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Enterprise data warehouses work on the concept of schema-on-write but Big Data analytics want data storage which works on the schema-on-read concept. To fulfill market demand, researchers are working on a new data repository system for Big Data storage known as a data lake. The data lake is defined as a data landing area for raw data from many sources. There is some confusion and questions which must be answered about data lakes. The objective of this article is to reduce the confusion and address some question about data lakes with the help of architecture.<\/p>","DOI":"10.4018\/ijoci.2020010104","type":"journal-article","created":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T04:45:11Z","timestamp":1575002711000},"page":"63-75","source":"Crossref","is-referenced-by-count":19,"title":["Data Lake Architecture"],"prefix":"10.4018","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9957-6365","authenticated-orcid":true,"given":"Arvind","family":"Panwar","sequence":"first","affiliation":[{"name":"GGSIP University, Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vishal","family":"Bhatnagar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Ambedkar Institute of Advanced Communication Technologies and Research, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJOCI.2020010104-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2016.05.017"},{"key":"IJOCI.2020010104-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2014.08.003"},{"key":"IJOCI.2020010104-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.datak.2017.08.003"},{"key":"IJOCI.2020010104-3","doi-asserted-by":"crossref","unstructured":"Belle, A., Thiagarajan, R., Soroushmehr, S. 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