Implementing an InfoSphere Optim Data Growth Solution

Implementing an InfoSphere Optim Data Growth Solution

Author: Whei-Jen Chen

Publisher: IBM Redbooks

Published: 2011-11-09

Total Pages: 548

ISBN-13: 0738436135

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Today, organizations face tremendous challenges with data explosion and information governance. InfoSphereTM OptimTM solutions solve the data growth problem at the source by managing the enterprise application data. The Optim Data Growth solutions are consistent, scalable solutions that include comprehensive capabilities for managing enterprise application data across applications, databases, operating systems, and hardware platforms. You can align the management of your enterprise application data with your business objectives to improve application service levels, lower costs, and mitigate risk. In this IBM® Redbooks® publication, we describe the IBM InfoSphere Optim Data Growth solutions and a methodology that provides implementation guidance from requirements analysis through deployment and administration planning. We also discuss various implementation topics including system architecture design, sizing, scalability, security, performance, and automation. This book is intended to provide various systems development professionals, Data Solution Architects, Data Administrators, Modelers, Data Analysts, Data Integrators, or anyone who has to analyze or integrate data structures, a broad understanding about IBM InfoSphere Optim Data Growth solutions. By being used in conjunction with the product manuals and online help, this book provides guidance about implementing an optimal solution for managing your enterprise application data.


Book Synopsis Implementing an InfoSphere Optim Data Growth Solution by : Whei-Jen Chen

Download or read book Implementing an InfoSphere Optim Data Growth Solution written by Whei-Jen Chen and published by IBM Redbooks. This book was released on 2011-11-09 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, organizations face tremendous challenges with data explosion and information governance. InfoSphereTM OptimTM solutions solve the data growth problem at the source by managing the enterprise application data. The Optim Data Growth solutions are consistent, scalable solutions that include comprehensive capabilities for managing enterprise application data across applications, databases, operating systems, and hardware platforms. You can align the management of your enterprise application data with your business objectives to improve application service levels, lower costs, and mitigate risk. In this IBM® Redbooks® publication, we describe the IBM InfoSphere Optim Data Growth solutions and a methodology that provides implementation guidance from requirements analysis through deployment and administration planning. We also discuss various implementation topics including system architecture design, sizing, scalability, security, performance, and automation. This book is intended to provide various systems development professionals, Data Solution Architects, Data Administrators, Modelers, Data Analysts, Data Integrators, or anyone who has to analyze or integrate data structures, a broad understanding about IBM InfoSphere Optim Data Growth solutions. By being used in conjunction with the product manuals and online help, this book provides guidance about implementing an optimal solution for managing your enterprise application data.

IBM Information Governance Solutions

IBM Information Governance Solutions

Author: Chuck Ballard

Publisher: IBM Redbooks

Published: 2014-04-04

Total Pages: 264

ISBN-13: 0738439517

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Managing information within the enterprise has always been a vital and important task to support the day-to-day business operations and to enable analysis of that data for decision making to better manage and grow the business for improved profitability. To do all that, clearly the data must be accurate and organized so it is accessible and understandable to all who need it. That task has grown in importance as the volume of enterprise data has been growing significantly (analyst estimates of 40 - 50% growth per year are not uncommon) over the years. However, most of that data has been what we call "structured" data, which is the type that can fit neatly into rows and columns and be more easily analyzed. Now we are in the era of "big data." This significantly increases the volume of data available, but it is in a form called "unstructured" data. That is, data from sources that are not as easily organized, such as data from emails, spreadsheets, sensors, video, audio, and social media sites. There is valuable information in all that data but it calls for new processes to enable it to be analyzed. All this has brought with it a renewed and critical need to manage and organize that data with clarity of meaning, understandability, and interoperability. That is, you must be able to integrate this data when it is from within an enterprise but also importantly when it is from many different external sources. What is described here has been and is being done to varying extents. It is called "information governance." Governing this information however has proven to be challenging. But without governance, much of the data can be less useful and perhaps even used incorrectly, significantly impacting enterprise decision making. So we must also respect the needs for information security, consistency, and validity or else suffer the potential economic and legal consequences. Implementing sound governance practices needs to be an integral part of the information control in our organizations. This IBM® Redbooks® publication focuses on the building blocks of a solid governance program. It examines some familiar governance initiative scenarios, identifying how they underpin key governance initiatives, such as Master Data Management, Quality Management, Security and Privacy, and Information Lifecycle Management. IBM Information Management and Governance solutions provide a comprehensive suite to help organizations better understand and build their governance solutions. The book also identifies new and innovative approaches that are developed by IBM practice leaders that can help as you implement the foundation capabilities in your organizations.


