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| financial services cloud data model: Banking on Cloud Data Platforms: A Guide Dillip Kumar, Sarah Mohapatra, 2023-10-12 This book explores the evolution of data platforms over the last five decades, spanning from data warehousing to big data and cloud technologies. It discusses architecture, guiding principles, technology, and various use cases in the banking industry. The role of fintech and meeting digital payment demands with modern platforms is addressed. Techniques for handling PII/SPDI data in the cloud, ingestion frameworks, real-time and streaming data, and data availability are discussed practically. Additionally, it covers the increasing roles of CDOs, governance, data security, and DPDP. These chapters serve as valuable references for banks and financial institutions, drawing from real-world data sources and global events. |
| financial services cloud data model: Cloud Computing in Financial Services B. Nicoletti, 2013-02-27 Financial institutions must become more innovative in the conduct of their business. Cloud computing helps to achieve several objectives: innovative services, re-engineered processes, business agility and value optimization. Research, consultancy practice and case studies in this book consider the opportunities and risks with vendor relationships. |
| financial services cloud data model: ICPDI 2023 Md Rabiul Islam, Rongjuan Chen, Jing Ma, 2023-11-21 The 2nd International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2023) was successfully held on 1-3 September 2023 in Chongqing, China. This conference aimed to bring together researchers, scholars, and practitioners from various fields to exchange ideas and discuss advancements in the areas of public management, digital economy, and internet technology. The conference featured a diverse range of research topics, including but not limited to Public Management, Digital Economy and Internet Technology. The conference fostered a rich and stimulating intellectual environment. The program included keynote speeches by renowned experts in the field, parallel sessions for paper presentations, and panel discussions addressing emerging trends and challenges. The conference proceedings showcased a wide array of research papers, providing valuable insights into the latest theoretical and practical developments in the field of public management, digital economy, and internet technology. Participants had the opportunity to engage in constructive discussions, offer feedback, and establish potential collaborations for future research endeavors. We extend our gratitude to all participants, presenters, organizers, and sponsors for their contributions in making this conference a resounding success. We look forward to the 3rd edition of this conference, where we can further explore the dynamic intersections of public management, digital economy, and internet technology. |
| financial services cloud data model: Salesforce Data Architect Certification Guide Aaron Allport, 2022-11-18 Learn data architecture essentials and prepare for the Salesforce Certified Data Architect exam with the help of tips and mock test questions Key FeaturesLeverage data modelling, Salesforce database design, and techniques for effective data designLearn master data management, Salesforce data management, and how to include considerationsGet to grips with large data volumes, performance tuning, and poor performance mitigation techniquesBook Description The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence. The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You'll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You'll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification. By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts. What you will learnUnderstand the topics relevant to passing the Salesforce Data Architect examExplore specialist areas, such as large data volumesTest your knowledge with the help of exam-like questionsPick up useful tips and tricks that can be referred to time and againUnderstand the reasons underlying the way Salesforce data management worksDiscover the techniques that are available for loading massive amounts of dataWho this book is for This book is for both aspiring Salesforce data architects and those already familiar with Salesforce data architecture who want to pass the exam and have a reference guide to revisit the material as part of their day-to-day job. Working knowledge of the Salesforce platform is assumed, alongside a clear understanding of Salesforce architectural concepts. |
| financial services cloud data model: Financial Services and General Government Appropriations for Fiscal Year 2015 United States. Congress. Senate. Committee on Appropriations. Subcommittee on Financial Services and General Government, 2015 |
