Updating derived relations: detecting irrelevant and autonomously computable updates
ACM Transactions on Database Systems (TODS)
Incremental maintenance of views with duplicates
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A relational model of data for large shared data banks
Communications of the ACM
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
Conceptual modeling for ETL processes
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
Incremental Recomputation of Active Relational Expressions
IEEE Transactions on Knowledge and Data Engineering
Data Integration using Self-Maintainable Views
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Efficient Snapshot Differential Algorithms for Data Warehousing
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Incremental Maintenance of Materialized Views
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
A Method for Change Computation in Deductive Databases
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Comparing Very Large Database Snapshots
Comparing Very Large Database Snapshots
Optimizing ETL Processes in Data Warehouses
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Mapping conceptual to logical models for ETL processes
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Incremental maintenance of aggregate and outerjoin expressions
Information Systems
The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data
Incremental maintenance for non-distributive aggregate functions
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Orchid: Integrating Schema Mapping and ETL
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Graph-based modeling of ETL activities with multi-level transformations and updates
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
A data warehouse approach to semantic integration of pseudomonas data
DILS'10 Proceedings of the 7th international conference on Data integration in the life sciences
International Journal of Intelligent Information and Database Systems
Lazy ETL in action: ETL technology dates scientific data
Proceedings of the VLDB Endowment
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Extract, Transform, and Load (ETL) processes physically integrate data from multiple, heterogeneous sources in a central repository referred to as data warehouse. Physically integrated data gets stale when source data is changed, hence periodic refreshes are required. For efficiency reasons data warehouses are typically refreshed incrementally, i.e. changes are captured at the sources and propagated to the data warehouse on a regular basis. Dedicated ETL processes referred to as incremental load processes are employed to extract changes from the sources, propagate the changes, and refresh the data warehouse incrementally. Changes required in the data warehouse are inferred from changes captured at the sources during change propagation. The creation of incremental load processes is a complex task reserved to trained ETL programmers. In this paper we review existing Change Data Capture (CDC) techniques and discuss limitations of different approaches. We further review existing techniques for refreshing data warehouses. We then present an approach for generating incremental load processes from abstract schema mappings.