Data accuracy using natural language processing

A method comprising:

• receiving, by a processor, a data from a repository, wherein the retriever receives the data based on a data receiving rule;
• generating, by the processor, a first dataset from the received data using statistical modeling;
• generating, by the processor, a first data veracity score for the dataset of the data, wherein the first data veracity score is indicative of a degree of usability of the dataset;
• identifying, by the processor, an anomaly in the first dataset, wherein the identifying comprises ascertaining an optimal correction technique from amongst a plurality of correction techniques to substantially remove the anomaly, wherein the identifying comprises, based on a type of the data, determining one of a machine learning model from amongst a plurality of machine learning models and a statistical data analysis technique from amongst a plurality of statistical data analysis techniques as the optimal correction technique;
• and
• generating, by the processor, a second dataset using the optimal correction technique, wherein the generating comprises generating a second data veracity score for the second dataset, the second data veracity score being higher than the first data veracity score.

A non-transitory computer medium including computer-readable instructions which, when executed, causes a processor to:

• receive data from a repository, wherein the data based on a data receiving rule;
• generate a first dataset from the received data, wherein the first dataset is generated using statistical modeling;
• generate a first data veracity score for the first dataset of the data, wherein the first data veracity score is indicative of a degree of usability of the first dataset;
• identify an anomaly in the first dataset, wherein the processor is to identify an optimal correction technique from amongst a plurality of correction techniques to substantially remove the anomaly, wherein the processor is to determine, based on a type of the data, one of a machine learning model from amongst a plurality of machine learning models and a statistical data analysis technique from amongst a plurality of statistical data analysis techniques as the optimal correction technique;
• and
• generate a second dataset using the identified correction technique, wherein a second data veracity score is generated for the second dataset, the second data veracity score being higher than the first data veracity score.