Book Synopsis IBM Information Governance Solutions by : Chuck Ballard

Download or read book IBM Information Governance Solutions written by Chuck Ballard and published by IBM Redbooks. This book was released on 2014-04-04 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing information within the enterprise has always been a vital and important task to support the day-to-day business operations and to enable analysis of that data for decision making to better manage and grow the business for improved profitability. To do all that, clearly the data must be accurate and organized so it is accessible and understandable to all who need it. That task has grown in importance as the volume of enterprise data has been growing significantly (analyst estimates of 40 - 50% growth per year are not uncommon) over the years. However, most of that data has been what we call "structured" data, which is the type that can fit neatly into rows and columns and be more easily analyzed. Now we are in the era of "big data." This significantly increases the volume of data available, but it is in a form called "unstructured" data. That is, data from sources that are not as easily organized, such as data from emails, spreadsheets, sensors, video, audio, and social media sites. There is valuable information in all that data but it calls for new processes to enable it to be analyzed. All this has brought with it a renewed and critical need to manage and organize that data with clarity of meaning, understandability, and interoperability. That is, you must be able to integrate this data when it is from within an enterprise but also importantly when it is from many different external sources. What is described here has been and is being done to varying extents. It is called "information governance." Governing this information however has proven to be challenging. But without governance, much of the data can be less useful and perhaps even used incorrectly, significantly impacting enterprise decision making. So we must also respect the needs for information security, consistency, and validity or else suffer the potential economic and legal consequences. Implementing sound governance practices needs to be an integral part of the information control in our organizations. This IBM® Redbooks® publication focuses on the building blocks of a solid governance program. It examines some familiar governance initiative scenarios, identifying how they underpin key governance initiatives, such as Master Data Management, Quality Management, Security and Privacy, and Information Lifecycle Management. IBM Information Management and Governance solutions provide a comprehensive suite to help organizations better understand and build their governance solutions. The book also identifies new and innovative approaches that are developed by IBM practice leaders that can help as you implement the foundation capabilities in your organizations.

Information Governance Principles and Practices for a Big Data Landscape

Information Governance Principles and Practices for a Big Data Landscape

Author: Chuck Ballard

Publisher: IBM Redbooks

Published: 2014-03-31

Total Pages: 280

ISBN-13: 0738439592

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This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.


Book Synopsis Information Governance Principles and Practices for a Big Data Landscape by : Chuck Ballard

Download or read book Information Governance Principles and Practices for a Big Data Landscape written by Chuck Ballard and published by IBM Redbooks. This book was released on 2014-03-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.

Developing Quality Technical Information

Developing Quality Technical Information

Author: Michelle Carey

Publisher: IBM Press

Published: 2014-06-23

Total Pages: 612

ISBN-13: 0133119025

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The #1 Guide to Excellence in Technical Communication—Fully Updated for Embedded Assistance, Mobile, Search, Multimedia, and More Direct from IBM’s own content design experts, this guide shows you how to design product interfaces and technical information that always place users front and center. This edition has been fully revised to help you consistently deliver the right content at the right time. You’ll master today’s best practices to apply nine essential characteristics of high-quality technical information: accuracy, clarity, completeness, concreteness, organization, retrievability, style, task orientation, and visual effectiveness. Coverage Includes Advocating for users throughout the entire product development process Delivering information in an ordered manner by following progressive disclosure techniques Optimizing content so that users can find it from anywhere Streamlining information for mobile delivery Helping users right where they are Whether you’re a writer, editor, information architect, user experience professional, or reviewer, this book shows you how to create great technical information, from the product design to the user interface, topics, and other media. Thoroughly revised and updated Extensive new coverage of self-documenting interfaces and embedded assistance Updated practical guidelines and checklists Hundreds of new examples