| financial services cloud data model: Cloud Data Centers and Cost Modeling Caesar Wu, Rajkumar Buyya, 2015-02-27 Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge. The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundation of cloud concepts and definitions, the book addresses data center creation, infrastructure development, cost modeling, and simulations in decision-making, each part building on the previous. In this way the authors bridge technology, management, and infrastructure as a service, in one complete guide to data centers that facilitates educated decision making. - Explains how to balance cloud computing functionality with data center efficiency - Covers key requirements for power management, cooling, server planning, virtualization, and storage management - Describes advanced methods for modeling cloud computing cost including Real Option Theory and Monte Carlo Simulations - Blends theoretical and practical discussions with insights for developers, consultants, and analysts considering data center development |
| financial services cloud data model: Handbook of Research on Big Data Storage and Visualization Techniques Segall, Richard S., Cook, Jeffrey S., 2018-01-05 The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject. |
| financial services cloud data model: The Semantic Web: ESWC 2020 Satellite Events Andreas Harth, Valentina Presutti, Raphaël Troncy, Maribel Acosta, Axel Polleres, Javier D. Fernández, Josiane Xavier Parreira, Olaf Hartig, Katja Hose, Michael Cochez, 2020-11-10 Chapter “ABECTO: An ABox Evaluation and Comparison Tool for Ontologies” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| financial services cloud data model: The Data Model Resource Industry Download Len Silverston, 2001-04-01 |
| financial services cloud data model: Cloud Scale Analytics with Azure Data Services Patrik Borosch, 2021-07-23 A practical guide to implementing a scalable and fast state-of-the-art analytical data estate Key FeaturesStore and analyze data with enterprise-grade security and auditingPerform batch, streaming, and interactive analytics to optimize your big data solutions with easeDevelop and run parallel data processing programs using real-world enterprise scenariosBook Description Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs. What you will learnImplement data governance with Azure servicesUse integrated monitoring in the Azure Portal and integrate Azure Data Lake Storage into the Azure MonitorExplore the serverless feature for ad-hoc data discovery, logical data warehousing, and data wranglingImplement networking with Synapse Analytics and Spark poolsCreate and run Spark jobs with Databricks clustersImplement streaming using Azure Functions, a serverless runtime environment on AzureExplore the predefined ML services in Azure and use them in your appWho this book is for This book is for data architects, ETL developers, or anyone who wants to get well-versed with Azure data services to implement an analytical data estate for their enterprise. The book will also appeal to data scientists and data analysts who want to explore all the capabilities of Azure data services, which can be used to store, process, and analyze any kind of data. A beginner-level understanding of data analysis and streaming will be required. |
| financial services cloud data model: Financial Accounting in SAP S/4HANA Finance Simplified Narayanan Veeriah, 2024-09-11 DESCRIPTION SAP S/4HANA Finance is a revolutionary financial accounting solution that leverages the latest in-memory database technology to deliver unparalleled performance and efficiency. Financial Accounting in SAP S/4HANA Finance Simplified – Questions & Answers is the most updated book in SAP Financial Accounting, in an easy-to-learn format. This second edition builds on the first by going in-depth into SAP HANA, Fiori, and SAP S/4HANA Finance. It offers expanded coverage with clearer explanations, practical examples, and step-by-step guidance. You will learn about global settings, the document principle, and managing accounts receivable, payable, bank accounting, and asset accounting processes, making it easier to master these key concepts. The content is presented in a Q&A format with about 650 questions, enhanced with live system screenshots, examples, and illustrations for better understanding. It also includes menu paths and transaction codes for system customization and task execution, making it an effective learning resource. By the end of this book, you will have a solid understanding of financial accounting in SAP S/4HANA Finance. You will be equipped with the knowledge and skills to streamline your financial processes, improve efficiency, and make informed business decisions. KEY FEATURES ● Comprehensive coverage of SAP FI modules and their integration with other SAP components. ● Know SAP G/L, FI-A/P, FI-A/R, FI-AA, and Bank Accounting in detail. ● Practical examples and step-by-step instructions for hands-on learning. WHAT YOU WILL LEARN ● This new edition expands on SAP S/4HANA Finance by covering its integration with other SAP modules and cloud-based solutions. ● Configure global