CONTROL OF ENERGY EFFICIENCY IN INDUSTRY AND HOUSING AND COMMUNAL SERVICES
Sign | Register
UDC 004.4
Improvement in data quality in the context of modern analytical technologies
Vladimir Nickolaevich Lyubitsyn, Candidate of Science (Engineering), Associate Professor of Information and Analytical Support in Social and Economic Systems Management Department, South Ural State University, Chelyabinsk, Russian Federation, lvn_iaou@mail.ru
Abstract
Identification of the term "data quality" with respect to the information-analytical systems is made in the article. Division of methods for enhancing the quality of the data into groups and species is carried out. Assessment of data quality as a key element of IT-related technology connected with management of data quality is emphasized. To form an effective methodology for assessing the data classification of stages of the process for assessing data quality is given, and brief comparative analysis is provided, data quality problems based on three levels, indicating the specificity of each of them, including the relevant factors, manifestations and control sites with identified problems, are systematized.
Keywords
information-analytical system, data warehouse, data quality, ETL-process, data cleaning, data preprocessing, data enrichment, data quality assessment tool
References
1. Hank, D.EH. Biznes-prognozirovanie: per. s angl. / D.EH. Hank, D.U. Uichern, A.D. Rajts. – 7-e izd. – M.: Izdat. dom «Vil'yams», 2003. – 651 s.
2. Tekhnologii analiza dannyh: Data Mining, Visual Mining, Text Mining, OLAP / A.A. Barsegyan i dr. – 2-e izd., pererab. i dop. – SPb.: BHV-Peterburg, 2007. – 384 s.
3. Paklin, N.B. Biznes-analitika: ot dannyh k znaniyam / N.B. Paklin. – SPb.: Piter, 2009. – 624 s.
4. Prikladnaya informatika: ucheb. posobie / pod red. V.N. Volkovoj i V.N. YUr'eva. – M.: Finansy i statistika: Infra-M, 2008. – 768 s.
5. Revyakin, S.A. O vazhnosti kachestvennoj informacii dlya prinyatiya upravlencheskih reshenij. – http://www.global-katalog.ru/cncat_jump.php?13146
2. Tekhnologii analiza dannyh: Data Mining, Visual Mining, Text Mining, OLAP / A.A. Barsegyan i dr. – 2-e izd., pererab. i dop. – SPb.: BHV-Peterburg, 2007. – 384 s.
3. Paklin, N.B. Biznes-analitika: ot dannyh k znaniyam / N.B. Paklin. – SPb.: Piter, 2009. – 624 s.
4. Prikladnaya informatika: ucheb. posobie / pod red. V.N. Volkovoj i V.N. YUr'eva. – M.: Finansy i statistika: Infra-M, 2008. – 768 s.
5. Revyakin, S.A. O vazhnosti kachestvennoj informacii dlya prinyatiya upravlencheskih reshenij. – http://www.global-katalog.ru/cncat_jump.php?13146
Source
Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control, Radio Electronics, 2012, iss. 16, no. 23 (282), pp. 83-86. (in Russ.) (The main)