Modern Information Retrieval
Lineage tracing for general data warehouse transformations
The VLDB Journal — The International Journal on Very Large Data Bases
WebTables: exploring the power of tables on the web
Proceedings of the VLDB Endowment
Data integration flows for business intelligence
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
An Enhanced Extract-Transform-Load System for Migrating Data in Telecom Billing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Learning string transformations from examples
Proceedings of the VLDB Endowment
Schema Normalization for Improving Schema Matching
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
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Extract-Transform-Load (Etl) tools are used for the creation, maintenance, and evolution of data warehouses, data marts, and operational data stores. Etl workflows populate those systems with data from various data sources by specifying and executing a DAG of transformations. Over time, hundreds of individual workflows evolve as new sources and new requirements are integrated into the system. The maintenance and evolution of large-scale Etl systems requires much time and manual effort. A key problem is to understand the meaning of unfamiliar attribute labels in source and target databases and Etl transformations. Hard-to-read attribute labels in schemata lead to frustration and time spent to develop and understand Etl workflows. We present a schema decryption technique to support Etl developers in understanding cryptic schemata of sources, targets, and Etl transformations. For a given Etl system, our recommender-like approach leverages the large number of mapped attribute labels in existing Etl workflows to produce good and meaningful decryptions. In this way we are able to decrypt attribute labels consisting of a number of unfamiliar few-letter abbreviations, such as UNP_PEN_INT , which we decrypt to UNPAID_PENALTY_INTEREST . We evaluate our schema decryption approach on three real-world repositories of Etl workflows and show that our approach is able to suggest high-quality decryptions for cryptic attribute labels in a given schema.