Analysis and challenge of large data in cloud computing era

Intel anthropologist Genevieve Bell shared her research on big data, and she thought deeply about the possible changes that big data might make to the future and explored the implications of these big data phenomena in many different contexts.

Bell in http://www.aliyun.com/zixun/aggregation/18652.html "> the official title of Intel Corporation is the director of interactive and experiential research at Intel Labs, She is responsible for the work that is different from other Intel scientists and engineers, covering all the recent data tsunami, cloud computing, device proliferation (device proliferation), and more powerful servers that have sparked heated discussions in the industry. "Big Data" is Bell's next major research project.

The question is where to start? For the topic we want to discuss, we are still at the stage of trying to visualize the outline and size of the subject, "Bell said at a conference on the Xeon E5 processor in London earlier this time. "Today, all the databases that have reached full edge are just a start."

Next, Bell says, the world has to think, how do we filter that data? What changes will this bring to the traditional online database? Will the existing data world begin to become disorderly or even face collapse and then build?

and in all this change, Bell says, at least we are beginning to understand that everything is going to be in the direction of building a data-tracking law, including simulations and digital data, and that we must be able to manage all the data.

for me, in this job, the data itself is not what interests me the most, because all things produce data, and what's really interesting is how to develop algorithms that are better at using the data, she explains.

Today, the way we use data is not all visually revealing the meaning of the data itself, Bell said, especially the algorithm--to make all the data good to use, you have to understand the correctness of the data itself, which is closely related to the original data-filling person.

"All the ideas we try to use to make the data more reasonable will be in the first place at the outset," she said. In fact, she also points out that when we begin to look for fixed patterns, causal relationships, and associations between data in a single data model, we are already in the inherent bias.

"For me, the most fascinating aspects of large data analysis are not only the gathering of extensive data from various fields, butThe important thing is what you can do with them, "Bell says," We are increasingly reliant on data analysis, which, at some level, represents a cultural script that is entering a new level of barely. The idea of data analysis such as

also drives data toward "personification" (anthropomorphizing). Bell points out that all this data will be necessary at the beginning of the discussion of the "Secret Life of Data" (The secret). These discussions will further expand applications such as large data and cloud computing.

Bell says that all data actually has its own characteristics, which is what makes it different from all other data, so it's a good idea to clarify the characteristics of all the data before analyzing it.

(editor: Heritage)