[PDF] A Course In In Memory Data Management eBook

Author : Hasso Plattner
Publisher : Springer
Page : 315 pages
File Size : 41,55 MB
Release : 2014-05-28
Category : Business & Economics
ISBN : 3642552706

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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.

Author : Hasso Plattner
Publisher : Springer Science & Business Media
Page : 286 pages
File Size : 30,89 MB
Release : 2012-04-17
Category : Business & Economics
ISBN : 3642295754

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In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes.

Author : Felix Gessert
Publisher : Springer Nature
Page : 199 pages
File Size : 38,73 MB
Release : 2020-05-15
Category : Computers
ISBN : 3030435067

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The unprecedented scale at which data is both produced and consumed today has generated a large demand for scalable data management solutions facilitating fast access from all over the world. As one consequence, a plethora of non-relational, distributed NoSQL database systems have risen in recent years and today’s data management system landscape has thus become somewhat hard to overlook. As another consequence, complex polyglot designs and elaborate schemes for data distribution and delivery have become the norm for building applications that connect users and organizations across the globe – but choosing the right combination of systems for a given use case has become increasingly difficult as well. To help practitioners stay on top of that challenge, this book presents a comprehensive overview and classification of the current system landscape in cloud data management as well as a survey of the state-of-the-art approaches for efficient data distribution and delivery to end-user devices. The topics covered thus range from NoSQL storage systems and polyglot architectures (backend) over distributed transactions and Web caching (network) to data access and rendering performance in the client (end-user). By distinguishing popular data management systems by data model, consistency guarantees, and other dimensions of interest, this book provides an abstract framework for reasoning about the overall design space and the individual positions claimed by each of the systems therein. Building on this classification, this book further presents an application-driven decision guidance tool that breaks the process of choosing a set of viable system candidates for a given application scenario down into a straightforward decision tree.

Author : Hasso Plattner
Publisher : Springer Science & Business Media
Page : 239 pages
File Size : 44,67 MB
Release : 2013-11-19
Category : Science
ISBN : 3319030353

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Recent achievements in hardware and software developments have enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of data, such as diagnoses, therapies, and human genome data. This book shares the latest research results of applying in-memory data management to personalized medicine, changing it from computational possibility to clinical reality. The authors provide details on innovative approaches to enabling the processing, combination, and analysis of relevant data in real-time. The book bridges the gap between medical experts, such as physicians, clinicians, and biological researchers, and technology experts, such as software developers, database specialists, and statisticians. Topics covered in this book include - amongst others - modeling of genome data processing and analysis pipelines, high-throughput data processing, exchange of sensitive data and protection of intellectual property. Beyond that, it shares insights on research prototypes for the analysis of patient cohorts, topology analysis of biological pathways, and combined search in structured and unstructured medical data, and outlines completely new processes that have now become possible due to interactive data analyses.

Author : Hasso Plattner
Publisher : Springer
Page : 284 pages
File Size : 49,69 MB
Release : 2015-12-28
Category : Business & Economics
ISBN : 3319166735

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This book describes the next generation of business applications in the innovative new SAP Business Suite 4 SAP HANA (SAP S/4HANA), exploiting the revolutionary capabilities of the SAP HANA in-memory database. Numerous real-world examples are presented illustrating the disruptive potential of this technology and the quantum leap it has facilitated in terms of simplicity, flexibility, and speed for new applications. The intuitive structure of this book offers a straightforward business perspective grounded in technology in order to enable valuable business insights drawn from the wealth of real-world experience of the book’s two authors, both prominent figures in the field of business application systems: Hasso Plattner and Bernd Leukert. Hasso Plattner is the co-founder of SAP and the founder of the Hasso Plattner Institute, affiliated with the University of Potsdam, Germany. Bernd Leukert is a member of the SAP Executive Board and the Global Managing Board of SAP.

Author : Peter Langkafel
Publisher : Walter de Gruyter GmbH & Co KG
Page : 258 pages
File Size : 32,38 MB
Release : 2015-11-27
Category : Computers
ISBN : 3110445743

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Big Data in medical science – what exactly is that? What are the potentials for healthcare management? Where is Big Data at the moment? Which risk factors need to be kept in mind? What is hype and what is real potential? This book provides an impression of the new possibilities of networked data analysis and "Big Data" – for and within medical science and healthcare management. Big Data is about the collection, storage, search, distribution, statistical analysis and visualization of large amounts of data. This is especially relevant in healthcare management, as the amount of digital information is growing exponentially. An amount of data corresponding to 12 million novels emerges during the time of a single hospital stay. These are dimensions that cannot be dealt with without IT technologies. What can we do with the data that are available today? What will be possible in the next few years? Do we want everything that is possible? Who protects the data from wrong usage? More importantly, who protects the data from NOT being used? Big Data is the "resource of the 21st century" and might change the world of medical science more than we understand, realize and want at the moment. The core competence of Big Data will be the complete and correct collection, evaluation and interpretation of data. This also makes it possible to estimate the frame conditions and possibilities of the automation of daily (medical) routine. Can Big Data in medical science help to better understand fundamental problems of health and illness, and draw consequences accordingly? Big Data also means the overcoming of sector borders in healthcare management. The specialty of Big Data analysis will be the new quality of the outcomes of the combination of data that were not related before. That is why the editor of the book gives a voice to 30 experts, working in a variety of fields, such as in hospitals, in health insurance or as medical practitioners. The authors show potentials, risks, concrete practical examples, future scenarios, and come up with possible answers for the field of information technology and data privacy.

Author : Hasso Plattner
Publisher : Springer Science & Business Media
Page : 286 pages
File Size : 49,55 MB
Release : 2012-05-14
Category : Business & Economics
ISBN : 3642295746

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This book examines for the first time, the ways that in-memory computing is changing the way businesses are run. The authors describe techniques that allow analytical and transactional processing at the speed of thought and enable new ways of doing business.

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 1946 pages
File Size : 48,89 MB
Release : 2018-10-19
Category : Computers
ISBN : 1522575995

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From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.

Author : Rajiv Chopra
Publisher : S. Chand Publishing
Page : 824 pages
File Size : 47,63 MB
Release : 2010
Category : Computers
ISBN : 8121932459

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Many books on Database Management Systems (DBMS) are available in the market, they are incomplete very formal and dry. My attempt is to make DBMS very simple so that a student feels as if the teacher is sitting behind him and guiding him. This text is bolstered with many examples and Case Studies. In this book, the experiments are also included which are to be performed in DBMS lab. Every effort has been made to alleviate the treatment of the book for easy flow of understanding of the students as well as the professors alike. This textbook of DBMS for all graduate and post-graduate programmes of Delhi University, GGSIPU, Rajiv Gandhi Technical University, UPTU, WBTU, BPUT, PTU and so on. The salient features of this book are: - 1. Multiple Choice Questions 2. Conceptual Short Questions 3. Important Points are highlighted / Bold faced. 4. Very lucid and simplified approach 5.Bolstered with numerous examples and CASE Studies 6. Experiments based on SQL incorporated. 7. DBMS Projects added Question Papers of various universities are also included.

Author : Kristin Briney
Publisher : Pelagic Publishing Ltd
Page : 312 pages
File Size : 43,15 MB
Release : 2015-09-01
Category : Computers
ISBN : 178427013X

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A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin