Analysis of AI based Data Wrangling Methods in Intelligent Knowledge Lakes

Abstract

A novel conception of Knowledge Lake, i.e., a Contextualized Data Lake is to be soundly educated. The deliberated big-data practices pave a means for the erection of Intelligent Knowledge Lakes and that being the resources for big-data applications and analytics. This analysis likewise opens the welfares, disputes, and exploration prospects of Intelligent Knowledge Lakes. Data Science is launched as an influential discernment through businesses. Organizations today are dedicated on transforming their facts into ultra-practical intuitions. This work is challenging, as in present day’s intelligence, amenity and cloud customary budget trades accumulate immense aggregates of unprocessed data after a variety of funds. Data Lakes are familiar as a packing depository that fetch concurrently the unprocessed data in its innate set-up (sustaining to NoSQL from relational databases) which is crucial. The logic behind Data Lake is to stockpile unprocessed data and let the data analyst resolve the way to curate them well ahead of reviewing the idea of Knowledge Lake, which is an anecdotal Data Lake. The Intelligent Knowledge Lake stipulate the basis for big data analytics by robotically curating the unprocessed data in the Data Lake grooming these for stemming intuitions via programmed interactive real-time optimized data wrangling in intelligent knowledge lakes. Computerization of an exposed free public Data and Knowledge Lake amenity provides developers and researchers a distinct REST API to systematize, curate, catalog and interrogate their data and metadata in the Lake for a longer time. It administers manifold database/databank know-hows (from Relational to NoSQL) that deals with an inherent scheme for data security, curation, and provenance.