Big Data Mining


Big Data Mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interesting metrics, post-processing of discovered structures & visualization. As is the analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records, anomaly detection, and dependencies.

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What is the SECNOLOGY vision on Data Mining ?

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SECNOLOGY is a turnkey, intuitive, universal Big Data Mining solution with a breakthrough technology and a unique architecture.  With SECNOLOGY, users are able to process years of data and billions of records a day as well as access to all their information instantly.

SECNOLOGY’s vision & construct is at the crossroads of Data Mining & Big Data. Our aim is to offer massive scalability without the complexity of traditional solutions.

It is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including machine learning, and business intelligence. It is also is the process of applying these methods with the intention of uncovering hidden patterns in large data sets.

Big Data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them. Challenges include analysis, capture, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term “big data” often refers simply to the use of predictive user behavior & analytics, or methods that extract value from data, and seldom to a particular size of data set.

Data grow

Data sets grow rapidly - in part because they are increasingly gathered by cheap and numerous information-sensing mobile devices, software logs, cameras, microphones, RFID readers and wireless sensor networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the'80s; as of 2012, every year almost 1 Zettabyte of data is generated.


Relational database management systems and desktop statistics & visualization packages often have difficulty handling big data. The work may require ``massively parallel software running on tens, hundreds, or even thousands of servers``. What counts as ``big data`` varies depending on the capabilities of the users and their tools. Until now products like Hadoop were the gold standard despite its intricate architecture.

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We focus strongly on the feature, ease of use, power and simplicity of our secnology solution to help you effectively secure your information system and quickly reach your goals. We guarantee a quality customer service dedicated to the satisfaction of each customer.