The extract, transform, and load (ETL) process is at the core of data warehousing
architectures. As such, the success of data warehouse (DW) projects is essentially based on …

In order to create better decisions for business analytics, organizations increasingly use
external data, structured, semi-structured and unstructured, in addition to the (mostly …

A key challenge in current Business Analytics (BA) is the selection of suitable indicators for
business objectives. This requires the exploration of business data through data-driven …

Sažetak Big data have analytical potential that was hard to realize with available
technologies. After new storage paradigms intended for big data such as NoSQL databases …

The popularity of the Semantic Web (SW) encourages organizations to organize and publish
semantic data using the RDF model. This growth poses new requirements to Business …

Business intelligence (BI) systems depend on efficient integration of disparate and often
heterogeneous data. The integration of data is governed by data-intensive flows and is …

Extraction transformation loading (ETL) processes play an increasingly important role for the
support of modern business operations. These business processes are centred around …

The purpose of this book is to question the relationships involved in decision making and the
systems designed to support it: decision support systems (DSS). The focus is on how these …

Comprehensively describing data analytics requirements is becoming an integral part of
develo** enterprise information systems. It is a challenging task for analysts to completely …

Data-intensive flows are central processes in today's business intelligence (BI) systems,
deploying different technologies to deliver data, from a multitude of data sources, in user …