settings like ledgers, fiscal years, document types, and tax settings to align with your organization's specific requirements. ● Master accounts receivable and payable management, bank reconciliation, and asset accounting processes. ● Leverage advanced features like in-memory computing, real-time analytics, and automation. ● Create reports, comply with regulations, and manage financial risks. WHO THIS BOOK IS FOR This book is for all professionals, consultants, end-users, and business leaders involved with SAP, to gain expertise in financial accounting for better organizational performance with improved business efficiency, financial compliance, and effective reporting. TABLE OF CONTENTS 1. SAP Basics 2. ABAP, Basis and NetWeaver 3. SAP HANA 4. SAP S/4HANA 5. SAP Fiori 6. Project Implementation 7. SAP S/4HANA Finance 8. FI: General 9. FI: Enterprise Structure 10. FI Global Settings: Ledgers 11. FI Global Settings: Document 12. FI Global Settings: Tax on Sales/Purchase 13. FI Global Settings: Withholding Tax 14. FI Global Settings: Inflation Accounting 15. FI: General Ledger 16. FI: Accounts Receivable & Accounts Payable – I 17. FI: Accounts Receivable & Accounts Payable – II 18. FI: Bank Accounting 19. FI: Asset Accounting |
| financial services cloud data model: A Quick Start Guide to Cloud Computing Mark I Williams, 2010-10-03 Cloud computing has caused a marketing fog, confusing business executives seeking to understand the technology's potential applications and business benefits. A Quick-Start Guide to Cloud Computing cuts through the industry hype and provides non-technical explanations about what it is and how it can improve your business. With case studies from large and small business, it shows how enabling a remote workforce and sharing resources can reduce your organisation's carbon footprint. It describes: the benefits of cloud computing; how to choose the right supplier and technologies for your particular business; key security issues and the perils and pitfalls to avoid. This Quick Start Guide puts business needs before technology, enabling you to make confident decisions about IT strategy, make the right choices for your business and reject 'solutions' that fix problems you don't have. |
| financial services cloud data model: Mastering Cloud Data Cybellium Ltd, 2023-09-06 Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books. |
| financial services cloud data model: Financial Intermediation Versus Disintermediation: Opportunities and Challenges in the FinTech era Meryem Duygun, Shatha Qamhieh Hashem, Alessandra Tanda, 2021-02-11 |
| financial services cloud data model: Fintech Business Models Matthias Fischer, 2021-02-08 This book on fintechs shows an international comparison on a global level. It is the first book where 10 years of financing rounds for fintechs have been analyzed for 10 different fintech segments. It is the first book to show the Canvas business model for fintechs. Professionals and students get a global understanding of fintechs. The case examples in the book cover Europe, the U.S. and China. Teaser of the OPEN vhb course Principles of Fintech Business Models: https://www.youtube.com/watch?v=UN38YmzzvXQ |
| financial services cloud data model: Modeling and Selection of Software Service Variants Wittern, John Erik, 2015-05-29 Providers and consumers have to deal with variants of software services, which are alternative instances of a services design, implementation, deployment, or operation. This work develops the service feature modeling language to represent software service variants and a suite of methods to select variants for development or delivery. An evaluation describes the systems implemented to make use of service feature modeling and its application to two real-world use cases. |
| financial services cloud data model: MACHINE LEARNING APPLICATIONS IN FINANCE Dr. Hemant N. Patel, Dr. Mitesh J. Patel, Mr. Sunil P. Patel, Shakti Bharatbhai Dodiya, 2023-07-17 In order to tackle the computer challenge, we will need an algorithm. A collection of instructions that must be carried out in order to transform an input into an outcome is referred to as an algorithm. One illustration of this would be the development of an algorithm to produce a classification. Your ordered list is the result, and the input is a series of numerical values to be arranged. You might be interested in discovering the most effective algorithm, which either needs fewer instructions or less memory or both, and you might discover that there are numerous algorithms for the same work. On the other hand, we do not have an algorithm for certain tasks, such as determining what constitutes spam and what constitutes legitimate e-mail. We are aware of the nature of the entry, which is a simple typeface file contained within an email document. We are aware of the expected outcome, which is a yes/no answer signifying whether or not the communication should be considered spam. We are not familiar with the process of converting