Relational Nosql And Artificial Intelligence Integrated Database Architectures Foundations Cloud Platforms And Regulatory Compliant Systems
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Relational Nosql And Artificial Intelligence Integrated Database Architectures Foundations Cloud Platforms And Regulatory Compliant Systems
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Author : Sibaram Prasad Panda
language : en
Publisher: Deep Science Publishing
Release Date : 2025-06-22
Relational Nosql And Artificial Intelligence Integrated Database Architectures Foundations Cloud Platforms And Regulatory Compliant Systems written by Sibaram Prasad Panda and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-22 with Computers categories.
A modern entrance to the science of data. This textbook introduces the basic principles of the database system and guides students to advanced subjects such as distributed data processing, NOSQL model and intelligent query. Explanation, with practice on hands and real-world scenarios, prepares learners for both academic and professional activities in data management. Beyond the tradition, the book examines modern architecture including emerging patterns such as NoSQL database, Amazon RDS and Google Big Query such as cloud-country platforms and distributed and multi-model systems. We also check how artificial intelligence is changing database management through automation, discrepancy detection and future maintenance. Recognizing the increasing importance of trust and compliance, dedicated chapters focus on industries’ rules such as safety, access control, data governance and GDPR and HIPAA. The study of real-world cases from areas such as retail, healthcare and finance provides valuable insight into practical implementation, challenges and migration strategies. Whether you are a student, data engineer, software developer, or IT leader, this book serves as a complete guide to understand the developed world of database-where basic knowledge fulfils the state-of-the-art innovation.
Ethical Considerations And Bias Detection In Artificial Intelligence Machine Learning Applications
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Author : Jayesh Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-10
Ethical Considerations And Bias Detection In Artificial Intelligence Machine Learning Applications written by Jayesh Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-10 with Computers categories.
At a time when artificial intelligence (AI) and machine learning (ML) are used to make sensitive societal decisions such as the ones related to criminal justice, healthcare, finance, education, employment, algorithmic fairness and bias mitigation are among the most important but challenging issues at hand. The goal of this book is to provide a holistic view across various disciplines of the ethical base, detection methods, and technical measures for trustworthy AI systems. Starting from a solid foundation of statistical bias, transparency systems and fairness-aware ML models, this book methodically looks at state-of-the-art methodologies, where we highlight their shortcomings and introduce a unified model framework for detecting bias and transparent algorithms. Moving beyond technical diagnoses, it examines key sociotechnical and policy tools that are required to implement AI responsibly, providing guidance to researchers, engineers, policy makers, and organizational leaders. Literature review has been driven following the experimental case, the fairness trade-offs, intersectional bias, explainability and regulatory compliance are discussed in depth by the authors. This work underscores that fairness in automated decision-making systems depends not only on algorithmic accuracy, but also institutional will and stakeholder engagement. The chapters in this book function as both an academic primer and a resourceful handbook, transitioning readers through an ever-growing ethical AI terrain. Whether you are a data scientist building and deploying an algorithm that encourages ethical speech, or a regulator working to create and refine guidelines around such algorithms, this book provides you with both the tools and the understanding you need for ethical technology development and deployment.
Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle
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Author : Partha Mohapatra
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-27
Intelligent Assurance Artificial Intelligence Powered Software Testing In The Modern Development Lifecycle written by Partha Mohapatra and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-27 with Computers categories.
Traditional testing can’t match the speed and reliability demanded in modern software development and releases. This book explains the integration of Artificial Intelligence is transforming software testing—enabling smarter, faster, and more scalable quality assurance across the development lifecycle. This book demystifies the integration of AI, machine learning, and natural language processing into modern testing workflows. From automated test case generation and defect prediction to adaptive test maintenance and intelligent prioritization, it offers practical insights and real-world applications that empower QA teams to deliver higher-quality software with greater efficiency. Through a structured, hands-on approach, readers will explore AI-driven testing strategies, tools, and architectures that align with DevOps and agile practices. The book also delves into ethical considerations, challenges in AI adoption, and the future of autonomous testing agents. Whether you're a software tester, QA lead, DevOps engineer, or technology decision-maker, this book equips you with the knowledge to embrace AI-driven testing as a strategic advantage in delivering resilient, secure, and high-performance software.
