4. Data processing In the data processing stage, the input data is transformed, analyzed, and organized to produce relevant information. Several data processing techniques, like filtering, sorting, aggregation, or classification, may be employed to process the data. The choice of methods depends on...
Data profiling.This is the process of examining, analyzing and reviewing data to collect statistics about its quality.Data profilingstarts with a survey of existing data and its characteristics. Data scientists identify data sets pertinent to the problem at hand, inventory their attributes and form a...
Process mining is a data-driven technique used to understand, track, and improve processes by analyzing data from information systems.Applications such as CRM and ERP systems as well as other systems of record automatically create event logs that record every action taken. The data in these logs...
Data annotation process here includes training data of pairs of sentences in different languages. Each pair will consist of an input sentence(in English) and an output sentence(in French). The source sentence serves as an input for the encoder, and the target is the output of the decoder. ...
Data generating processt distributionBayesian analysisAs the usual normality assumption is firmly rejected by the data, investors encounter a data-generating process (DGP) uncertainty in making investment decisions. In this paper, we propose a novel way to incorporate uncertainty about the DGP into ...
However, the downside of data erasure is that it is a time-consuming process, is difficult to carry out during the lifetime of the device, and requires that each decommissioned device goes through a strict sanitization process. Cryptographic Erasure ...
SAS (Statistical Analysis System) software suite is used for advanced analytics, business intelligence, and data management. Apache Spark is an open-source, distributed computing system that can process large-scale data and perform advanced analytics. Jupyter Notebooks is an open-source web application...
When the data becomes obsolete, every copy is deleted and destroyed as part of the removal process. The data destruction process might include the media on which the data resides. This data lifecycle flowchart describes each step involved in data management. Why is data lifecycle management impor...
Data visualization refers to the practice of representing data using visual formats such as tables, charts, graphs, and maps.
Data parsing is the process of taking data in one format and transforming it to another format. This is particulary interesting for web scraping.