The data transformation platform is to remove the data analysis bottleneck. It uses visualization, machine learning methods and predictive interaction technology to remove a critical data in the big data stack turning raw data into a usable form. Currently, the data scientist, IT programmers, and business analyst must work through the time-consuming challenge of transforming the data into the workable inputs for their analytic tools. The data scientist spends as much as sixty to eighty percentage of their time just transforming data rather than focusing on finding insights. The human bottleneck is hindering the ability of the enterprise to extract value from the data. The data transformation platform uses predictive interaction technology to elevate the data manipulation into the visual experience. It allows the user to quickly and easily identify the features of interest or concern. The predictive algorithms observe both the user behavior and the properties of the data to anticipate the user’s intent and make the suggestion without the need for the user specification.
As a result, the data transformation becomes a lightweight experience that is far agiler and effective than traditional coding or manual manipulation. It uses the visual approach to data transformation providing the user with the continuous visual feedback. The content of the data set if affected when the different transforms are applied. Trifacta enhances the value of an enterprise’s big data by enabling the users to easily transform the raw, complex data into clean and the structured formats for the analysis of the data. the data transformation platform users can process the data value of any volume the users can scale their data transformation from immediate execution on small data through the interactive execution on medium sized data, all the way to the execution of terabytes to petabytes. Its platform addresses the complete range of processing use cases available on the Hadoop software.