Book Synopsis Developing Quality Technical Information by : Michelle Carey

Download or read book Developing Quality Technical Information written by Michelle Carey and published by IBM Press. This book was released on 2014-06-23 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: The #1 Guide to Excellence in Technical Communication—Fully Updated for Embedded Assistance, Mobile, Search, Multimedia, and More Direct from IBM’s own content design experts, this guide shows you how to design product interfaces and technical information that always place users front and center. This edition has been fully revised to help you consistently deliver the right content at the right time. You’ll master today’s best practices to apply nine essential characteristics of high-quality technical information: accuracy, clarity, completeness, concreteness, organization, retrievability, style, task orientation, and visual effectiveness. Coverage Includes Advocating for users throughout the entire product development process Delivering information in an ordered manner by following progressive disclosure techniques Optimizing content so that users can find it from anywhere Streamlining information for mobile delivery Helping users right where they are Whether you’re a writer, editor, information architect, user experience professional, or reviewer, this book shows you how to create great technical information, from the product design to the user interface, topics, and other media. Thoroughly revised and updated Extensive new coverage of self-documenting interfaces and embedded assistance Updated practical guidelines and checklists Hundreds of new examples

Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition

Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition

Author: Whei-Jen Chen

Publisher: IBM Redbooks

Published: 2012-10-02

Total Pages: 506

ISBN-13: 0738437255

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IBM® InfoSphere® Warehouse is the IBM flagship data warehouse platform for departmental data marts and enterprise data warehouses. It offers leading architecture, performance, backup, and recovery tools that help improve efficiency and reduce time to market through increased understanding of current data assets, while simplifying the daily operations of managing complex warehouse deployments. InfoSphere Warehouse Advanced Enterprise Edition delivers an enhanced set of database performance, management, and design tools. These tools assist companies in maintaining and increasing value from their warehouses, while helping to reduce the total cost of maintaining these complex environments. In this IBM Redbooks® publication we explain how you can build a business intelligence system with InfoSphere Warehouse Advanced Enterprise to manage and support daily business operations for an enterprise, to generate more income with lower cost. We describe the foundation of the business analytics, the Data Warehouse features and functions, and the solutions that can deliver immediate analytics solutions and help you drive better business outcomes. We show you how to use the advanced analytics of InfoSphere Warehouse Advanced Enterprise Edition and integrated tools for data modeling, mining, text analytics, and identifying and meeting the data latency requirements. We describe how the performance and storage optimization features can make building and managing a large data warehouse more affordable, and how they can help significantly reduce the cost of ownership. We also cover data lifecycle management and the key features of IBM Cognos® Business Intelligence. This book is intended for data warehouse professionals who are interested in gaining in-depth knowledge about the operational business intelligence solution for a data warehouse that the IBM InfoSphere Warehouse Advanced Enterprise Edition offers.


Book Synopsis Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition by : Whei-Jen Chen

