Big Data Age: how valuable is the data?

With the deep application of large data in various fields, the value of large data itself is being highlighted, researchers and business users to analyze large data, is to insight into the real needs of customers.

The data is valuable, the company can not leave the data, but how valuable is the data? How much does it cost to analyze large data and gain value from it?

In the past, technical experts provided senior management with historical data so they could identify http://www.aliyun.com/zixun/aggregation/10240.html "> Market trends." Statistical data, while helpful in understanding market trends at a higher level and how organizations do markets, is not enough to determine what new products or services need to be developed. These statistics don't tell you what customers really want.

Analysts, researchers and business users analyze big data to make decisions faster and better. By using advanced analytical techniques such as word analysis, machine learning, predictive analysis, data mining, and statistics, companies can analyze previously untapped data.

Companies generate large amounts of data and are able to collect information from other sources, including mobile applications, sensors, Web sites, click-Stream data, and social media activities. This data can be turned into a product.

Collecting and analyzing large amounts of data, especially unstructured data, is not an easy task. The company's system is now equipped to handle 500TB of data per week, so there is no way to dig up the nuggets that help companies develop new products and services that customers need. This has led companies to look for high-performance computing resources that can solve problems, such as weather and climate forecasts, parametric modeling and stochastic modeling, to deal with large-scale commercial data.

Large data analysis utilizes analytical techniques to analyze a very large and diverse set of data, including structured/unstructured, stream data, or batch processing data, and varies widely in scale, ranging from TB to PB or ZB. It examines different data types to discover patterns hidden in them, unknown associations, and other useful information.

D1net Comments:

Thus, the above information can provide competitive advantage to competitors, the result is commercial interests, such as more effective marketing and income increase. High-Performance Computational data analysis (HPDA) is a term used to describe the market shift in data-intensive HPC markets and high-end business data analysis, which is the embodiment of data value.