In recent years, real-time processing and analytics systems for big data--in the context of
Business Intelligence (BI)--have received a growing attention. The traditional BI platforms …

In this paper, we discuss the state of the art and current trends in designing and optimizing
ETL workflows. We explain the existing techniques for:(1) constructing a conceptual and a …

Smart meters are increasingly used worldwide. Smart meters are the advanced meters
capable of measuring energy consumption at a fine-grained time interval, eg, every 15 min …

Extract-transform-load (ETL) workflows model the population of enterprise data warehouses
with information gathered from a large variety of heterogeneous data sources. ETL …

With the widely used smart meters in the energy sector, anomaly detection becomes a
crucial mean to study the unusual consumption behaviors of customers, and to discover …

Among the so-called “4Vs”(volume, velocity, variety, and veracity) that characterize the
complexity of Big Data, this paper focuses on the issue of “Volume” in order to ensure good …

Extract-Transform-Load (ETL) programs process data into data warehouses (DWs). Rapidly
growing data volumes demand systems that scale out. Recently, much attention has been …

This paper demonstrates ETLMR, a novel dimensional Extract--Transform--Load (ETL)
programming framework that uses Map-Reduce to achieve scalability. ETLMR has built-in …

Big data is an opportunity in the emergence of novel business applications such as “Big
Data Analytics”(BDA). However, these data with non-traditional volumes create a real …

Extract-Transform-Load (ETL) handles large amounts of data and manages workload
through dataflows. ETL dataflows are widely regarded as complex and expensive …