information to output. The definition of what constitutes spam shifts over time and differs from one individual to the next. Using statistics, we are able to compensate for our dearth of understanding. We are able to quickly collect thousands of example messages, some of which we are aware are spam and would like to learn more about how they are constructed. Therefore, we would like the computer (machine) to automatically determine the procedure that should be used for this work. There is no need for you to learn how to arrange numbers because we already have algorithms for that; however, there are many applications with example data that do not require an algorithm. Because of developments in computer technology, we are now able to store and analyze large quantities of data, as well as retrieve this data from geographically dispersed locations through the use of a computer network. Most data acquisition instruments today are computerized and capture accurate data. |
| financial services cloud data model: The Data Warehouse Toolkit Ralph Kimball, Margy Ross, 2011-08-08 This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts. |
| financial services cloud data model: Cloud Computing Basics S. Srinivasan, 2014-05-14 Cloud Computing Basics covers the main aspects of this fast moving technology so that both practitioners and students will be able to understand cloud computing. The author highlights the key aspects of this technology that a potential user might want to investigate before deciding to adopt this service. This book explains how cloud services can be used to augment existing services such as storage, backup and recovery. Addressing the details on how cloud security works and what the users must be prepared for when they move their data to the cloud. Also this book discusses how businesses could prepare for compliance with the laws as well as industry standards such as the Payment Card Industry. |
| financial services cloud data model: Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing Management Association, Information Resources, 2021-01-25 Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. The Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing is a vital reference source that provides valuable insight into current and emergent research occurring within the field of distributed computing. It also presents architectures and service frameworks to achieve highly integrated distributed systems and solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting a range of topics such as data sharing, wireless sensor networks, and scalability, this multi-volume book is ideally designed for system administrators, integrators, designers, developers, researchers, academicians, and students. |
| financial services cloud data model: The New Cycle and New Finance in China Shusong Ba, 2022-01-23 This book is a selection of research by a Chinese economist who explains China's financial system, as well as predicting the future. The selected 45 articles focus on six topics covering diverse levels: China's macroeconomic and financial system, financial institutions, payment and clearing industry, inclusive finance, urbanization and financial supervision. The book builds a brand overview on China's financial development trend in the past recent years and long term.-- |
| financial services cloud data model: Handbook of Innovation & Appropriate Technologies for International Development Régnier, Philippe, Frey, Daniel, Pierre, Samuel, Varghese, Koshy, Wild, Pascal, 2022-10-20 This timely Handbook provides a conceptual discussion and an empirical review of new disruptive forms of innovation producing appropriate technologies, which address both the needs of low-income populations worldwide, and provides alternative solutions for sustainable development. |
| financial services cloud data model: Digitalization of Financial Services in the Age of Cloud Jamil Mina, Armin Warda, Rafael Marins, Russ Miles, 2023-05-09 If you're planning, building, or implementing a cloud strategy that supports digitalization for your financial services business, this invaluable guide clearly sets out the crucial factors and questions to consider first. With it, you'll learn how to avoid the costly and time-consuming pitfalls and disappointments of cloud adoption and take full advantage of the cloud operational model. You'll discover cloud tactics that unlock the benefits of digitalization and how to create a cloud strategy that has the flexibility to streamline operations, integrate channels, and encourage innovation in your firm. Packed with invaluable advice and real-world case studies, this book will show you how to: Select the right operational models for your needs Build resilience into your company's technologies Assess the trade-offs of third-party digital native services versus developing them in-house Ensure operability across cloud services providers Balance innovation and accountability Deal with digitalization issues of particular importance in finance, such as governance, security, and regulatory compliance And more |
