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Big Data are growing at an exponential rate and it becomes necessary the use of tools and technologies to manage, process and visualize them in order to extract value. In this paper a micro-service based platform is presented for the…
One of the challenges currently problems in the use of cloud services is the task of designing of specialized data management systems. This is especially important for hybrid systems in which the data are located in public and private…
This paper examines how a "Distributed Heterogeneous Relational Data Warehouse" can be integrated in a Grid environment that will provide physicists with efficient access to large and small object collections drawn from databases at…
The technique of database refactoring is all about applying disciplined and controlled techniques to change an existing database schema. The problem is to successfully create a Database Refactoring Framework for databases. This paper…
The availability of both structured and unstructured databases, such as electronic health data, social media data, patent data, and surveys that are often updated in real time, among others, has grown rapidly over the past decade. With this…
F\"ur eine fr\"uhzeitige Erkennung von Lieferengp\"assen m\"ussen Lieferketten in einer geeigneten digitalen Form vorliegen, damit sie verarbeitet werden k\"onnen. Der f\"ur die Datenmodellierung ben\"otigte Arbeitsaufwand ist jedoch,…
During the last two decades, it has been increasingly acknowledged that the engineering of information systems usually requires a huge effort in integrating master data and business processes. This has led to a plethora of proposals, both…
This work provides a framework for a workspace aware online grasp planner. This framework greatly improves the performance of standard online grasp planning algorithms by incorporating a notion of reachability into the online grasp planning…
This is a thought piece on data-intensive science requirements for databases and science centers. It argues that peta-scale datasets will be housed by science centers that provide substantial storage and processing for scientists who access…
Anyone in need of a data system today is confronted with numerous complex options in terms of system architectures, such as traditional relational databases, NoSQL and NewSQL solutions as well as several sub-categories like column-stores,…
Current automation approaches in the Industry 4.0 have generated increased interest in the utilization of Integration Platforms as a Service (iPaaS) cloud architectures in order to unify and synchronize several systems, applications, and…
We suggest a new web-based approach for browsing and visualizing data produced by a network of telescopes, such as those of the ongoing TAOS and the forthcoming TAOS II projects. We propose a modern client-side technology and we present two…
Management of data in education sector particularly management of data for big universities with several employees, departments and students is a very challenging task. There are also problems such as lack of proper funds and manpower for…
The application of Deep Learning and Natural Language based ChatBots are growing rapidly in recent years. They are used in many fields like customer support, reservation system and as personal assistant. The Enterprises are using such…
Efficient data exploration is crucial as data becomes increasingly important for accelerating processes, improving forecasts and developing new business models. Data consumers often spend 25-98 % of their time searching for suitable data…
Tabular data is a common form of organizing data. Multiple models are available to generate synthetic tabular datasets where observations are independent, but few have the ability to produce relational datasets. Modeling relational data is…
The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as…
Data lakes have emerged as an alternative to data warehouses for the storage, exploration and analysis of big data. In a data lake, data are stored in a raw state and bear no explicit schema. Thence, an efficient metadata system is…
Many questions in computational social science rely on datasets assembled from heterogeneous online sources, a process that is often labor-intensive, costly, and difficult to reproduce. Recent advances in large language models enable…
Data wrangling tasks such as obtaining and linking data from various sources, transforming data formats, and correcting erroneous records, can constitute up to 80% of typical data engineering work. Despite the rise of machine learning and…