ask you a question:
Do you have many times determined to do big data work, but because I do not know how to start and give up?
Once the interview is not going to work too much data, but because there is no experience continuously run into a wall?
You did well in the company, the arrangement always good and fast task completion, but two years, your salary has been 10,003, many times a raise with the leadership, the leadership of the result every time oh Got it.
You knew that work now encountered a bottleneck, you want to pay more than 50% of the growth has been very difficult, can do only a career change.
Recently, several programmers around friends are learning Spark, Hadoop and other related knowledge, if not keep up the pace, it will be thrown out half the street at any time of the rhythm; know almost open, such as "getting started how big data "" how Java Web programmers transformation big data "and the like are also frequent topic of concern.
McKinsey report notes, big data, artificial intelligence, talent shortage, surge in demand. We have a technological advantage, and large data industry is also very short, and now into the line is the most appropriate time.
So what's hot big data depends on?
1. maturing technology, the use of space to expand
Big Data technology, the first to be mentioned for the first time in 1980, but only get rapid development in recent years. Compared to a few decades ago the computing power of neural network algorithm stretched now processor for fast processing of large data undoubtedly played a key role. By means of a high-performance processor, the machine learning and training model we completed in a short time PB-level data is made possible, thus laying the foundation for highly dependent image, rapid iteration depth study of speech recognition products, space is big data applications expand, thus also spawned related products and services to technology companies.
2. The importance of data assets, data mining has become an inevitable
Modern information technology so that the amount of data generated each day exponential growth, companies can no longer avoid the development of mining and utilization of data values.
3. Technical birth of new business models, new opportunities inherent in entrepreneurship
Big Data industry chain, gave birth to provide products and services for different sections of the portfolio of new models, either using the recommendation algorithm to make content services headlines today, or provide monitoring services-based data integration TalkingData, or provide the underlying architecture supports Ali cloud, big data found there were not inherent in the industrial chain business opportunities.
4. Market demand, job challenges large space
According to the mainstream media survey data, big data talent across the country, only 460,000, the next 3--5 years, big data talent gap will reach 1.5 million. There are agencies tier cities in 2018 domestic science and technology popular posts salary ranges and job-hopping gains were predicted: Big Data direction due to a higher degree of scarcity of talent, the case of the same length of service, salary large data engineers generally higher, the treatment also rose more than other jobs.
At present, the common Hadoop big data engineer starting salary is also 20K / month, pay a little experience will be much higher, data mining, machine learning, artificial intelligence related to higher personnel salaries.
(The above data collation from pull hook net)
For ordinary programmers, in Hadoop big data, data mining related work is the best choice, for three reasons:
1, the lower threshold, there will be able to learn basic programming;
2, compared to other development positions to pay 10-20 million and the annual salary of only 250,000 minimum.
3, Python is the most mainstream of the field of artificial intelligence programming language, Python Big Data technologies now hold more conducive to the future seamlessly into the AI field.
Learn how to get started quickly and be proficient in it?
When you really start learning do not always know where to start, leading to inefficiencies affect confidence to continue learning, and even affect the current work.
Actually, the most important thing is you do not know what technologies need to focus on to master, frequently stepped pit learning, end up wasting a lot of time, so a set of practical video lessons to learn is to follow very necessary.