| financial services cloud data model: The WEALTHTECH Book Susanne Chishti, Thomas Puschmann, 2018-04-19 Get a handle on disruption, innovation and opportunity in investment technology The digital evolution is enabling the creation of sophisticated software solutions that make money management more accessible, affordable and eponymous. Full automation is attractive to investors at an early stage of wealth accumulation, but hybrid models are of interest to investors who control larger amounts of wealth, particularly those who have enough wealth to be able to efficiently diversify their holdings. Investors can now outperform their benchmarks more easily using the latest tech tools. The WEALTHTECH Book is the only comprehensive guide of its kind to the disruption, innovation and opportunity in technology in the investment management sector. It is an invaluable source of information for entrepreneurs, innovators, investors, insurers, analysts and consultants working in or interested in investing in this space. • Explains how the wealth management sector is being affected by competition from low-cost robo-advisors • Explores technology and start-up company disruption and how to delight customers while managing their assets • Explains how to achieve better returns using the latest fintech innovation • Includes inspirational success stories and new business models • Details overall market dynamics The WealthTech Book is essential reading for investment and fund managers, asset allocators, family offices, hedge, venture capital and private equity funds and entrepreneurs and start-ups. |
| financial services cloud data model: Cyber Security Intelligence and Analytics Zheng Xu, Reza M. Parizi, Octavio Loyola-González, Xiaolu Zhang, 2021-03-10 This book presents the outcomes of the 2021 International Conference on Cyber Security Intelligence and Analytics (CSIA 2021), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly focusing on threat intelligence, analytics, and countering cybercrime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings and novel techniques, methods and applications on all aspects of cyber security intelligence and analytics. Due to COVID-19, Authors, Keynote Speakers and PC committees will attend the conference online. |
| financial services cloud data model: Professional SharePoint 2010 Cloud-Based Solutions Steve Fox, Girish Raja, Paul Stubbs, Donovan Follette, 2011-11-14 An authoritative guide to extending SharePoint's power with cloud-based services If you want to be part of the next major shift in the IT industry, you'll want this book. Melding two of the hottest trends in the industry—the widespread popularity of the SharePoint collaboration platform and the rapid rise of cloud computing—this practical guide shows developers how to extend their SharePoint solutions with the cloud's almost limitless capabilities. See how to get started, discover smart ways to leverage cloud data and services through Azure, start incorporating Twitter or LinkedIn into your solutions, find the best ways to secure everything, and much more. Shows developers how to use Microsoft SharePoint 2010 to create scalable, cloud-based solutions Melds the hottest new trend in the industry—developing, hosting, managing, or storing code in the cloud—with what SharePoint developers need to know to weave these technologies into their solutions Provides developer patterns, real-world examples, and invaluable walkthroughs Topics include SQL Azure for data management and BI, building an Azure-based corporate tax service, connecting Linked In and SharePoint profile data, creating a filterable Twitter dashboard, leveraging Bing Maps Geo services, maintaining security, and more SharePoint developers, discover exciting new ways to extend SharePoint's functionality with this practical and content-rich guide. |
| financial services cloud data model: The Cloud Computing Journey Divit Gupta, 2024-01-05 Elevate your expertise and gain holistic insights into cloud technology with a focus on smoothly transitioning from on-premises to the cloud Key Features Analyze cloud architecture in depth, including different layers, components, and design principles Explore various types of cloud services from AWS, Microsoft Azure, Google Cloud, Oracle Cloud Infrastructure, and more Implement best practices and understand the use of various cloud deployment tools Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the need for digital transformation and remote work surges, so does the demand for cloud computing. However, the complexity of cloud architecture and the abundance of vendors and tools can be overwhelming for businesses. This book addresses the need for skilled professionals capable of designing, building, and managing scalable and resilient cloud systems to navigate the complex landscape of cloud computing through practical tips and strategies. This comprehensive cloud