| 000 -LEADER |
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| fixed length control field |
a |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20191016095811.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
191016b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
AIKTC-KRRC |
| Transcribing agency |
AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
9878 |
| Author |
Onyeabor, Grace Amina |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Data Quality Evaluation Framework for Big Data |
| 250 ## - EDITION STATEMENT |
|---|
| Volume, Issue number |
Vol.5(2), Jul-Dec |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Tamil Nadu |
| Name of publisher, distributor, etc. |
i-manager's |
| Year |
2018 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Pagination |
27-35p. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Data is an important asset in all business organizations of today. Thus the results of its poor quality can be very grievous leading to erroneous insights. Therefore, Data Quality (DQ) needs to be evaluated before the analysis of any Big Data (BD). The evaluation of DQ in BD is challenging. Given the enormous datasets that are of varied format fashioned at a rapid speed, it is impossible to use the traditional methods of evaluating DQ in BD. Rather, there is a requirement of strategies and devices for the assessment and evaluation of DQ in BD in a rapid and more efficient manner. However, assessing the quality of data on the whole BD can be very expensive. In addition, there is also a need for improvement in data transformation activities of BD. This paper proposes a framework for DQ evaluation with the application of data sampling technique on BD sets from different data sources reducing the size of the data to samples representing the population of the BD sets. The Bag of Little Bootstrap (BLB) sampling technique will be used. The target Data Quality Dimensions (DQDs) to be used in this paper are completeness, consistency, and accuracy. In addition, the DQDs will be measured using different metric functions relevant to the DQDs. This will be done before and after an improved data transformation techniques to check the improvement of DQ in BD. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
4622 |
| Topical term or geographic name entry element |
Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
9879 |
| Co-Author |
Azman Ta'a |
| 773 0# - HOST ITEM ENTRY |
|---|
| Place, publisher, and date of publication |
Nagercoil i-manager Publication |
| Title |
i-manager's journal on cloud computing (JCC) |
| International Standard Serial Number |
2349-6835 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| URL |
https://www.imanagerpublications.com/article/15692/23 |
| Link text |
Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Articles Abstract Database |
