Big data brings unlimited development opportunities

In today's society, the tide of big data has already swept numerous organizations in the world. As the global economic competition intensifies, the development of big data will also bring unlimited business opportunities. Therefore, understanding your preferences and timely forecasting of market growth trends is absolutely necessary, and once you have the core information, it means you can take the lead in the competition.

Therefore, enterprises should seize this opportunity in time. But at the same time, it also needs the support of the corresponding technicians who are more knowledgeable about managing data and building analytic systems and can make the data more valuable. A recent EMC survey also testified to this. The survey results show that: 83% of people think that due to the wave of big data and the birth of new technologies to increase the demand for data scientists, of which 64% of people think that there will soon be technically in short supply worldwide scene.

Big data makes enterprises in trouble A huge gap of skilled personnel

In fact, the McKinsey Global Institute research predicts that in the next six years alone, there may be a lack of 140,000 to 190,000 people with in-depth analytical data capabilities in the United States alone, along with the ability to analyze big data and make effective decisions for businesses The data management and analysts also have a gap of 1.5 million people.

David Menninger, an analyst at Ventana Research Inc., said recent surveys conducted by his company show that three-quarters of the 169 executives think the lack of technicians is an important factor in a company's inability to meet the challenge of big data.

Hadoop In addition to the core design ideas MapReduce and HDFS (Hadoop Distributed File System), Hadoop also includes a class from the SQL query language HQL to NoSQL HBase database (NoSQL database is usually used to deal with unstructured data, including audio and video. ), And machine learning library Mahout content. Cloudera, Hortonworks and MapR have all added Hadoop projects to their distributed systems.

MapReduce programming model can be regarded as the soul of cloud computing technology. MapReduce is a programming model that handles large and very large data sets and generates related executions. The main idea is to learn from functional programming languages, including features borrowed from vector programming languages.

Beth Stackpole, a contributing editor at TechTarget, points out that today's teams that manage traditional structured data environments are truly professional, but appear to be unwieldy when faced with open source big data technologies such as Hadoop and MapReduce. The reason for this is that the skills to deal with traditional relational databases can not be translated into the skills to deal with the massive unstructured data in the big data world. NoSQL database technology is precisely built according to the new platform core.

Popular career in the era of big data

Big data processing system administrator

Big data processing system administrator is responsible for daily Hadoop cluster up and running. For example, direct or indirect management of hardware, when the need to add hardware to ensure that the cluster can still be stable operation. At the same time also responsible for system monitoring and configuration, to ensure that Hadoop and other systems of organic integration.

Big data processing platform developer

Big data processing platform developers responsible for building big data processing platform and used to analyze data applications. Because of its experience in the field of development has been related, so more familiar with the relevant tools or algorithms. This helps when writing, optimizing, and deploying various complex MapReduce jobs. The role of practitioners who use big data-related technologies is similar to the positioning of DBAs in a traditional database world.

Data analysis and data scientist

Data analysis and data scientists basically belong to the same category of work. Those with specialized field knowledge study the corresponding problems in algorithmic analysis, and data mining is also an important technique they should master. Helps create the right big data products and big data solutions that drive business growth.

Data steward

Enterprises must consider the appointment of data stewards to improve data quality. Data stewards need to use Hadoop to bring together large amounts of data around the enterprise and to clean and standardize the data through the ETL process into a data warehouse to make a usable version. Then, through reporting and analysis techniques, the data is sliced, diced, and delivered to thousands of people. Be a data steward to ensure the integrity, accuracy, uniqueness, authenticity and non-redundancy of market data.

The lack of skilled personnel today is not desperate. Omer Trajman of Cloudera pointed out that Hadoop as a big data technology solution is not as hard as learning how to make a rocket. A few years ago, there were very few people who knew about Hadoop, but more and more people are now learning Hadoop. Businesses should encourage and train technicians to learn Hadoop technology.