Title
Data Shapes and Data Transformations
Abstract
Nowadays, information management systems deal with data originating from different sources including relational databases, NoSQL data stores, and Web data formats, varying not only in terms of data formats, but also in the underlying data model. Integrating data from heterogeneous data sources is a time-consuming and error-prone engineering task; part of this process requires that the data has to be transformed from its original form to other forms, repeating all along the life cycle. With this report we provide a principled overview on the fundamental data shapes tabular, tree, and graph as well as transformations between them, in order to gain a better understanding for performing said transformations more efficiently and effectively.
Year
Venue
Field
2012
CoRR
Data warehouse,Semi-structured data,Data modeling,Data mining,Computer science,Data mapping,Data element,Logical data model,NoSQL,Data model,Database
DocType
Volume
Citations 
Journal
abs/1211.1565
3
PageRank 
References 
Authors
0.80
1
3
Name
Order
Citations
PageRank
Michael Hausenblas147852.35
Boris Villazón-terrazas219021.23
Richard Cyganiak33204189.59