A New Metadata Model to Uniformly Handle Heterogeneous Data Lake Sources

Diamantini, Claudia; Giudice, Paolo Lo; Musarella, Lorenzo; Potena, Domenico; Storti, Emanuele; Ursino, Domenico

doi:10.1007/978-3-030-00063-9_17

Cited by 28 publications

(34 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We proposed a metadata typology for data lakes. It is based on the object notion, which represents any set of homogeneous data [5], and the typology declines metadata into three categories. Intra-object metadata describe objects through versions, representations and various properties to name a few ; interobject metadata explain how objects are linked together ; and global metadata facilitate and improve data analyses and the use of the data lake in general.…”

Section: First Results and Future Outcomesmentioning

confidence: 99%

“…We believe that the analytic atom concept, combined with the object notion [5], will help us propose a metadata system for a data lake efficient enough to manage any type of data, Big Data included. Although several studies have already been carried out on metadata systems for data lakes, and some of them have proven their efficiency [9, 10, 2], we believe we can offer a more complete metadata system that offers all the features we consider essential, and thus completely meets our expectations.…”

Section: The Phd Projectmentioning

confidence: 99%

See 1 more Smart Citation

Business Intelligence & Analytics Applied to Public Housing

Scholly

2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

Business Intelligence, with data warehouses, reporting and OnLine Analytical Processing (OLAP) are about twenty years old technologies, they are mastered and widely used in companies. Their goal is to collect, organize, store and analyse data to support decision-making. In parallel, there are many algorithms from Data Science for conducting advanced data analyses, including the ability to conduct predictive analyses. However, the reflection on the integration of Data Science methods into reporting or OLAP analysis is relatively incomplete, although there is a real demand from companies to integrate prediction into decisionmaking processes. In the meantime, with the rise of the Internet, the proliferation of multimedia data (sound, image, video, etc.), and the fast development of social networks, data has become massive, heterogeneous, of diverse and rapid varieties. The Big Data phenomenon challenges the process of data storage and analysis and creates new research problems. The PhD thesis is at the junction of these three main topics : Business Intelligence, Data Science and Big Data. The objective is to propose an approach, a framework and finally an architecture allowing prediction to be made in a decision-making process, but with a Big Data perspective.

show abstract

Section: First Results and Future Outcomesmentioning

confidence: 99%

Section: The Phd Projectmentioning

confidence: 99%

Business Intelligence & Analytics Applied to Public Housing

Scholly

2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

show abstract

“…For example, a textual document can be represented without stopwords or as a bag of words. It is essential in the context of data lakes to at least partially structure unstructured data to allow their automated analysis [5]. Simultaneously storing several representations of the same data notably avoids repeating preprocessings and thus speeds up analyses.…”

Section: Expected Featuresmentioning

confidence: 99%

“…Thus, such features are often integrated together in a provenance tracking module [12,13,27]. Yet, we still consider that they remain different features since they are not systematically proposed together [3,5,26].…”

Section: Expected Featuresmentioning

confidence: 99%

See 1 more Smart Citation

Metadata Systems for Data Lakes: Models and Features

Sawadogo

Scholly

Favre

et al. 2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

2 BIAL-X https://www.bial-x.com/ Abstract. Over the past decade, the data lake concept has emerged as an alternative to data warehouses for storing and analyzing big data. A data lake allows storing data without any predefined schema. Therefore, data querying and analysis depend on a metadata system that must be efficient and comprehensive. However, metadata management in data lakes remains a current issue and the criteria for evaluating its effectiveness are more or less nonexistent. In this paper, we introduce MEDAL, a generic, graph-based model for metadata management in data lakes. We also propose evaluation criteria for data lake metadata systems through a list of expected features. Eventually, we show that our approach is more comprehensive than existing metadata systems.

show abstract

Textual Data Analysis from Data Lakes

Sawadogo¹

2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

A New Metadata Model to Uniformly Handle Heterogeneous Data Lake Sources

Cited by 28 publications

References 16 publications

Business Intelligence & Analytics Applied to Public Housing

Business Intelligence & Analytics Applied to Public Housing

Metadata Systems for Data Lakes: Models and Features

Textual Data Analysis from Data Lakes

Contact Info

Product

Resources

About