Take you to pack B, take you flying big Data age

I have contacted http://www.aliyun.com/zixun/aggregation/14294.html "> Big Data:

1. American Prism Program

2. A few days ago, the news reported that Apple stole user privacy

3. Baidu's user search habits statistical analysis

4. Taobao user shopping habits analysis, smart recommendation baby

5. Smart Tag page for browsers

...

Most want to understand the large data architecture and algorithms:

1. The famous Google page ranking algorithm: PageRank

2. Famous Clustering algorithm: K

7.CART

3.c4.5

4.k-means

5.SVM

6.Apriori

...

Future challenges and trends for large data applications are:

The biggest challenge is not the technology and the data itself, but the perception and attitude towards the data. Many internet companies do better in this respect, they have a wealth of data at the same time also have a strong profit demand, can make a fuss over the various data, and for many traditional industries, especially the government, they still pay much attention to data, and even more than internet companies have to pay attention, but for the administration, Organizational benefits and security considerations often result in the formation of islands difficult to achieve comprehensive utilization.

On the other hand, the challenge is to build a successful large data application needs to have a more in-depth understanding of business logic and data processing technology, and it's hard to unravel because the requirements of the business directly affect the design of the underlying architecture and the choice of algorithms and tools, which are very different from traditional trading systems. So now some industries in the SOFTWARE + database + hardware Division of labor model is not suitable for large data application development, the market can be a comprehensive consideration of various factors for the overall structure of the company is not many.

Trend of my understanding, now technical level of tools, technology is a hundred-place situation, the reason is that the open source project operating mode is more and more mature, on the other hand, the analysis of large data processing is diverse, I believe that the future will maintain this situation for a long time, Traditional software development has gradually shifted to service providers, the product itself may become more and more unimportant, customized architecture and solutions to fit user needs may be more popular, and the continuous development of cloud computing will make future architectural design easier, deployment and migration more convenient.

The prospects for future big data are enormous, now people's lives can not be separated from large data, cloud computing, cloud storage, electricity and so on site data are large data, but the development of large data technology or challenges, technology development of new technologies are constantly updated, so the challenge of large data applications is the combination of new technologies, Algorithms that continually optimize large data.

Large data storage technology, parallel computing, throughput

After reading the probation-like chapter of the inspiration:

The big data is just beginning, is breaking the development, facing great opportunities and challenges, mass to be mined data, data segmentation algorithm, distributed graph calculation to understand the depth of large data, there are many to learn, I feel the shortcomings of their own, big data refueling, you will be better, I watch you Oh, Hope you can take me to fly higher, go,go ...