Over the past two decades, we have witnessed an exponential increase of data production
in the world. So-called big data generally come from transactional systems, and even more …

Data lakes are becoming increasingly prevalent for Big Data management and data
analytics. In contrast to traditional 'schema-on-write'approaches such as data warehouses …

The variety feature of Big Data, represented by multi-model data, has brought a new
dimension of complexity to all aspects of data management. The need to process a set of …

During the development of NoSQL-backed software, the database schema evolves
alongside the application code. Especially in agile development, new application releases …

Recent position papers demand more schema flexibility, such as the ability to handle
variational data [3, 42]. Many agile software developers have long since turned towards …

ABSTRACT A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of
data. It accumulates substantial volumes of data and employs advanced analytics to …

Data-driven methods and data science are important scientific methods in many research
fields. All data science approaches require professional data engineering components. At …

In the last years, data lakes are emerging as an effective and an efficient support for
information and knowledge extraction from a huge amount of highly heterogeneous and …

When NoSQL database systems are used in an agile software development setting, data
model changes occur frequently and thus, data is routinely stored in different versions. The …

With data lakes and schema-free NoSQL document stores, extracting a descriptive schema
from JSON data collections is an acute challenge. In this paper, we target the discovery of …