Books in Database management

Data Architecture: A Primer for the Data Scientist

1st Edition
November 26, 2014
W.H. Inmon + 1 more
English
Paperback
9 7 8 0 1 2 8 0 2 0 4 4 9
eBook
9 7 8 0 1 2 8 0 2 0 9 1 3

Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist. Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to: Turn textual information into a form that can be analyzed by standard tools. Make the connection between analytics and Big Data Understand how Big Data fits within an existing systems environment Conduct analytics on repetitive and non-repetitive data

Enterprise Business Intelligence and Data Warehousing

1st Edition
November 24, 2014
Alan Simon
English
Paperback
9 7 8 0 1 2 8 0 1 5 4 0 7
eBook
9 7 8 0 1 2 8 0 1 7 4 6 3

Corporations and governmental agencies of all sizes are embracing a new generation of enterprise-scale business intelligence (BI) and data warehousing (DW), and very often appoint a single senior-level individual to serve as the Enterprise BI/DW Program Manager. This book is the essential guide to the incremental and iterative build-out of a successful enterprise-scale BI/DW program comprised of multiple underlying projects, and what the Enterprise Program Manager must successfully accomplish to orchestrate the many moving parts in the quest for true enterprise-scale business intelligence and data warehousing. Author Alan Simon has served as an enterprise business intelligence and data warehousing program management advisor to many of his clients, and spent an entire year with a single client as the adjunct consulting director for a $10 million enterprise data warehousing (EDW) initiative. He brings a wealth of knowledge about best practices, risk management, organizational culture alignment, and other Critical Success Factors (CSFs) to the discipline of enterprise-scale business intelligence and data warehousing.

Social Data Analytics

1st Edition
November 10, 2014
Krish Krishnan + 1 more
English
Paperback
9 7 8 0 1 2 3 9 7 1 8 6 9
eBook
9 7 8 0 1 2 3 9 7 7 8 0 9

Social Data Analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease. You'll learn everything you need to know to monitor social media and get an overview of the leading vendors in a crowded space of BI applications. By the end of this book, you will be well prepared for your organization’s next social data analytics project.

Business Intelligence Guidebook

1st Edition
November 4, 2014
Rick Sherman
English
Paperback
9 7 8 0 1 2 4 1 1 4 6 1 6
eBook
9 7 8 0 1 2 4 1 1 5 2 8 6

Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success.

Modern Enterprise Business Intelligence and Data Management

1st Edition
August 28, 2014
Alan Simon
English
Paperback
9 7 8 0 1 2 8 0 1 5 3 9 1
eBook
9 7 8 0 1 2 8 0 1 7 4 5 6

Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the "Big Data Era"…and most see a critical need to revitalize their current capabilities. Whether they find the frustrating and business-impeding continuation of a long-standing "silos of data" problem, or an over-reliance on static production reports at the expense of predictive analytics and other true business intelligence capabilities, or a lack of progress in achieving the long-sought-after enterprise-wide "single version of the truth" – or all of the above – IT Directors, strategists, and architects find that they need to go back to the drawing board and produce a brand new BI/data warehousing roadmap to help move their enterprises from their current state to one where the promises of emerging technologies and a generation’s worth of best practices can finally deliver high-impact, architecturally evolvable enterprise-scale business intelligence and data warehousing. Author Alan Simon, whose BI and data warehousing experience dates back to the late 1970s and who has personally delivered or led more than thirty enterprise-wide BI/data warehousing roadmap engagements since the mid-1990s, details a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale. Simon addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic.

Bitemporal Data

1st Edition
August 19, 2014
Tom Johnston
English
Paperback
9 7 8 0 1 2 4 0 8 0 6 7 6
eBook
9 7 8 0 1 2 4 0 8 0 5 5 3

Bitemporal data has always been important. But it was not until 2011 that the ISO released a SQL standard that supported it. Currently, among major DBMS vendors, Oracle, IBM and Teradata now provide at least some bitemporal functionality in their flagship products. But to use these products effectively, someone in your IT organization needs to know more than how to code bitemporal SQL statements. Perhaps, in your organization, that person is you. To correctly interpret business requests for temporal data, to correctly specify requirements to your IT development staff, and to correctly design bitemporal databases and applications, someone in your enterprise needs a deep understanding of both the theory and the practice of managing bitemporal data. Someone also needs to understand what the future may bring in the way of additional temporal functionality, so their enterprise can plan for it. Perhaps, in your organization, that person is you. This is the book that will show the do-it-yourself IT professional how to design and build bitemporal databases and how to write bitemporal transactions and queries, and will show those who will direct the use of vendor-provided bitemporal DBMSs exactly what is going on "under the covers" of that software.