computing guide offers the expertise and best practices for evaluating different cloud vendors and tools. The first part will help you gain a thorough understanding of cloud computing basics before delving deeper into cloud architecture, its design, and implementation. Armed with this expert insight, you'll be able to avoid costly mistakes, ensure that your cloud systems are secure and compliant, and build cloud systems that can adapt and grow with the business. By the end of this book, you’ll be proficient in leveraging different vendors and tools to build robust and secure cloud systems to achieve specific goals and meet business requirements.What you will learn Get to grips with the core concepts of cloud architecture and cost optimization Understand the different cloud deployment and service models Explore various cloud-related tools and technologies Discover cloud migration strategies and best practices Find out who the major cloud vendors are and what they offer Analyze the impact and future of cloud technology Who this book is for The book is for anyone interested in understanding cloud technology, including business leaders and IT professionals seeking insights into the benefits, challenges, and best practices of cloud computing. Those who are just starting to explore cloud technology, as well as those who are already using cloud technology and want to deepen their understanding to optimize usage, will find this resource especially useful. |
| financial services cloud data model: Inverting the Paradox of Excellence Vivek Kale, 2014-07-14 Drawing lessons from one of the best models of success, the evolutionary model, this book explains why an organization must actively monitor the market environment and competitors to ascertain excellence and reconfigure and reframe continuously. It introduces the patterns and anti-patterns of excellence and includes detailed case studies based on different variations, including structure variations, shared values variations, and staff variations. The book includes case history segments from Toyota, Acer, eBay, Cisco, Blackberry, Samsung, Volvo, Charles Schwab, McDonalds, Starbucks, Google, Disney, and NUMMI; as well as detailed case histories of GE, IBM, and UPS. |
| financial services cloud data model: Strategic Blueprint for Enterprise Analytics Liang Wang, |
| financial services cloud data model: The Essentials of Machine Learning in Finance and Accounting Mohammad Zoynul Abedin, M. Kabir Hassan, Petr Hajek, Mohammed Mohi Uddin, 2021-06-20 This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management. |
| financial services cloud data model: The Official (ISC)2 CCSP CBK Reference Aaron Kraus, 2022-09-09 The only official body of knowledge for CCSP—the most popular cloud security credential—fully revised and updated. Certified Cloud Security Professional (CCSP) certification validates the advanced technical skills needed to design, manage, and secure data, applications, and infrastructure in the cloud. This highly sought-after global credential has been updated with revised objectives. The new third edition of The Official (ISC)2 Guide to the CCSP CBK is the authoritative, vendor-neutral common body of knowledge for cloud security professionals. This comprehensive resource provides cloud security professionals with an indispensable working reference to each of the six CCSP domains: Cloud Concepts, Architecture and Design; Cloud Data Security; Cloud Platform and Infrastructure Security; Cloud Application Security; Cloud Security Operations; and Legal, Risk and Compliance. Detailed, in-depth chapters contain the accurate information required to prepare for and achieve CCSP certification. Every essential area of cloud security is covered, including implementation, architecture, operations, controls, and immediate and long-term responses. Developed by (ISC)2, the world leader in professional cybersecurity certification and training, this indispensable guide: Covers the six CCSP domains and over 150 detailed objectives Provides guidance on real-world best practices and techniques Includes illustrated examples, tables, and diagrams The Official (ISC)2 Guide to the CCSP CBK is a vital ongoing resource for IT and information security leaders responsible for applying best practices to cloud security architecture, design, operations and service orchestration. |
| financial services cloud data model: Developing and Securing the Cloud Bhavani Thuraisingham, 2013-10-28 Although the use of cloud computing platforms and applications has expanded rapidly, most books on the subject focus on high-level concepts. There has long been a need for a book that provides detailed guidance on how to develop secure clouds.Filling this void, Developing and Securing the Cloud provides a comprehensive overview of cloud computing t |
