Big Data Analysis Based Intelligent Technology

"Big data" is not just large amounts of information but rather it's about in-depth mining the big data to capture valuable information from the vast data to utilize. Today, more and more applications involve big data. With the progress of The Times, the feature of big data, no longer confined to 3Vs: Volume, Velocity and Variety. It is presenting new Vs: Value, Veracity and Viability. Big data contains a low proportion of useful information and has strong timeliness in specific situations. Moreover, it also involves a large amount of uncertain or imprecise information. Veracity deals with those information to guarantee a reliable result. In the more popular words, big data analytics technology refers to the process of collecting, storage, analysing and visualizing large sets of data to obtain high value information by solving the above “V” problems.

Data-indexing is working closely with the well-known research institutions to help enterprises to improve the data application efficiently in a variety of data patterns. This helps to ensure that clients have much choice in expanding of big data mining to achieve specific objectives. Clients can obtain key solution for any type of data through our service. We are now in the age of data revolution and it will be a long-term challenge to keep up with the pace of the explosive growth of data. The real winners will be those who control the information flow and make the best use of analysis throughout the value chain.


  1. Visual Analysis
  2. Users of big data analysis are not limited only to experts but also ordinary users. And visual analysis is the most basic requirement from both of them. Because the visual analysis can intuitively show characteristics of big data, at the same time, it is very easily accepted by users. We help clients integrate various data types and show the underlying trends as well as characteristics of the data intuitively and dynamically in charts and graphics form.

  3. Data Mining Algorithm
  4. The theoretical foundation of big data is data mining algorithms. Based on different data types and formats, data mining algorithms can show the characteristics of data itself more scientifically. It is precisely because of these world recognized statistical methods that deeper value of the data can be extracted. On the other side, these data mining algorithms can make the big data processing faster. Without good methods, there would be no value to speak of. Hence we can provide customized data mining algorithms upon client's request.

  5. Predictive Analysis
  6. Predictive analysis is one of the most important applications of big data analysis, mining characteristics from big data, scientifically establishing the model and importing new data into it to predict the future data. We can predict the future client behavior, operational opportunities and risk through statistics, modeling and data collection to help clients make business strategy for future development.

  7. Semantic Engine
  8. Big data analysis is widely used in internet data mining, analyzing and judging the needs of users from their search keyword, keyword tag or other input semantics. Semantic engine can free users from complex search entries and make it faster, more accurately and comprehensive to get information, thus achieving a better user experience and advertising matching,

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