Time and Relational Theory

2nd Edition
July 16, 2014
C.J. Date + 2 more
English
Paperback
9 7 8 0 1 2 8 0 0 6 3 1 3
eBook
9 7 8 0 1 2 8 0 0 6 7 5 7

Time and Relational Theory provides an in-depth description of temporal database systems, which provide special facilities for storing, querying, and updating historical and future data. Traditionally, database management systems provide little or no special support for temporal data at all. This situation is changing because: Cheap storage enables retention of large volumes of historical data in data warehouses Users are now faced with temporal data problems, and need solutions Temporal features have recently been incorporated into the SQL standard, and vendors have begun to add temporal support to their DBMS products Based on the groundbreaking text Temporal Data & the Relational Model (Morgan Kaufmann, 2002) and new research led by the authors, Time and Relational Theory is the only book to offer a complete overview of the functionality of a temporal DBMS. Expert authors Nikos Lorentzos, Hugh Darwen, and Chris Date describe an approach to temporal database management that is firmly rooted in classical relational theory and will stand the test of time. This book covers the SQL:2011 temporal extensions in depth and identifies and discusses the temporal functionality still missing from SQL.

Concurrency Control in Distributed Database Systems

1st Edition
Volume 3
June 28, 2014
W. Cellary + 2 more
English
eBook
9 7 8 1 4 8 3 2 9 4 6 4 3

Distributed Database Systems (DDBS) may be defined as integrated database systems composed of autonomous local databases, geographically distributed and interconnected by a computer network.The purpose of this monograph is to present DDBS concurrency control algorithms and their related performance issues. The most recent results have been taken into consideration. A detailed analysis and selection of these results has been made so as to include those which will promote applications and progress in the field. The application of the methods and algorithms presented is not limited to DDBSs but also relates to centralized database systems and to database machines which can often be considered as particular examples of DDBSs.The first part of the book is devoted to basic definitions and models: the distributed database model, the transaction model and the syntactic and semantic concurrency control models. The second discusses concurrency control methods in monoversion DDBSs: the locking method, the timestamp ordering method, the validation method and hybrid methods. For each method the concept, the basic algorithms, a hierarchical version of the basic algorithms, and methods for avoiding performance failures are given. The third section covers concurrency control methods in multiversion DDBSs and the fourth, methods for the semantic concurrency model. The last part concerns performance issues of DDBSs.The book is intended primarily for DDBMS designers, but is also of use to those who are engaged in the design and management of databases in general, as well as in problems of distributed system management such as distributed operating systems and computer networks.

Deductive and Object-Oriented Databases

1st Edition
June 28, 2014
W. Kim + 2 more
English
eBook
9 7 8 1 4 8 3 2 9 8 1 9 1

Deductive databases and object-oriented databases are at the forefront of research in next-generation intelligent database systems.Object-orien... programming and design methodologies have great potential, promising to reduce the complexity of very large software systems in such domains as computer-aided design and manufacturing, integrated office information systems, and artificial intelligence. Object-oriented database systems will enhance the programmer/user productivity of such systems. Research into deductive databases is aimed at discovering efficient schemes to uniformly represent assertions and deductive rules, and to respond to highly expressive queries against the knowledge base of assertions and rules. This area of research is strongly interacting with Logic Programming which has developed in parallel, sharing Logic as a common basis. Recently, research has aimed at integrating the object-oriented paradigm and rule-based deduction to provide a single powerful framework for intelligent database systems.The aim of this book is to present research papers and technical discussions between researchers concerned with deductive databases, object-oriented databases, and their integration.

Interoperable Database Systems (DS-5)

1st Edition
Volume 25
May 23, 2014
D.K. Hsiao + 2 more
English
eBook
9 7 8 1 4 8 3 2 9 8 4 7 4

The proliferation of databases within organizations have made it imperative to allow effective sharing of information from these disparate database systems. In addition, it is desirable that the individual systems must maintain a certain degree of autonomy over their data in order to continue to provide for their existing applications and to support controlled access to their information. Thus it becomes necessary to develop new techniques and build new functionality to interoperate these autonomous database systems and to integrate them into an overall information system. Research into interoperable database systems has advanced substantially over recent years in response to this need.The papers presented in this volume cover a wide spectrum of both theoretical and pragmatic issues related to the semantics of interoperable database systems. Topics covered include techniques to support the translation between database schema and between database languages; object oriented frameworks for supporting interoperability of heterogeneous databases, knowledge base integration and techniques for overcoming schematic discrepancies in interoperable databases. In addition, there are papers addressing issues of security transaction processing, data modelling and object identification in interoperable database systems. It is hoped the publication will represent a valuable collective contribution to research and development in the field for database researchers, implementors, designers, application builders and users alike.

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