tool.
java development
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All kinds of big data frameworks such as Hadoop, spark, storm, flink, a variety of middleware such as flume, kafka, sqoop and so on, most of these frameworks and tools is written in Java or Scala JVM-based language, so the current reorientation most large data from Java Kong.
Andrews / c ++ and other development post
Andrews transition from development to post large data also many people, the development partner for small hillock transformation are programmed, as long as the foundation, effort, job transfer large data outlook is still very impressive.
In fact, if a little large data base programmers transformation, has advanced natural advantage.
Even if you do not have any zero-based programming language learned, but also can be learned.
Whether beginner or experienced programmer, you should focus on the <language features> instead of tangled what kind of language, the only way to achieve mastery, pick up any language will basically use, and write quality code.
/ Job transfer large data pathway /
Mainly in the following ways:
1) internal job transfer
By way of internal job transfer business, this is the best way to achieve job transfer, convenient, high success rate.
2) With the strength of re-employment training institutions
In the case usually do not have spare time to accumulate in this direction, to participate in a short-term professional training courses for centralized charging, very necessary. When choosing a job again to raise the bar, take part in some of the interviews to gain experience, find a job or post large data very easy. Of course, you need to have the determination and perseverance, great effort, this is understandable Oh!
3) books, videos daily accumulation
No chance to internal job transfer, and are unwilling to spend money to participate in training courses, it is usually nice to read it, some of the basic frameworks, techniques and tools of big data at least get a good read classic books, then at least a complete set of large instructional video with data entry.
Secondly, more attention may focus on current industry jobs, to understand under what conditions need to meet, completion of a period of time out on the next candidate, a wake-up call not only for himself, but also required a more accurate grasp of the interview.
/ Big data professional development /
Above everyone to mention a few former reorientation need to consider carefully the issue.
One of them is sure to want to turn to the new position of industry prospects, career development, job characteristics even work content must have a basic understanding.
Big Data can be divided into two general direction of the overall five career.
2 categories are technical and traffic class type, wherein the direction of focusing on how to handle the technology well data, focusing on how the traffic direction with good data;
Technical direction
Large data-technical direction agricultural sector code, the programmer.
1) Big Data platform R & D line
Responsibilities: The main responsible for the product of Big Data technologies, including research, development and packaging open source technology framework
Getting Started: systematic understanding of big data technology system (spark, hadoop, hbase technology), read through the technical framework of technical documentation, know that each technology can solve any problem, its implementation principles, advantages and disadvantages; able to call the technical framework API function package
Advanced: open-source framework to optimize and improve the performance of open source technologies, as the open source community commiter
Development: Data Architect development platform, the data platform product manager
2) the development of large data line
Responsibilities: also known as ETL engineers, responsible for the use of big data technology to collect, process, analyze data;
Getting started: with data platform R & D engineers, and skilled use of SQL, stored procedures;
Advanced: technology selection, technical architecture design, data architecture design, platform performance tuning
Development: data architects, large data DBA
3) Big Data line algorithm
Responsibilities: commonly known as the assistant engineer, is responsible for using a machine learning algorithm modeling, business process needs, based on an algorithm engine package algorithmic tools.
Getting Started: python language, sklearn, tensorflow engine algorithms, familiar with the decision tree, SVM, Naive Bayes and neural network algorithms and apply various principles scene;
Advanced: business modeling, parameter adjustment
Development: Data Scientist
4) Large data visualization route
Responsibilities: The main responsible for data visualization application development
Getting Started: various chart data visualization application scenarios, echarts frame, vue, BI tools
Advanced: Application data visualization UIUE design, large screen design show
Development: Data Artists
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Business class
1) Big Data analysis route
Position: primarily responsible for binding business issues, the use of large data analysis, data analysis, production reporting, planning and data applications
Getting Started: Familiar with a variety of analytical charts, data analysis tools, data analysis, report writing have the ability
Advanced: familiar with the various concepts of algorithms and usage scenarios, have a keen business mind, thinking and application management planning capabilities
Development: Data Consultant, Product Manager data
