The success of companies hugely depends on how well they can analyze the available data
and extract meaningful knowledge. The Extract-Transform-Load (ETL) process is …

The growing importance of data analytics is leading to a shift in data management strategy
at many companies, moving away from simple data storage towards adopting Online …

NoSQL Database is one solution that can be used to store large amounts of data and have
an excellent performance during the reading and writing process. Analysis of data with large …

NoSQL Database Manager Systems (DBMS) are an alternative to analytical systems and
have been used in this regard. As analytical systems often use data multidimensional …

Today, the relational database is not suitable for data management due to the large variety
and volume of data which are mostly untrusted. Therefore, NoSQL has attracted the attention …

When engineering complex systems, models are typically used to represent various systems
aspects. These models are often heterogeneous in terms of modeling languages …

Column-oriented stores, known for their scalability and flexibility, are a common NoSQL
database implementation and are increasingly used in big data management. In column …

Due to unstructured and large amounts of data, relational databases are no longer suitable
for data management. As a result, new databases known as NOSQL have been introduced …

The data warehouse design methodologies require a novel approach in the Big Data
context, because the methodologies have to provide solutions to face the issues related to …

Typical data warehouse systems are implemented either on a relational database or on a
multi-dimensional database. While the former supports ROLAP operations the latter …