A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years
Published on 29. May 2017
IX, 502 pages
978-3-319-61893-7 (ISBN)
Description
This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present-and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research.
The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.
More details
Series
Edition
1st ed. 2018
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
IX, 502 p. 95 illus.
File size
12,90 MB
ISBN-13
978-3-319-61893-7 (9783319618937)
DOI
10.1007/978-3-319-61893-7
Schweitzer Classification
Other editions
Additional editions
Sergio Flesca | Sergio Greco | Elio Masciari
A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years
Book
06/2017
Springer
€213.99
Shipment within 10-15 days
Persons
Content
The visual side of the data.- Digital Libraries: From Digital Resources to Challenges in Scienti?c Data Sharing and Re-use.- From Data Integration to Big Data Integration.- Matching Techniques for Data Integration and Exploration: fromDatabases to Big Data.- 25+ Years of Query Processing - From a Single, Stored Data Set to Big Data.- From Star Schemas to Big Data: 20+ Years of Data Warehouse Research.- A short account of techniques for assisting users in mastering BigData.- Multimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs.- Dealing with Inconsistency in Databases: An Overview.- First-order Ontology Mediated Database Querying via Query Reformulation.- Using ontologies for semantic data integration.- Schema Mappings: from Data Translation to Data Cleaning.