| financial services cloud data model: Business Intelligence and the Cloud Michael S. Gendron, 2014-05-12 How to measure cloud computing options and benefits to impact business intelligence infrastructure This book is a guide for managers and others involved in using cloud computing to create business value. It starts with a discussion of the media hype around cloud computing and attempt to pull together what industry experts are saying in order to create a unified definition. Once this foundation is created—assisting the reader's understanding of what cloud computing is—the discussion moves to getting business benefits from cloud computing. Lastly, the discussion focuses on examples of cloud computing, public clouds, private clouds, and virtualization. The book emphasizes how these technologies can be used to create business value and how they can be integrated into an organizations business intelligence system. It helps the user make a business case for cloud computing applications—applications that are used to gather/create data, which in turn are used to generate business intelligence. |
| financial services cloud data model: MACHINE LEARNING APPROACHES FOR BETTER BUSINESS MANAGEMENT IN COMPETITIVE ENVIRONMENT Khaja Mannanuddin, Dr. Purnendu Bikash Acharjee, AKASH BAG, Dr.Sushma Jaiswal, 2023-04-06 |
| financial services cloud data model: Amazon Redshift: The Definitive Guide Rajesh Francis, Rajiv Gupta, Milind Oke, 2023-10-03 Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value |
| financial services cloud data model: Model Optimization Methods for Efficient and Edge AI Pethuru Raj Chelliah, Amir Masoud Rahmani, Robert Colby, Gayathri Nagasubramanian, Sunku Ranganath, 2025-01-09 Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data Overcoming cyberattacks on mission-critical software systems by leveraging federated learning |
| financial services cloud data model: Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations for 2015 United States. Congress. House. Committee on Appropriations. Subcommittee on the Departments of Labor, Health and Human Services, Education, and Related Agencies, 2014 |
| financial services cloud data model: Data Science and Risk Analytics in Finance and Insurance Tze Leung Lai, Haipeng Xing, 2024-10-02 This book presents statistics and data science methods for risk analytics in quantitative finance and insurance. Part I covers the background, financial models, and data analytical methods for market risk, credit risk, and operational risk in financial instruments, as well as models of risk premium and insolvency in insurance contracts. Part II provides an overview of machine learning (including supervised, unsupervised, and reinforcement learning), Monte Carlo simulation, and sequential analysis techniques for risk analytics. In Part III, the book offers a non-technical introduction to four key areas in financial technology: artificial intelligence, blockchain, cloud computing, and big data analytics. Key Features: Provides a comprehensive and in-depth overview of data science methods for financial and insurance risks. Unravels bandits, Markov decision processes, reinforcement learning, and their interconnections. Promotes sequential surveillance and predictive analytics for abrupt changes in risk factors. Introduces the ABCDs of FinTech: Artificial intelligence, blockchain, cloud computing, and big data analytics. Includes supplements and exercises to facilitate deeper comprehension. |
| financial services cloud data model: ICICKM 2018 15th International Conference on Intellectual Capital Knowledge Management & Organisational Learning Prof. Shaun Pather, 2018-11-29 |
| financial services cloud data model: Semantic Web Technologies and Applications in Artificial Intelligence of Things Ortiz-Rodriguez, Fernando, Leyva-Mederos, Amed, Tiwari, Sanju, Hernandez-Quintana, Ania R., Martinez-Rodriguez, Jose L., 2024-05-16 The confluence of Artificial Intelligence of Things (AIoT) and Semantic Web technologies is nothing short of revolutionary. The profound impact of this synergy extends far beyond the realms of industry, research, and society; it shapes the very fabric of our future. Semantic Web Technologies and Applications in Artificial Intelligence of Things is a meticulously crafted reference that not only acknowledges this significance but also serves as a guide for those navigating the complexities of Industry 4.0 and AIoT. This curated compendium of cutting-edge technologies acts as a veritable knowledge base for future developments. As academics, scholars, and industry professionals, the ideal audience of this book, will find meticulously curated content that caters to their diverse interests and expertise, covering topics ranging from smart agriculture, manufacturing, industry, health sciences, and government. Seasoned academics, students, and visionary industry leaders, will find this book to be an indispensable guide that paves the way for innovation and progress. |
Data Model Overview - Salesforce
Learn about the objects and relationships within the Financial Services Cloud data model that represent a person along with their relationships and financ...