Mastering Microsoft Fabric Unified Data Engineering Governance And Artificial Intelligence In The Cloud
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Author :
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-12
Mastering Microsoft Fabric Unified Data Engineering Governance And Artificial Intelligence In The Cloud written by and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-12 with Computers categories.
The development of cloud platforms has changed how organizations manage data, implement governance, and incorporate artificial intelligence into business processes. Microsoft Fabric combines data engineering, governance, real-time analytics, and AI into a single, scalable ecosystem. This book, Mastering Microsoft Fabric: Unified Data Engineering, Governance, and AI in the Cloud, is designed for professionals, researchers, and architects interested in Microsoft Fabric. It covers real-world use cases, architectural patterns, and practical implementations, this guide explores how to build modern, governed, and intelligent data systems that meet the demands of today’s dynamic digital environments. Drawing on extensive experience in databases, cybersecurity, and AI, I have written this book to address the divide between theoretical concept and practical implementation. This work focuses on role- and rule-based access control, multi-tenant data governance, AI integration, and secure data pipelines, all critical pillars in modern enterprise architecture. This book functions as both a technical guide and a strategic reference, outlining how Microsoft Fabric is influencing cloud-native data engineering and decision-making. It aims to inform readers about compliance focused architectures and servers as a resource for professionals working within cloud-first and AI-driven environments.
Foundations Of Databases
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Author : Serge Abiteboul
language : en
Publisher: Addison Wesley
Release Date : 1995
Foundations Of Databases written by Serge Abiteboul and has been published by Addison Wesley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
This product is a complete reference to both classical material and advanced topics that are otherwise scattered in sometimes hard-to-find papers. A major effort in writing the book was made to highlight the intuitions behind the theoretical development.
Software Architecture For Big Data And The Cloud
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Author : Ivan Mistrik
language : en
Publisher: Morgan Kaufmann
Release Date : 2017-06-12
Software Architecture For Big Data And The Cloud written by Ivan Mistrik and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-12 with Computers categories.
Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors.
Ibm Cloud Pak For Data
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Author : Hemanth Manda
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-11-24
Ibm Cloud Pak For Data written by Hemanth Manda and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Computers categories.
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
Dama Dmbok
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Author : Dama International
language : en
Publisher:
Release Date : 2017
Dama Dmbok written by Dama International and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Database management categories.
Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.
Ai And Big Data On Ibm Power Systems Servers
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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2019-04-10
Ai And Big Data On Ibm Power Systems Servers written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Computers categories.
As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.
Sql Nosql Databases
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Author : Andreas Meier
language : en
Publisher: Springer
Release Date : 2019-07-05
Sql Nosql Databases written by Andreas Meier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-05 with Computers categories.
This book offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types: SQL and NoSQL databases, and their respective management systems The nature and uses of Big Data A high-level view of the organization of data management Data Modeling and Consistency Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. Coverage of languages extends from an overview of operators, to SQL and and QBE (Query by Example), to integrity constraints and more. A full chapter probes the challenges of Ensuring Data Consistency, covering: Multi-User Operation Troubleshooting Consistency in Massive Distributed Data Comparison of the ACID and BASE consistency models, and more System Architecture also gets from its own chapter, which explores Processing of Homogeneous and Heterogeneous Data; Storage and Access Structures; Multi-dimensional Data Structures and Parallel Processing with MapReduce, among other topics. Post-Relational and NoSQL Databases The chapter on post-relational databases discusses the limits of SQL – and what lies beyond, including Multi-Dimensional Databases, Knowledge Bases and and Fuzzy Databases. A final chapter covers NoSQL Databases, along with Development of Non-Relational Technologies, Key-Value, Column-Family and Document Stores XML Databases and Graphic Databases, and more The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. SQL & NoSQL Databases conveys the strengths and weaknesses of relational and non-relational approaches, and shows how to undertake development for big data applications. The book benefits readers including students and practitioners working across the broad field of applied information technology. This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.