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Books > Computing & IT > Applications of computing > Databases > Data mining
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A Course in In-Memory Data Management - The Inner Mechanics of In-Memory Databases (Hardcover, 2nd ed. 2014)
Loot Price: R3,441
Discovery Miles 34 410
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A Course in In-Memory Data Management - The Inner Mechanics of In-Memory Databases (Hardcover, 2nd ed. 2014)
Expected to ship within 10 - 15 working days
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Recent achievements in hardware and software development, such as
multi-core CPUs and DRAM capacities of multiple terabytes per
server, enabled the introduction of a revolutionary technology:
in-memory data management. This technology supports the flexible
and extremely fast analysis of massive amounts of enterprise data.
Professor Hasso Plattner and his research group at the Hasso
Plattner Institute in Potsdam, Germany, have been investigating and
teaching the corresponding concepts and their adoption in the
software industry for years. This book is based on an online course
that was first launched in autumn 2012 with more than 13,000
enrolled students and marked the successful starting point of the
openHPI e-learning platform. The course is mainly designed for
students of computer science, software engineering, and IT related
subjects, but addresses business experts, software developers,
technology experts, and IT analysts alike. Plattner and his group
focus on exploring the inner mechanics of a column-oriented
dictionary-encoded in-memory database. Covered topics include -
amongst others - physical data storage and access, basic database
operators, compression mechanisms, and parallel join algorithms.
Beyond that, implications for future enterprise applications and
their development are discussed. Step by step, readers will
understand the radical differences and advantages of the new
technology over traditional row-oriented, disk-based databases. In
this completely revised 2nd edition, we incorporate the feedback of
thousands of course participants on openHPI and take into account
latest advancements in hard- and software. Improved figures,
explanations, and examples further ease the understanding of the
concepts presented. We introduce advanced data management
techniques such as transparent aggregate caches and provide new
showcases that demonstrate the potential of in-memory databases for
two diverse industries: retail and life sciences.
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