One of the development trend of the future of big data industry: cloud computing, artificial intelligence and other cutting-edge innovations depth of integration. Development emergence and development of big data, cloud computing, artificial intelligence and other cutting-edge technologies are from social progress and production of IT industry. The integration of each other cutting-edge technologies will be able to achieve ultra-large-scale computing, intelligent automation and analysis of massive data, in a short time to complete high complexity, high precision information processing. For example, Alibaba e-commerce transaction platform to complete order transactions per second, 175,000 strokes and 120,000 orders per second pen pay double 11 day, mainly due to the fusion of the "flying platform" cloud computing and big data. Baidu brain also incorporate a variety of techniques cloud, large data, artificial intelligence, with strong performance achieved.
The future development trend of the industry in the second big data: Big Data for manufacturing solutions escalating power intelligent manufacturing. Manufacturing product life cycle to produce large amounts of structured and unstructured data from market planning, design, manufacture, sales and maintenance process will form a big manufacturing data. In addition, a big manufacturing data also with multi-source heterogeneous, multi-scale, uncertainty, high noise characteristics. In the "Intelligent Manufacturing Development Plan 2016-2020" in 2025 made it clear, to promote the implementation of intelligent manufacturing "two-step" strategy: "The first step, in 2020, the development of intelligent manufacturing base and support capabilities significantly enhanced, traditional manufacturing industry areas of focus basically digital manufacturing, conditions-based intelligent transformation of key industries made significant progress; the second step, by 2025, intelligent manufacturing support system basically established, the initial realization of intelligent transformation of key industries. " In the big data market segments Industry Solutions accounted for up to 34.3%, it will play an important role in the development of intelligent manufacturing industry.
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Future Big Data industry outlook is excellent, if you want to join the Big Data industry,
Third, what big data can do?
Forecasting, decision-making, provide support for machine learning and artificial intelligence
From ancient times to do a forecast, but the core of large data do predict that the whole sample, the whole sample multiple dimensions, cross-validation, people will lie, in social situations or obscure portions of the heart, but this part of the heart cumulative total on the Internet there are string and wind horse track will stay, therefore, more and more data model and data will give nearly unlimited perception results. That is, you can let the computer capable of learning, machine learning is to design something that makes a computer can automatically learning algorithms, artificial intelligence is the core of what? The final analysis, "with a large computer data instead of thinking in the human brain; computer may be more comprehensive and rapid brain than people think
Of course, the application is not an article of big data, a simple example will be able to understand that now is the era of data is king, and we are only now really started to appreciate the charm of the "most convincing data" is, I think, the data local action to be developed too much, the role of data, limitless future, can not predict, did not dare to predict, we can only look forward. I think about the future a lot of data really is a "terrible" thing, humans also need these data applications in production, otherwise, would have disastrous results.
Fourth, the big data jobs What are the main directions, how treatment?
Is the development, preparation of large data processing program
For example mapreduce write, hbase database operations, hive program. . storm also write Java programs and so on. . Mainly oriented development. spark may write Scala program
Development ah. . Data volume, high concurrency large-scale project architect, technical director, jd, Ali and other Internet companies Technical Director, will definitely have these big data technology, students after completion of both are very in listed companies or other companies of these projects good
Development class:
Storm Development Engineer:
Salary: 15K-25K
Job Description: Storm Development Engineer is responsible for real-time processing, computing, storage and other development business data. Scenarios such as: real-time statistics trading volume, real-time statistics website pv amount. The data from the source into the format required for the business process or the result of analysis obtained, and then stored or displayed. Technology needs are: Strom and principles underlying architecture, distributed storage system, HDFS, the distributed database.
Machine Learning Engineer:
Salary: 25K-40K
Job Description: The Machine Learning Engineer is responsible for business needs, combining the characteristics of different algorithms of training model, using the algorithm automatically learning for the future business scenarios to predict or analysis to assist decision-making. Technology needs are: statistics, machine learning algorithms, large data computing framework related technologies.
Spark Development Engineer:
Salary: 17K-35K
Job Description: Spark Development Engineer primarily responsible for implementing the appropriate business needs based on the use of Spark technology development, including off-line computing, real-time online calculation and SQL analysis. Technology needs are: Hadoop ecosystem related technologies, SparkCore, SparkSQL, SparkStreaming and so on.
Hadoop Engineer:
Salary: 15K-35K
Job Description: Hadoop development engineer responsible for the use of Hadoop ecosystem related technology business achieved by programming based on statistical data, calculation and analysis, the results are displayed or stored data. Technology needs are: HDFS, Yarn, Hive, Hbase and so on.
algorithm engineer:
Salary: 25K-40K
Job Description: The algorithm engineer responsible for the development of algorithms, including information classification, identification of noise, text clustering, event analysis, machine translation, and also responsible for selecting according to different business scenarios, design, optimization algorithm and its innovation. Technology needs are: statistics related technologies, various types of machine learning algorithms, large data related technology.
Big Data Platform Architect:
Big Data Architect:
Salary: 25K-40K
Job Description: The Big Data Architect is responsible for selection of technology based companies do business and future plans, there is a global technology business plan based on the needs of product items including analysis, design and implementation to achieve the overall system architecture, system architecture guarantees rationality and scalability. Technology needs are: HDFS, Yarn, Hive, Hbase, MR, Spark, Storm and other technologies.
Operation and maintenance analysis categories:
Big Data Retrieval Engineer:
Salary: 15K-30K
Job Description: Data Retrieval engineer responsible for the data stored in the distributed according to specified users or business needs
Seeking to extract the data. Technical data retrieval needs of HDFS have distributed technology, Hive data warehouse, Hbase points
Distributed databases.
Cluster operation and maintenance engineers:
Salary: 15K-25K
Job Description: The operation and maintenance engineers responsible for cluster management, optimize system architecture and resources, improve deployment efficiency, the most important thing is stability, high availability security services to ensure that services can be 7 * 24 hours a day to provide users with services. Techniques are required to: data structures, algorithms, programming the shell, Python programming techniques, distributed storage and computing related technology.
Data mining engineer:
Salary: 17K-35K
Job Description: Data mining engineer responsible for patterns and model presentation of data from existing data, the data filter out important information for machine learning, modeling and analysis, mainly the relationship between the dig, according to the data variables, data mining is the basis of machine learning, machine learning and have some contact. The main techniques used are: distributed storage, computing technology, Python language, machine learning algorithms, Spark technology.
Data Warehouse Engineer:
Salary: 15K-35K
Job Description: Data Warehouse Engineer is responsible for data extraction, transformation, loading storage, and data modeling, data service optimization, data from the warehouse to the front desk several reports show. Technology needs are: Hadoop ecosystem technology, Spark, Hive, Hbase etc.