big data analytics turning big data into big money

A modular big data platform can solve 80% of the big data problems. To solve the other 20% of the problems, big data platform vendors must meet the special needs of industry customers for customized development. ZTE's DAP 2.0

big data Services for AWS, Azure and Google. Amazon Web Services AWS offers a very broad range of big data services. For example, Amazon elastic MapReduce can run Hadoop and Spark, while Kinesis Firehose and Kinesis Streams provide a way to import large datasets into AWS. Users can store

7 months, my * * * for "Big Data operation" in the crowdfunding network launched a book pre-sale activities, the amount of money , from the project initiated two days and a half, that Friday afternoon to Sunday night, Over the completion of the predetermined target, very shocking. In the end, a total of 102 supporters, in addition to the two selfless supporters,

Data visualization technology can help people to understand the large amount of data information and discover the laws hidden in the data, so as to improve the efficiency of the data using the visual thinking ability of the human brain. In the face of big Data's profundity,

described above several algorithms, but will not feel the information from the big data is too little point, With a lot of problems just through the above several algorithms are not extrapolated, but this information happens to be the top leaders concerned, for example, said:1. As a data analyst, can you predict the sales performance of the next year according t

Big Data Glossary The emergence of big data has brought about many new terms, but these terms are often hard to understand. Therefore, we use this article to provide a frequently-used big data glossary for your in-depth understand

distributed in the computing resources, and can freely expand computing resources and storage space. The platform is capable of processing petabytes of data and is characterized by high reliability, high scalability, high efficiency and fault tolerance. The processing of massive data is realized by high-speed processing technology, and the data security analysis

A few years ago, the company focused on information technology and Internet technology, and today, the company is more focused on cloud computing, mobile technology and social technology. Regardless of the development trend of the above-mentioned technologies, the processing and analysis of company data has caused a lot of problems. The diversity of data and the security of

ability, machine learning ability under the guidance of algorithm, such as neural network (nonlinear regression), neural network is a very fire model in learning algorithm.The distinction between data mining and machine learning is:Data mining problems generally have huge data, especially the problem that the computational efficiency is more important than the statistic precision, usually stand in the comm

our best customer base (will buy bicycles), which is described above several algorithms, but will not feel the information from the big data is too little point, With a lot of problems just through the above several algorithms are not extrapolated, but this information happens to be the top leaders concerned, for example, said:1. As a data analyst, can you predi