Learn About the Financial Services Cloud Data Model - Trailhead
Explore the structure of Financial Services Cloud data model, learn about key database concepts like objects, fields, and records.
Data Cloud for Financial Services | Salesforce US
Connect your data to Financial Services Cloud using data model objects for core banking data and insurance policy and claims data. Get started quickly with prebuilt mappings and streams …
Financial Services Cloud | Data Model Gallery - Salesforce …
Data Loader. Use a client application to manage data and Salesforce records. Tableau Embedding Playground. Experience the Tableau Embedded API with zero-setup
Data Models of Financial Services Cloud (FSC)
May 14, 2024 · By combining the FSC Standard Objects and the FSC Packaged Objects, Salesforce Financial Services Cloud offers a comprehensive and flexible data model that …
Insurance and Financial Services Data Model - Salesforce
The Industries Insurance and Financial Services data model is a comprehensive data model covering everything needed to address the complexities and challenges faced by cloud based …
Optimize Financial Services Data with Custom Modeling - Trailhead
Discover how to model data effectively for Financial Services. Learn to configure objects, fields, and relationships for optimal structure.
overview of FinancialServicesCommonDataModel - Common Data Model ...
Apr 10, 2023 · FinancialServicesCommonDataModel is a folder that contains standard entities related to the Common Data Model.
Introduction to Salesforce Financial Services Cloud - Apex Hours
Salesforce Financial Service Cloud (FSC) is industry specific offering from Salesforce with out of the box workflows and data model specific to Financial Services Industry. FSC caters to three …
Salesforce Financial Services Cloud Implementation Guide
Introduction or What Is a Salesforce Financial Service Cloud? Financial Services Cloud Salesforce is a versatile CRM platform, specially tailored for finance sector needs.
Data Model Overview - Salesforce
Learn about the objects and relationships within the Financial Services Cloud data model that represent a person along with their relationships and financ...
Learn About the Financial Services Cloud Data Model - Trailhead
Explore the structure of Financial Services Cloud data model, learn about key database concepts like objects, fields, and records.
Data Cloud for Financial Services | Salesforce US
Connect your data to Financial Services Cloud using data model objects for core banking data and insurance policy and claims data. Get started quickly with prebuilt mappings and streams …
Financial Services Cloud | Data Model Gallery - Salesforce …
Data Loader. Use a client application to manage data and Salesforce records. Tableau Embedding Playground. Experience the Tableau Embedded API with zero-setup
Data Models of Financial Services Cloud (FSC)
May 14, 2024 · By combining the FSC Standard Objects and the FSC Packaged Objects, Salesforce Financial Services Cloud offers a comprehensive and flexible data model that …
Insurance and Financial Services Data Model - Salesforce
The Industries Insurance and Financial Services data model is a comprehensive data model covering everything needed to address the complexities and challenges faced by cloud based …
Optimize Financial Services Data with Custom Modeling
Discover how to model data effectively for Financial Services. Learn to configure objects, fields, and relationships for optimal structure.
overview of FinancialServicesCommonDataModel - Common Data Model ...
Apr 10, 2023 · FinancialServicesCommonDataModel is a folder that contains standard entities related to the Common Data Model.
Introduction to Salesforce Financial Services Cloud - Apex Hours
Salesforce Financial Service Cloud (FSC) is industry specific offering from Salesforce with out of the box workflows and data model specific to Financial Services Industry. FSC caters to three …
Salesforce Financial Services Cloud Implementation Guide
Introduction or What Is a Salesforce Financial Service Cloud? Financial Services Cloud Salesforce is a versatile CRM platform, specially tailored for finance sector needs.
