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  1. Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP (DOLAP '09)
  2. pygrametl: a powerful programming framework for extract-transform-load programmers
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Discovering functional dependencies for multidimensional design
A taxonomy of ETL activities
pygrametl: a powerful programming framework for extract-transform-load programmers
Consistency-aware evaluation of OLAP queries in replicated data warehouses
Dimension table driven approach to referential partition relational data warehouses
Automatic generation of ETL processes from conceptual models
Cardinality estimation in ETL processes
Query recommendations for OLAP discovery driven analysis
A comprehensive approach to data warehouse testing
Defining ETL worfklows using BPMN and BPEL
Generating data quality rules and integration into ETL process
LMDQL: link-based and multidimensional query language
View usability and safety for the answering of top-k queries via materialized views

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pygrametl: a powerful programming framework for extract-transform-load programmers

Content Provider ACM Digital Library
Author Thomsen, Christian Bach Pedersen, Torben
Abstract Extract-Transform-Load (ETL) processes are used for extracting data, transforming it and loading it into data warehouses (DWs). Many tools for creating ETL processes exist. The dominating tools all use graphical user interfaces (GUIs) where the developer visually defines the data flow and operations. In this paper, we challenge this approach and propose to do ETL programming by writing code. To make the programming easy, we present the (Python-based) framework pygrametl which offers commonly used functionality for ETL development. By using the framework, the developer can efficiently create effective ETL solutions from which the full power of programming can be exploited. Our experiments show that when pygrametl is used, both the development time and running time are short when compared to an existing GUI-based tool.
Starting Page 49
Ending Page 56
Page Count 8
File Format PDF
ISBN 9781605588018
DOI 10.1145/1651291.1651301
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-11-06
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Data warehouse (dw) Extract-transform-load (etl) Python
Content Type Text
Resource Type Article
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