Engineering Agile Big-Data Systems

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Engineering Agile Big-Data Systems
Συγγραφείς: Feeney, Kevin
Στοιχεία εκδότη: River Publishers, 2022.
Έτος έκδοσης: 2022
Original Material: MODID-943f4d11b5b:Taylor & Francis
Θεματικοί όροι: Science / Energy, Computers / Data Science / Data Analytics, Computers / Software Development & Engineering
Περιγραφή: To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems.
Τύπος εγγράφου: BOOK
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
ISBN: 978-1-00-079586-8
1-00-079586-1
Σύνδεσμος πρόσβασης: https://openresearchlibrary.org/viewer/7cbc77ed-e271-4caa-88c7-56fbc31bf35c
https://openresearchlibrary.org/ext/api/media/7cbc77ed-e271-4caa-88c7-56fbc31bf35c/assets/external_content.pdf
Αριθμός Καταχώρησης: edsors.7cbc77ed.e271.4caa.88c7.56fbc31bf35c
Βάση Δεδομένων: Open Research Library