Shulou(Shulou.com)06/03 Report--

Big data, also known as a huge amount of data, is a large amount of data, a wide range of sources, a wide variety (log, video, audio), large to the PB level, the current framework is to solve the PB level data.

Professionally speaking: big data (big data,mega data), or huge amount of data, refers to the massive, high growth rate and diversified information assets that need a new processing model to have stronger decision-making power, insight and process optimization ability.

Big data's 5V features: Volume (mass), Velocity (high speed), Variety (diversity), Value (value density), Veracity (authenticity).

Second, what language foundation do you need to learn big data?

First of all, learning big data needs to have the foundation of java,python and R language.

1) at what level can Java learn from big data?

Java needs to learn javaSE. Javaweb,javaee is not needed for big data. Once you learn javase, you can understand the hadoop framework.

2) python is the easiest to learn, the degree of difficulty: python java Scala.

Python is more intuitive and easier to understand than java, because if you know Python, you still have to learn java. You have learned java, and then it will be very easy to learn python. You can learn python in a week.

3) R language can also be learned, but it is not recommended, because java uses the most people. Big data's first framework, Hadoop, was written by Java at the bottom. Even if I learned R, I still can't understand hadoop.

The role of java in big data is to form big data's language, big data's first framework Hadoop and other big data technical frameworks, the underlying language is all written by Java, so it is recommended to learn java first.

Let me give you an example to illustrate their division of labor and role. Java pays attention to business, big data pays attention to data, the front end is the face (page display), java is the arm (business), big data is the straight male brain, artificial intelligence, deep learning is the brain with EQ.

Here I still want to recommend the big data Learning Exchange Group I built myself: 529867072, all of them are developed by big data. If you are studying big data, the editor welcomes you to join us. Everyone is a software development party. Irregularly share practical information (only related to big data software development), including the latest big data advanced materials and advanced development tutorials sorted out by myself. Welcome to join us if you want to go deep into big data.

Third, big data's career development direction

Learned big data, do not need to start from java, can directly do big data development engineer. After accumulating a few years of experience, you can become an algorithm engineer. Take a look at what positions big data can take:

Big data Development engineer

Data analyst

Hadoop Development engineer

Spark Development engineer

Data Warehouse Development engineer

Data cleaning engineer (ETL)

Big data architect

Algorithm engineering

IV. Big data's advantages

Big data is strongly supported by the state and a lot of resources are invested in this area. Big data Center sits in Guizhou. Artificial intelligence and cloud computing are based on big data, which requires a large number of big data talents.

1) big data's salary and treatment for talents

In general, the average monthly salary of big data-related jobs in first-tier cities is 12-15K in Beijing, the average monthly salary is 17K, and the annual salary of big data algorithm engineer is about 300000-500000.

2) do you have any academic / professional requirements to study big data?

I also found a job in high school, but college degree or above is better. Although I have a bachelor's degree, I have not learned practical operational skills in four years of college. What I have learned is not needed at work, but it is easier to understand some things.

Big data's learning route

Big data master class syllabus:

Linux+ High concurrency + Hadoop Biosphere + distributed search + Strom streaming Computing + Spark + Machine Learning algorithm

Normally, you have to do the following before learning big data:

1. Learn the basic programming language (java)

two。 Master the basics of entry programming (linux operation, database operation, git operation)

3. Learn the various frameworks in big data (hadoop, hive, hbase, spark)

These are the three steps that must be done to learn big data normally. If you have the foundation of java and then you have basically achieved half the success, at least you don't have to be annoyed for the learning of the basic language.

The real learning of big data can not only stay at the theoretical level, for example, the frequently used spark framework currently supports the development of java or Scala in both languages, and now the Python language can also support it. Big data's direction of cutting is omni-directional, the basic language learning is only a very small aspect, programming to the final implementation of the programming idea, with the guiding ideology to learn can be a lot more convenient.

Can you learn from big data in the basics?

Although big data needs the foundation of Java. However, 0 basic partners can also learn.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.