Download or read book Solving Operational Business Intelligence with InfoSphere Warehouse Advanced Edition written by Whei-Jen Chen and published by IBM Redbooks. This book was released on 2012-10-02 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: IBM® InfoSphere® Warehouse is the IBM flagship data warehouse platform for departmental data marts and enterprise data warehouses. It offers leading architecture, performance, backup, and recovery tools that help improve efficiency and reduce time to market through increased understanding of current data assets, while simplifying the daily operations of managing complex warehouse deployments. InfoSphere Warehouse Advanced Enterprise Edition delivers an enhanced set of database performance, management, and design tools. These tools assist companies in maintaining and increasing value from their warehouses, while helping to reduce the total cost of maintaining these complex environments. In this IBM Redbooks® publication we explain how you can build a business intelligence system with InfoSphere Warehouse Advanced Enterprise to manage and support daily business operations for an enterprise, to generate more income with lower cost. We describe the foundation of the business analytics, the Data Warehouse features and functions, and the solutions that can deliver immediate analytics solutions and help you drive better business outcomes. We show you how to use the advanced analytics of InfoSphere Warehouse Advanced Enterprise Edition and integrated tools for data modeling, mining, text analytics, and identifying and meeting the data latency requirements. We describe how the performance and storage optimization features can make building and managing a large data warehouse more affordable, and how they can help significantly reduce the cost of ownership. We also cover data lifecycle management and the key features of IBM Cognos® Business Intelligence. This book is intended for data warehouse professionals who are interested in gaining in-depth knowledge about the operational business intelligence solution for a data warehouse that the IBM InfoSphere Warehouse Advanced Enterprise Edition offers.

Performance Management: Using IBM InfoSphere Optim Performance Manager and Query Workload Tuner

Performance Management: Using IBM InfoSphere Optim Performance Manager and Query Workload Tuner

Author: Chuck Ballard

Publisher: IBM Redbooks

Published: 2013-11-27

Total Pages: 412

ISBN-13: 0738438456

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This IBM® Redbooks® publication describes the architecture and components of IBM InfoSphere® OptimTM Performance Manager Extended Edition. Intended for DBAs and those involved in systems performance, it provides information for installation, configuration, and deployment. InfoSphere Optim Performance Manager delivers a new paradigm used to monitor and manage database and database application performance issues. It describes product dashboards and reports and provides scenarios for how they can be used to identify, diagnose, prevent, and resolve database performance problems. IBM InfoSphere Optim Query Workload Tuner facilitates query and query workload analysis and provides expert recommendations for improving query and query workload performance. Use InfoSphere Optim Performance Manager to identify slow running queries, top CPU consumers, or query workloads needing performance improvements and seamlessly transfer them to InfoSphere Optim Query Workload Tuner for analysis and recommendations. This is done using query formatting annotated with relevant statistics, access plan graphical or hierarchical views, and access plan analysis. It further provides recommendations for improving query structure, statistics collection, and indexes including generated command syntax and rationale for the recommendations.


Book Synopsis Performance Management: Using IBM InfoSphere Optim Performance Manager and Query Workload Tuner by : Chuck Ballard

Download or read book Performance Management: Using IBM InfoSphere Optim Performance Manager and Query Workload Tuner written by Chuck Ballard and published by IBM Redbooks. This book was released on 2013-11-27 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redbooks® publication describes the architecture and components of IBM InfoSphere® OptimTM Performance Manager Extended Edition. Intended for DBAs and those involved in systems performance, it provides information for installation, configuration, and deployment. InfoSphere Optim Performance Manager delivers a new paradigm used to monitor and manage database and database application performance issues. It describes product dashboards and reports and provides scenarios for how they can be used to identify, diagnose, prevent, and resolve database performance problems. IBM InfoSphere Optim Query Workload Tuner facilitates query and query workload analysis and provides expert recommendations for improving query and query workload performance. Use InfoSphere Optim Performance Manager to identify slow running queries, top CPU consumers, or query workloads needing performance improvements and seamlessly transfer them to InfoSphere Optim Query Workload Tuner for analysis and recommendations. This is done using query formatting annotated with relevant statistics, access plan graphical or hierarchical views, and access plan analysis. It further provides recommendations for improving query structure, statistics collection, and indexes including generated command syntax and rationale for the recommendations.

