The Golem In The Machine: FERPA, Dirty Data, and Digital Distortion in the Education Record

2020 ◽  
Author(s):  
Najarian Peters
Keyword(s):  
Dirty Data ◽  
Digital Distortion

Sampling dirty data for matching attributes

2010 ◽  
Author(s):  
Henning Köhler ◽  
Xiaofang Zhou ◽  
Shazia Sadiq ◽  
Yanfeng Shu ◽  
Kerry Taylor
Keyword(s):  
Dirty Data

Between the Spreadsheets

2021 ◽  
Author(s):  
Susan Walsh
Keyword(s):  
Data Quality ◽  
Deep Understanding ◽  
Data Classification ◽  
Dirty Data ◽  
Quality Issues ◽  
Book Covers ◽  
Level Of Experience ◽  
The Impact

Dirty data is a problem that costs businesses thousands, if not millions, every year. In organisations large and small across the globe you will hear talk of data quality issues. What you will rarely hear about is the consequences or how to fix it.<br><br><i>Between the Spreadsheets: Classifying and Fixing Dirty Data</i> draws on classification expert Susan Walsh's decade of experience in data classification to present a fool-proof method for cleaning and classifying your data. The book covers everything from the very basics of data classification to normalisation, taxonomies and presents the author's proven <b>COAT</b> methodology, helping ensure an organisation's data is <b>Consistent</b>, <b>Organised</b>, <b>Accurate</b> and <b>Trustworthy</b>. A series of data horror stories outlines what can go wrong in managing data, and if it does, how it can be fixed. <br><br>After reading this book, regardless of your level of experience, not only will you be able to work with your data more efficiently, but you will also understand the impact the work you do with it has, and how it affects the rest of the organisation.<br><br>Written in an engaging and highly practical manner, <i>Between the Spreadsheets</i> gives readers of all levels a deep understanding of the dangers of dirty data and the confidence and skills to work more efficiently and effectively with it.

A Discovery Method of the Dirty Data Transmission Path Based on Complex Network

2014 ◽  
Vol 651-653 ◽  
pp. 1741-1747
Author(s):  
Xiao Lin Zhao ◽  
Gang Hao ◽  
Chang Zhen Hu ◽  
Zhi Qiang Li
Keyword(s):  
Complex Network ◽  
Data Transmission ◽  
Software System ◽  
Power Law Distribution ◽  
Scale Free ◽  
Transmission Path ◽  
Binary File ◽  
Weighted Directed Graph ◽  
Dirty Data ◽  
Discovery Method

With the increasing scale of software system, the interaction between software elements becomes more and more complex, which lead to the increased dirty data in running software system. This may reduce the system performance and cause system collapse. In this paper, we proposed a discovery method of the dirty data transmission path based on complex network. Firstly, the binary file is decompiled and the function call graph is drawn by using the source code. Then the software structure is described as a weighted directed graph based on the knowledge of complex network. In addition, the dirty data node is marked by using the power-law distribution characteristics of the scale-free network construction of complex network chart. Finally, we found the dirty data transmission path during software running process. The experimental results show the transmission path of dirty data is accurate, which confirmed the feasibility of the method.

Dirty Data Management in Cloud Database

2011 ◽  
pp. 133-150 ◽  
Author(s):  
Hongzhi Wang ◽  
Jianzhong Li ◽  
Jinbao Wang ◽  
Hong Gao
Keyword(s):  
Data Management ◽  
Dirty Data ◽  
Cloud Database

Novel Statistical Analyses in Terrestrial Animal Ecology; Dirty Data and Clean Questions

1987 ◽  
pp. 559-572 ◽  
Author(s):  
D. Simberloff ◽  
P. Berthet ◽  
V. Boy ◽  
S. H. Cousins ◽  
M.-J. Fortin ◽  
...  
Keyword(s):  
Animal Ecology ◽  
Statistical Analyses ◽  
Terrestrial Animal ◽  
Dirty Data

Urban Tunnel Clean up the Dirty Data Based on Clara Optimization Clustering

2013 ◽  
Vol 13 (11) ◽  
pp. 1980-1983 ◽  
Author(s):  
KunHao Tang ◽  
Luo Zhong ◽  
Lin Li ◽  
Guang Yang
Keyword(s):  
Dirty Data
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