Related papers: Modeling Data Lake Metadata with a Data Vault
Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, that is designed for data sharing, search and analysis. A comparative study of existing repositories is performed to analyze…
Presently, large enterprises rely on database systems to manage their data and information. These databases are useful for conducting daily business transactions. However, the tight competition in the marketplace has led to the concept of…
Increasing amounts of structured data can provide value for research and business if the relevant data can be located. Often the data is in a data lake without a consistent schema, making locating useful data challenging. Table search is a…
Over the past decade, the proliferation of public and enterprise data lakes has fueled intensive research into data discovery, aiming to identify the most relevant data from vast and complex corpora to support diverse user tasks.…
The data warehousing and OLAP technologies are now moving onto handling complex data that mostly originate from the Web. However, intagrating such data into a decision-support process requires their representation under a form processable…
As information becomes increasingly sizable for organizations to maintain the challenge of organizing data still remains. More importantly, the on-going process of analysing incoming data occurs on a continual basis and organizations should…
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…
The variety of data in data lakes presents significant challenges for data analytics, as data scientists must simultaneously analyze multi-modal data, including structured, semi-structured, and unstructured data. While Large Language Models…
In this paper, we study the data warehouse modelling used in decision support systems. We provide an object-oriented data warehouse model allowing data warehouse description as a central repository of relevant, complex and temporal data.…
Ensembles of classifier models typically deliver superior performance and can outperform single classifier models given a dataset and classification task at hand. However, the gain in performance comes together with the lack in…
The Data Web refers to the vast and rapidly increasing quantity of scientific, corporate, government and crowd-sourced data published in the form of Linked Open Data, which encourages the uniform representation of heterogeneous data items…
Machine-learning from a disparate set of tables, a data lake, requires assembling features by merging and aggregating tables. Data discovery can extend autoML to data tables by automating these steps. We present an in-depth analysis of such…
The exponential growth of big data has transformed how large organisations leverage information to drive innovation, optimise processes, and maintain competitive advantages. However, managing and extracting insights from vast, heterogeneous…
Data warehouses are nowadays an important component in every competitive system, it's one of the main components on which business intelligence is based. We can even say that many companies are climbing to the next level and use a set of…
A method for representing the digest information of each dataset is proposed, oriented to the aid of innovative thoughts and the communication of data users who attempt to create valuable products, services, and business models using or…
Data warehouse, data lake, data lakehouse, data mesh ... many new names for analytical data architectures are currently circulating in the scene. But are the various approaches really so different? This article attempts a structured…
Data commons collate data with cloud computing infrastructure and commonly used software services, tools and applications to create biomedical resources for the large-scale management, analysis, harmonization, and sharing of biomedical…
In recent past, big data opportunities have gained much momentum to enhance knowledge management in organizations. However, big data due to its various properties like high volume, variety, and velocity can no longer be effectively stored…
Complex systems' modeling and simulation are powerful ways to investigate a multitude of natural phenomena providing extended knowledge on their structure and behavior. However, enhanced modeling and simulation require integration of…
The knowledge of the world is passed on through libraries. Accordingly, domain expertise and experiences should also be transferred within an enterprise by a knowledge base. Therefore, models are an established medium to describe good…