Skills Needed For Big Data

Aliyun, Sheng, Sina Cloud, Huawei Cloud, Baidu Cloud, with the development of the domestic cloud service industry, the continuous improvement of the industrial chain to the technical requirements are higher and high. In particular, the user's demand for cloud services is increasingly stringent. As for what technologies are the key to cloud computing, what are the common cloud development frameworks and tools? Let's count dozens of of them first. @ Tan Lin _hootch on his microblog, Cloudcamp founder Dave Nielsen faces the industry's development, analyzing the cloud services industry's 10 most needed job skills. Yesterday...

As the key word in the IT field, the "Big Data" is always in the spotlight, and the analysis and utilization of it has attracted much attention. On the other hand, problems that cannot be solved by IT technology, existing organization and talent skills are gradually surfacing. This requires "the analysis of data and its integration with the business technology." This paper summarizes the technologies needed to apply data analysis to the business and how to implement effective information applications in the enterprise. At the same time, it also lists the advanced examples of Japan and abroad. Three major technologies below, let's take a look at the big data age of the technology companies need? Business Skills This ...

In the internet age, large data is hot, many people must pro data, but can really say that the big data is not much, not to mention how to use large data to dig out the great business value. 　　How do you define large data? What are the characteristics of large data? This paper aims to clarify the concept of large data, illustrate the application of large data and explore the future development of large data. 　　Q1: Is big Data a commercial hype? The industry's definition of large data is 4 "V": Large volume (Volume), multiple species (produced), fast (velocity) ...

Large data Applications March 2012 The Obama administration issued a "Big data research and development plan". In response, the National Science Foundation, the National Institutes of Health, the Ministry of Defence, the Department of Energy and the United States Geological Survey are investing in big data innovation. Many companies in the United States are conducting their business activities around large data acquisition and utilization capabilities as part of their product or operational backend. Research groups, governments and the private sector are also speeding up the generation of large datasets of various themes, including: Climate change, traffic patterns, health and disease data, buying behavior ...

Big data goes from "concept" to "value", based on large data recommendations and forecasts gradually popular, data science will rise, security and privacy become an important issue, the large data industry into a strategic industry-this is the Chinese Computer Society large Data Expert committee on the "Big Data" 2014 Ten trends in the prediction of the content. In this forecast, it also includes data commercialization and data sharing alliance, large data ecological environment development and so on. At the same time, the large data experts committee predicts that 2014, the Internet and E-commerce, Finance (stock market forecasts, financial Analysis), health care (epidemiological monitoring and forecasting ...).

Big data goes from "concept" to "value", based on large data recommendations and forecasts gradually popular, data science will rise, security and privacy become an important issue, the large data industry into a strategic industry-this is the Chinese Computer Society large Data Expert committee on the "Big Data" 2014 Ten trends in the prediction of the content. In this forecast, it also includes data commercialization and data sharing alliance, large data ecological environment development and so on. At the same time, the large data experts committee predicts that 2014, the Internet and E-commerce, Finance (stock market forecasts, financial Analysis), health care (epidemiological monitoring and forecasting ...).

The development of big data in 2012 is in full swing, and it is catching up with cloud computing. If we compare this year to the year in which big data takes root, then 2013 will usher in a year of thriving and even blossoming.

In the past 30 years, many companies have added new management to cope with the vagaries of the business environment. In the middle of the 80, the CFO was a strange position for most companies. However, with the increasing transparency of value management and corporate-investor relations, more and more companies have CFOs. With the growing importance of brand building and customer management to the company, the chief marketing officer becomes more and more important, and many companies set up a chief strategist to help the company deal with the challenges from the market. Now, the power of data analysis is profoundly affecting the business landscape. Get hold of ...

BEIJING, July 22, 2014--companies are looking for innovative ways to manage as many data and data sources as possible. While technologies such as Hadoop and NoSQL provide specific ways to deal with large data problems, these technologies may introduce islands of data that can complicate data access and data analysis needed to form critical insights. In order to maximize the value of information and better handle large data, enterprises need to gradually change the data management architecture into a large data management system to seamlessly integrate various sources, all types of data, including Hadoop, relational databases, and nos ...

Large data is hailed as the key strategic business asset for the future. This means that in the near future, employees in other departments will also want to know the IT department's strategy for big data. How do you explain that to them? To be sure, handling large amounts of data is not new to most IT departments, but analysts say big data is different from data warehousing, data mining, and business intelligence analysis. Data is accumulating at unprecedented speed and variability, and unlike previous data, most of the data is unstructured and raw. Blogs, social networks, machine sensors and location ...