Open AccessManaging Data Acquisition, Cleansing and Transformation in an Agriculture Data Warehouse
Author(s) -
Abdul Ghani Kanesan Abdullah,
Fuad Bajaber
Publication year - 2016
Publication title -
journal of agricultural studies
Language(s) - English
Resource type - Journals
ISSN - 2166-0379
DOI - 10.5296/jas.v4i1.8583
Subject(s) - agriculture , data collection , data quality , yield (engineering) , data warehouse , business , data cleansing , quality (philosophy) , agricultural economics , agricultural science , geography , database , computer science , economics , marketing , environmental science , mathematics , metric (unit) , philosophy , statistics , materials science , archaeology , epistemology , metallurgy
Pakistan is the world’s fourth largest cotton producer. The country relies heavily on cotton yield to sustain and enhance its export and economic growth. Several state run organizations have been monitoring the cotton crop for decades through pest-scouting, agriculture and meteorological data-gathering processes. This non-digitized and non-standardized dirty data is of little use for strategic analysis and decision support. This paper is based on the data collection and cleansing issues of that cotton pest-scouting data consisting of approximately 15,000 sheets from 20 cotton-growing districts of Punjab province. Various real-life agriculture data management and data quality problems are discussed and explained in this paper using several real examples.