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FOR BIG DATA ANALYSIS

How it is working

Trifacta uses the mechanism named predictive interaction, where the user does not have to precisely specify data transformation before data analysis.
In fact, users model the data in Trifecta, highlighting the interesting characteristics in the visualisation (such as e.g. in Big Data semantic analysis). Therefore, the user makes his choices and devises his own analyses using Trifacta prediction methods, which suggest a variety of possible steps of data transformation leading to the understanding of their actual meaning, which in turn, makes it possible to formulate a strategy.
Trifacta, thanks to Machine Learning, from the very beginning classifies, in the order from the highest to the lowest possibility, the transformation and manipulation of data needed by the user, together with the collected data; it communicates directly with Hadoop.
Trifacta is a platform, which supports automatic data profiling in order to accelerate and guide company data cleansing and to integrate self-service of data from different sources.
Moreover, the users can do numerous activities connected with analysis by making selections. For example, on drop-down-lists you can select an appropriate data cleansing transformation form each column in order to improve the data quality profile. Trifacta can take over the functions of Machine Learning coming also from different tools, such as Sentiment Analysis and many other.

Therefore, Trifacta allows:

visual exploration, transformation, cleansing and unifying different sources of data; the solution gives intelligent recommendations for data cleansing and formatting, which otherwise would remain raw data

using advanced self-service data reparation for teams and departments and using a common platform for data preparation by means of machine learning of the platform owner, or eventually joining with other advanced analytical platforms; Talifacta platform automatises contrast operations, including different sources

Distributing a platform to order and understand business data for big and complex projects (Big Data collected in a long period of time and in a great amount)

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Progetto di Camillo Manera / Sviluppato da
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