Data Scientist Skill Set

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Data scientist: The sexiest career of the 21st century

In 2006 Jonathan Goldman went to the business social networking site, LinkedIn, when LinkedIn was just a start-up, with fewer than 8 million registered people, but many members invited their friends and classmates to join, so the number of registrations increased rapidly. But it is not easy for users to find users who are already registered on the site, and the ratio does not meet the expectations of managers. Obviously, some social experiences are missing. As a LinkedIn manager says, it's like, when you get to the conference reception, you find someone ...

14 Questions for Silicon Valley and Silicon Valley technology companies: Valuation Bubbles/Big Data

From the Silicon Valley firm, to everyone's discussion of the bubble problem, how large data and artificial intelligence combined? What is the prospect of science and technology in the 2015? Dong Fei, a Coursera software engineer from Silicon Valley, sorted out the dry goods and various occasions in his recent Stanford public lectures to share with you. He has a hands-on experience, as well as a detailed analysis of some of the companies that have worked or studied in depth, such as Hadoop, Amazon, and LinkedIn. Dong Fei page Here, the mailbox is Dongfeiwww@gmail ....

Big Data Brain drain: Why research is in trouble

However, in recent years, the rapid transformation of scientific research field to data-centered, has a negative impact. In summary, the ability of competent scientific researchers and the ability of qualified industry practitioners are increasingly indistinguishable. The typically inert academic community has just begun to adapt to this shift, and other areas have already begun to scale up and reward this capacity.   Unfortunately, this has led to a lot of talented would-be researchers in academia, can only invest in the arms of the industry. The magic effect of data the 1960s, physicist Eug ...

Big Data Hot Professional pay list Hadoop talent top

As more and more companies begin to dive into the torrent of big data technology, market demand for IT professionals is rising.   Today, people with the ability to collect, organize, analyze and build data from different sources are on the rise for their careers. In the current digital age, the volume of data is much richer than any period in history, and many times this richness even becomes a heavy burden. Companies are starting to devote a lot of resources to cloud technology, mobile technology and social media. Combined with these emerging areas, coupled with the enterprise's own operation of the inevitable ...

Big Data Hot Professional pay list Hadoop talent top

As more and more companies begin to dive into the torrent of big data technology, market demand for IT professionals is rising.   Today, people with the ability to collect, organize, analyze and build data from different sources are on the rise for their careers. In the current digital age, the volume of data is much richer than any period in history, and many times this richness even becomes a heavy burden. Companies are starting to devote a lot of resources to cloud technology, mobile technology and social media. Combined with these emerging areas, coupled with the enterprise's own operation of the inevitable ...

What is the majority of large data items that ended in failure?

In almost everyone's mind, big data is the large and small amount of structured and unstructured data that the enterprise IT department is growing exponentially. But while big data has become a mainstream it phenomenon, most large data projects still end in failure. The reason is that it is difficult for enterprises to find appropriate methods for large data collection, management and understanding, and ultimately from large data information to extract valuable things. Conquering large data items, and ultimately extracting the business insights that your business needs, is a daunting task in itself. But when it comes to defining ...

What is the majority of large data items that ended in failure?

In almost everyone's mind, big data is the large and small amount of structured and unstructured data that the enterprise IT department is growing exponentially. But while big data has become a mainstream it phenomenon, most large data projects still end in failure. The reason is that it is difficult for enterprises to find appropriate methods for large data collection, management and understanding, and ultimately from large data information to extract valuable things. Conquering large data items, and ultimately extracting the business insights that your business needs, is a daunting task in itself. But when it comes to defining ...

2014 eight hottest Big data jobs

Large data age, data surplus, talent shortage, more and more IT professionals want to be able to enter the big data fields full of opportunities, but, in the end what is the specific large data professional positions and talent most popular? Human Resources company Kforce recently released a report according to IT professional pay level gives 2014 hottest ten Big data jobs (annual salary): First, ETL developers (11.13 million U.S. dollars) with the increasing of data types, enterprises need more and more strong data integration professionals. ETL developer with different data ...

Three major factors to realize the value of mining large data

Many companies are exploring how to tap into the value of big data, but one type of company has to be good at doing it: data analysis providers.   The business model of these companies determines that they must be able to effectively and consistently provide the data products and services that customers are willing to pay for.   Here's a great data analysis provider-ComScore, how to tap into the value of large data through 3 key factors (a convenient, scalable platform, an employee team that understands data analysis, and a deep understanding of customers). 1 easy, scalable data flat ...

Three mark factors to realize large data mining

Many companies are exploring how to tap into the value of big data, but one type of company has to be good at doing it: data analysis providers.     The business model of these companies determines that they must be able to effectively and consistently provide the data products and services that customers are willing to pay for. Here's a great data analysis provider-ComScore, how to achieve the right results through 3 key factors (a convenient, scalable platform, an employee team that understands data analysis, and a deep understanding of the customer).

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