Where are the big data people?

Large data era has come, many companies want to use large data to drive the business, but do not know where to start. They cannot find a breakthrough in the combination of large data and business. And some real big data application in the actual combat enterprise, but in the application process is difficult: large data can not be combined with the business, not the ability to collect and analyze massive data, operators lack the power to apply large data, the data source is difficult to use.

Enterprises need to combine their own characteristics, and gradually promote large data applications. For the small and medium-sized enterprises without platform deployment capability and data collection ability, the data from the government, social network platform and other third parties can be used to analyze the whole data, so that many business models can be calculated in a short time, and the dependence on the massive data and complex models is reduced. Validate and select effective models through practical feedback. The industry has proved that a lot of data and simple models are more effective than some of the data plus complex models.

For enterprises with data collection capability, they can make full use of Internet resources and collect user behavior data in the process of users using products and services. Portal sites, Exchange records, customer service data can become the source of user data, enterprises can through online insights, O2O marketing links and resource integration, thereby improving the offline user experience. Multi-Source data is a significant feature that determines whether an enterprise applies large data.

For enterprises that already have large data deployment capabilities, the future can be built and deployed through the Hadoop platform, through data Warehouse centralization, integration, analysis of data and information, using a large number of structured, semi-structured and unstructured data to enhance enterprise information capacity, mining the value of big data.

In the future, the application of large data will go beyond the marketing category, fully into the enterprise supply chain, production, logistics, inventory, Web site and store operations, and other links, Hadoop will be from the experiment to production, large data talent will become scarce talent.

The 2013 large data and Analysis personnel survey showed that most companies plan to take a combination of retraining, recruitment and outsourcing to fill the talent gap.

HP announces course modules and certification exams around its mpp-based HP Vertica Analytics platform. Its introductory course will be taught in HP Expertone classrooms around the world for a period of over three days.

MAPR and its rival, Cloudera and Hortonworks, offer a number of training courses. Here in MapR, they usually offer MAPR learning videos from two to 3rd, and their online and classroom topics include the basics of cluster management, hive and pig hands-on, mapreduce training, and hbase programming.

These training programmes are premised on the assumption that the trainers are competent system administrators and developers who can quickly learn new technologies.

There is also a choice of online education, such as the National People's Congress Economic Forum, 51CTO, PPV classes have provided large data network courses. The advantage of online education is not limited by time and region, emphasizing the independent learning of users, although there are still some problems in the course of completion rate and training effect, but as a kind of rich content, can personalized teaching, marginal cost of training methods, online education in the future will have a broader space for development.

After you send out "where the big numbers are going," get confused, identify your needs and the size of your training, then find a suitable training facility, and maybe your problem will be solved.