Deployment Guide for InfoSphere Guardium

Deployment Guide for InfoSphere Guardium

Author: Whei-Jen Chen

Publisher: IBM Redbooks

Published: 2015-04-14

Total Pages: 472

ISBN-13: 0738439355

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IBM® InfoSphere® Guardium® provides the simplest, most robust solution for data security and data privacy by assuring the integrity of trusted information in your data center. InfoSphere Guardium helps you reduce support costs by automating the entire compliance auditing process across heterogeneous environments. InfoSphere Guardium offers a flexible and scalable solution to support varying customer architecture requirements. This IBM Redbooks® publication provides a guide for deploying the Guardium solutions. This book also provides a roadmap process for implementing an InfoSphere Guardium solution that is based on years of experience and best practices that were collected from various Guardium experts. We describe planning, installation, configuration, monitoring, and administrating an InfoSphere Guardium environment. We also describe use cases and how InfoSphere Guardium integrates with other IBM products. The guidance can help you successfully deploy and manage an IBM InfoSphere Guardium system. This book is intended for the system administrators and support staff who are responsible for deploying or supporting an InfoSphere Guardium environment.


Book Synopsis Deployment Guide for InfoSphere Guardium by : Whei-Jen Chen

Download or read book Deployment Guide for InfoSphere Guardium written by Whei-Jen Chen and published by IBM Redbooks. This book was released on 2015-04-14 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: IBM® InfoSphere® Guardium® provides the simplest, most robust solution for data security and data privacy by assuring the integrity of trusted information in your data center. InfoSphere Guardium helps you reduce support costs by automating the entire compliance auditing process across heterogeneous environments. InfoSphere Guardium offers a flexible and scalable solution to support varying customer architecture requirements. This IBM Redbooks® publication provides a guide for deploying the Guardium solutions. This book also provides a roadmap process for implementing an InfoSphere Guardium solution that is based on years of experience and best practices that were collected from various Guardium experts. We describe planning, installation, configuration, monitoring, and administrating an InfoSphere Guardium environment. We also describe use cases and how InfoSphere Guardium integrates with other IBM products. The guidance can help you successfully deploy and manage an IBM InfoSphere Guardium system. This book is intended for the system administrators and support staff who are responsible for deploying or supporting an InfoSphere Guardium environment.

Building Big Data and Analytics Solutions in the Cloud

Building Big Data and Analytics Solutions in the Cloud

Author: Wei-Dong Zhu

Publisher: IBM Redbooks

Published: 2014-12-08

Total Pages: 114

ISBN-13: 0738453994

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Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.


Book Synopsis Building Big Data and Analytics Solutions in the Cloud by : Wei-Dong Zhu

Download or read book Building Big Data and Analytics Solutions in the Cloud written by Wei-Dong Zhu and published by IBM Redbooks. This book was released on 2014-12-08 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.

INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS

INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS

Author: Shoban Babu Sriramoju

Publisher: Horizon Books ( A Division of Ignited Minds Edutech P Ltd)

Published: 2017-12-01

Total Pages: 197

ISBN-13: 9386369575

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Big data is certainly one of the biggest buzz phrases in IT today. Combined with virtualization and cloud computing, big data is a technological capability that will force data centers to significantly transform and evolve within the next five years. Similar to virtualization, big data infrastructure is unique and can create an architectural upheaval in the way systems, storage, and software infrastructure are connected and managed. Unlike previous business analytics solutions, the real-time capability of new big data solutions can provide mission critical business intelligence that can change the shape and speed of enterprise decision making forever. Hence, the way in which IT infrastructure is connected and distributed warrants a fresh and critical analysis.


Book Synopsis INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS by : Shoban Babu Sriramoju

Download or read book INTRODUCTION TO BIG DATA: INFRASTRUCTURE AND NETWORKING CONSIDERATIONS written by Shoban Babu Sriramoju and published by Horizon Books ( A Division of Ignited Minds Edutech P Ltd). This book was released on 2017-12-01 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is certainly one of the biggest buzz phrases in IT today. Combined with virtualization and cloud computing, big data is a technological capability that will force data centers to significantly transform and evolve within the next five years. Similar to virtualization, big data infrastructure is unique and can create an architectural upheaval in the way systems, storage, and software infrastructure are connected and managed. Unlike previous business analytics solutions, the real-time capability of new big data solutions can provide mission critical business intelligence that can change the shape and speed of enterprise decision making forever. Hence, the way in which IT infrastructure is connected and distributed warrants a fresh and critical analysis.

