What's the use of big data?

We are in the era of rapid development of science and technology, and now the Internet is closely related to our lives. We generate a lot of data on the Internet every day. These scattered data in the network seem to have little effect, but they are really valuable after systematic processing and integration.

First,? Developing big data technology can improve productivity.

Big data technology has become a very successful case in enterprises. Many application developers and large companies use big data technology to expand big data projects. When using big data technology, we can know which data is most needed through data mining, and gain more productivity, improve production capacity and bring more business value to enterprises through these data. At present, many enterprises solve problems through data mining analysis. Relatively speaking, big data analysis is faster than traditional data analysis, which can obtain "recyclable" information flow and improve industry productivity.

Second,? Developing big data technology can improve marketing decisions.

In recent years, the amount of data has exploded, and data profit is likely to become the main source of future income. Big data technology seeks the most suitable enterprise marketing strategy in the analysis of massive data, and brings more sensible strategies to enterprises through data analysis.

Big data engineers skillfully analyze customer data, analyze industry trends and customize more suitable products or services, effectively evaluate customer loyalty through the detection and analysis of pricing, and make a series of improved marketing decisions by using big data in time, bringing valuable data decisions to enterprises.

Third,? Future advantages of developing big data technology

With the rise of the big data industry, many development companies have realized that in order to continue to develop in the industry, they must use big data technology to enhance the brand value of their own enterprises and seek more competitive advantages in the industry competition. Large multinational companies such as Microsoft and Amazon are currently using big data to solve problems and provide better services to consumers.

At present, many industries and enterprises have tasted the sweetness of big data technology. In the future, there will be more and more industries using big data technology. At the current development speed of big data, the market size of big data will reach $203 billion in 2020. Many enterprises are looking forward to a wider range of big data projects, and then generate more interest space through applications.

Big data technology can improve productivity, improve marketing decisions and bring better development prospects to enterprises. At present, although the development of big data technology is in its infancy, its development momentum is very strong. In the future, more industries will be involved in the application of big data technology, and the future development of big data technology will be great!

At present, there are three main directions for big data employment: first, big data talents for data analysis, second, big data talents for system research and development, and third, big data talents for application development. Their basic positions are big data system R&D engineer, big data application development engineer and big data analyst. If you want to learn programming systematically, you can come to me.

For job seekers, big data is only one direction of career, while professional positions are about deciding what to do. Big data practitioners/job seekers can choose their own big data-related jobs according to their skills and interests. Here are ten hot jobs related to big data.

I. ETL research and development

With more and more types and sources of enterprise data, data integration and processing become more and more difficult, and enterprises urgently need a talent with data integration ability. ETL Developer This is a professional post born based on this demand. One of the reasons why ETL talents are hot in the era of big data is that in the early days of enterprise big data application, Hadoop was just ETL for the poor.

Second, Hadoop development

With the increasing scale of data, the data processing cost of traditional BI is too high, and the burden on enterprises is increasing. Hadoop's cheap data processing ability has been re-excavated, and enterprise demand continues to grow. And become a technology that big data talents must master.

Thirdly, the development of visualization tools.

Visual development means that on the graphical user interface provided by visual tools, relevant application software is automatically generated by visual development tools through operating interface elements, and all data can be easily connected across multiple resources and levels. Data visualization used to belong to business intelligence developers, but with the rise of Hadoop, data visualization has become an independent professional skill and post.

Fourth, information architecture development.

Big data reignited the upsurge of master data management. Making full use of enterprise data to support decision-making requires very professional skills. Information architects must know how to define and document key elements to ensure that data is managed and utilized in the most effective way. Key skills of an information architect include master data management, business knowledge and data modeling.

Research on verb (verb's abbreviation) data warehouse

In order to facilitate enterprise decision-making, the data warehouse research position created for analysis report and decision support is a strategic collection of all types of data. Provide business intelligence services for enterprises, guide business process improvement, and monitor time, cost, quality and control.

Sixth, the development of OLAP.

The developer of OLAP online analysis is responsible for extracting data from relational or non-relational data sources to build a model, and then creating a user interface for data access to provide high-performance predefined query functions.

Seven, data science research

Data scientist is a brand-new type of work, which can transform enterprise's data and technology into enterprise's commercial value. With the development of data science, more and more practical work will focus on data, which will enable human beings to understand data and thus understand nature and behavior.

Eight, data prediction and analysis

Marketing departments often use predictive analysis to predict user behavior or target users. Some scenarios of predictive analysis developers seem to be similar to data scientists, that is, testing thresholds and predicting future performance through assumptions based on historical data of enterprises.

Nine, enterprise data management

In order to improve the data quality, enterprises must consider data management and set up the position of data steward. The staff in this position need to be able to use various technical tools to collect a large amount of data around the enterprise, clean and standardize the data, and import the data into the data warehouse to become a usable version.

X. Data security research

Data security positions are mainly responsible for the management of large-scale servers, storage and data security in enterprises, as well as the planning, design and implementation of network and information security projects. Chengdu Jiamigu Big Data Training Institute focuses on the cultivation of big data talents.

I hope it helps you! ~