The software processes that facilitate the original loading and the periodic refreshment of the
data warehouse contents are commonly known as Extraction-Transformation-Loading (ETL) …

There is an abundance of data, but a large volume of it is unusable. Data may be noisy,
unstructured, stored in incompatible for direct analysis medium or format, and often …

Extract, Transform, and Load (ETL) processes physically integrate data from multiple,
heterogeneous sources in a central repository referred to as data warehouse. Physically …

We present HYPPO, a novel system to optimize pipelines encountered in exploratory
machine learning. HYPPO exploits alternative computational paths of artifacts from past …

Abstract Extraction-transformation-loading (ETL) processes play an important role in a data
warehouse (DW) architecture because they are responsible of integrating data from …

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 …

In this paper, we discuss the problem of performing impact prediction for changes that occur
in the schema/structure of the data warehouse sources. We abstract Extract-Transform-Load …

Extract-transform-load (ETL) tools are primarily designed for data warehouse loading, ie to
perform physical data integration. When the operational data sources happen to change, the …

The extract, transform and Load (ETL) tool is extracting data from multiple, heterogeneous
data source, transforming data, and finally loading data into the data warehouse. It is the …

In this paper, we deal with the problem of performing what-if analysis for changes that occur
in the schema/structure of the data warehouse sources. We abstract software modules …