Database Systems

Database Systems

Author: Elvis C. Foster

Publisher: CRC Press

Published: 2022-09-26

Total Pages: 504

ISBN-13: 1000562123

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This book provides a concise but comprehensive guide to the disciplines of database design, construction, implementation, and management. Based on the authors’ professional experience in the software engineering and IT industries before making a career switch to academia, the text stresses sound database design as a necessary precursor to successful development and administration of database systems. The discipline of database systems design and management is discussed within the context of the bigger picture of software engineering. Students are led to understand from the outset of the text that a database is a critical component of a software infrastructure, and that proper database design and management is integral to the success of a software system. Additionally, students are led to appreciate the huge value of a properly designed database to the success of a business enterprise. The text was written for three target audiences. It is suited for undergraduate students of computer science and related disciplines who are pursuing a course in database systems, graduate students who are pursuing an introductory course to database, and practicing software engineers and information technology (IT) professionals who need a quick reference on database design. Database Systems: A Pragmatic Approach, 3rd Edition discusses concepts, principles, design, implementation, and management issues related to database systems. Each chapter is organized into brief, reader-friendly, conversational sections with itemization of salient points to be remembered. This pragmatic approach includes adequate treatment of database theory and practice based on strategies that have been tested, proven, and refined over several years. Features of the third edition include: Short paragraphs that express the salient aspects of each subject Bullet points itemizing important points for easy memorization Fully revised and updated diagrams and figures to illustrate concepts to enhance the student’s understanding Real-world examples Original methodologies applicable to database design Step-by-step, student-friendly guidelines for solving generic database systems problems Opening chapter overviews and concluding chapter summaries Discussion of DBMS alternatives such as the Entity–Attributes–Value model, NoSQL databases, database-supporting frameworks, and other burgeoning database technologies A chapter with sample assignment questions and case studies This textbook may be used as a one-semester or two-semester course in database systems, augmented by a DBMS (preferably Oracle). After its usage, students will come away with a firm grasp of the design, development, implementation, and management of a database system.


Book Synopsis Database Systems by : Elvis C. Foster

Download or read book Database Systems written by Elvis C. Foster and published by CRC Press. This book was released on 2022-09-26 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise but comprehensive guide to the disciplines of database design, construction, implementation, and management. Based on the authors’ professional experience in the software engineering and IT industries before making a career switch to academia, the text stresses sound database design as a necessary precursor to successful development and administration of database systems. The discipline of database systems design and management is discussed within the context of the bigger picture of software engineering. Students are led to understand from the outset of the text that a database is a critical component of a software infrastructure, and that proper database design and management is integral to the success of a software system. Additionally, students are led to appreciate the huge value of a properly designed database to the success of a business enterprise. The text was written for three target audiences. It is suited for undergraduate students of computer science and related disciplines who are pursuing a course in database systems, graduate students who are pursuing an introductory course to database, and practicing software engineers and information technology (IT) professionals who need a quick reference on database design. Database Systems: A Pragmatic Approach, 3rd Edition discusses concepts, principles, design, implementation, and management issues related to database systems. Each chapter is organized into brief, reader-friendly, conversational sections with itemization of salient points to be remembered. This pragmatic approach includes adequate treatment of database theory and practice based on strategies that have been tested, proven, and refined over several years. Features of the third edition include: Short paragraphs that express the salient aspects of each subject Bullet points itemizing important points for easy memorization Fully revised and updated diagrams and figures to illustrate concepts to enhance the student’s understanding Real-world examples Original methodologies applicable to database design Step-by-step, student-friendly guidelines for solving generic database systems problems Opening chapter overviews and concluding chapter summaries Discussion of DBMS alternatives such as the Entity–Attributes–Value model, NoSQL databases, database-supporting frameworks, and other burgeoning database technologies A chapter with sample assignment questions and case studies This textbook may be used as a one-semester or two-semester course in database systems, augmented by a DBMS (preferably Oracle). After its usage, students will come away with a firm grasp of the design, development, implementation, and management of a database system.