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Books in Database management

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21-30 of 161 results in All results

Building a Scalable Data Warehouse with Data Vault 2.0

  • 1st Edition
  • September 15, 2015
  • Daniel Linstedt + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 2 5 1 0 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 2 6 4 8 - 9
The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.

Data Analysis in the Cloud

  • 1st Edition
  • September 15, 2015
  • Domenico Talia + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 2 8 8 1 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 2 9 1 4 - 5
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis.

Structured Search for Big Data

  • 1st Edition
  • August 26, 2015
  • Mikhail Gilula
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 4 6 3 1 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 4 6 5 2 - 4
The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big Data are arguably the most notable. Structured Search paradigm connects them via a fundamental concept of key-objects evolving out of keywords as the units of search. The key-object data model and KeySQL revamp the data independence principle making it applicable for Big Data and complement NoSQL with full-blown structured querying functionality. The ultimate goal is extracting Big Information from the Big Data. As a Big Data Consultant, Mikhail Gilula combines academic background with 20 years of industry experience in the database and data warehousing technologies working as a Sr. Data Architect for Teradata, Alcatel-Lucent, and PayPal, among others. He has authored three books, including The Set Model for Database and Information Systems and holds four US Patents in Structured Search and Data Integration.

Securing SQL Server

  • 3rd Edition
  • April 23, 2015
  • Denny Cherry
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 1 2 7 5 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 3 7 5 - 5
SQL server is the most widely-used database platform in the world, and a large percentage of these databases are not properly secured, exposing sensitive customer and business data to attack. In Securing SQL Server, Third Edition, you will learn about the potential attack vectors that can be used to break into SQL server databases as well as how to protect databases from these attacks. In this book, Denny Cherry - a Microsoft SQL MVP and one of the biggest names in SQL server - will teach you how to properly secure an SQL server database from internal and external threats using best practices as well as specific tricks that the author employs in his role as a consultant for some of the largest SQL server deployments in the world. Fully updated to cover the latest technology in SQL Server 2014, this new edition walks you through how to secure new features of the 2014 release. New topics in the book include vLANs, setting up RRAS, anti-virus installs, key management, moving from plaintext to encrypted values in an existing application, securing Analysis Services Objects, Managed Service Accounts, OS rights needed by the DBA, SQL Agent Security, Table Permissions, Views, Stored Procedures, Functions, Service Broker Objects, and much more.

Multi-Domain Master Data Management

  • 1st Edition
  • March 21, 2015
  • Mark Allen + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 0 8 3 5 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 1 4 7 - 8
Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration.

CMDB Systems

  • 1st Edition
  • March 20, 2015
  • Dennis Drogseth + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 1 2 6 5 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 3 7 3 - 1
CMDB Systems: Making Change Work in the Age of Cloud and Agile shows you how an integrated database across all areas of an organization’s information system can help make organizations more efficient reduce challenges during change management and reduce total cost of ownership (TCO). In addition, this valuable reference provides guidelines that will enable you to avoid the pitfalls that cause CMDB projects to fail and actually shorten the time required to achieve an implementation of a CMDB. Drawing upon extensive experience and using illustrative real world examples, Rick Sturm, Dennis Drogseth and Dan Twing discuss: Unique insights from extensive industry exposure, research and consulting on the evolution of CMDB/CMS technology and ongoing dialog with the vendor community in terms of current and future CMDB/CMS design and plans Proven and structured best practices for CMDB deployments Clear and documented insights into the impacts of cloud computing and other advances on CMDB/CMS futures

Data Mining and Predictive Analysis

  • 2nd Edition
  • December 30, 2014
  • Colleen McCue
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 0 2 2 9 - 2
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 0 4 0 8 - 1
Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings.This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.

Reliability Assurance of Big Data in the Cloud

  • 1st Edition
  • December 9, 2014
  • Yun Yang + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 2 5 7 2 - 7
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 2 6 6 8 - 7
With the rapid growth of Cloud computing, the size of Cloud data is expanding at a dramatic speed. A huge amount of data is generated and processed by Cloud applications, putting a higher demand on cloud storage. While data reliability should already be a requirement, data in the Cloud needs to be stored in a highly cost-effective manner. This book focuses on the trade-off between data storage cost and data reliability assurance for big data in the Cloud. Throughout the whole Cloud data lifecycle, four major features are presented: first, a novel generic data reliability model for describing data reliability in the Cloud; second, a minimum replication calculation approach for meeting a given data reliability requirement to facilitate data creation; third, a novel cost-effective data reliability assurance mechanism for big data maintenance, which could dramatically reduce the storage space needed in the Cloud; fourth, a cost-effective strategy for facilitating data creation and recovery, which could significantly reduce the energy consumption during data transfer.

How to Define and Build an Effective Cyber Threat Intelligence Capability

  • 1st Edition
  • December 5, 2014
  • Henry Dalziel
  • Eric Olson + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 2 7 3 0 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 2 7 5 2 - 3
Intelligence-Led Security: How to Understand, Justify and Implement a New Approach to Security is a concise review of the concept of Intelligence-Led Security. Protecting a business, including its information and intellectual property, physical infrastructure, employees, and reputation, has become increasingly difficult. Online threats come from all sides: internal leaks and external adversaries; domestic hacktivists and overseas cybercrime syndicates; targeted threats and mass attacks. And these threats run the gamut from targeted to indiscriminate to entirely accidental. Among thought leaders and advanced organizations, the consensus is now clear. Defensive security measures: antivirus software, firewalls, and other technical controls and post-attack mitigation strategies are no longer sufficient. To adequately protect company assets and ensure business continuity, organizations must be more proactive. Increasingly, this proactive stance is being summarized by the phrase Intelligence-Led Security: the use of data to gain insight into what can happen, who is likely to be involved, how they are likely to attack and, if possible, to predict when attacks are likely to come. In this book, the authors review the current threat-scape and why it requires this new approach, offer a clarifying definition of what Cyber Threat Intelligence is, describe how to communicate its value to business, and lay out concrete steps toward implementing Intelligence-Led Security.

Predictive Analytics and Data Mining

  • 1st Edition
  • November 27, 2014
  • Vijay Kotu + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 1 4 6 0 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 1 6 5 0 - 3
Put Predictive Analytics into ActionLearn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to:1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com