Handling Mislaid/Missing Data to Attain Data Trait
Sakshi Jolly1, Neha Gupta2
1Ms. Sakshi Jolly, Research Scholar, Department of Computer and Information Technology, Manav Rachna International University, Faridabad, Haryana, India.
2Dr. Neha Gupta*, PhD, Department of Computer and Information Technology, Manav Rachna International University, Faridabad, Haryana, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 4308-4311 | Volume-8 Issue-12, October 2019. | Retrieval Number: L27221081219/2019©BEIESP | DOI: 10.35940/ijitee.L2722.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Missing data are depicted as a piece of the qualities in the educational accumulation are either lost or not seen or not open because of customary or non typical reasons. Information with missing characteristics befuddles both the information examination and the convenience of a response for new information. Various experts are dealing with this issue to introduce increasingly present day methods. Notwithstanding the way that different frameworks are available, specialists are confronting burden in searching for a reasonable technique in perspective on non appearance of information about the methodology and their suitability. This investigation paper additionally arranges a formal review of the missing data framework. It examines the strategies that are dismembered in the made works and observations that the makers have made.
Keywords: Data quality (DQ), Data Warehouse (DW), ETL(Extraction Transformation Loading)
Scope of the Article: Aggregation, Integration, and Transformation