Self Service Data Analytics And Governance For Managers
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Self Service Data Analytics And Governance For Managers
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Author : Nathan E. Myers
language : en
Publisher: John Wiley & Sons
Release Date : 2021-06-02
Self Service Data Analytics And Governance For Managers written by Nathan E. Myers and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-02 with Business & Economics categories.
Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
Self Service Analytics Simplified
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Author : Arshad Khan
language : en
Publisher: Khan Consulting & Publishing LLC
Release Date : 2019-07-10
Self Service Analytics Simplified written by Arshad Khan and has been published by Khan Consulting & Publishing LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-10 with Computers categories.
Self-Service Analytics Simplified: How to Plan and Implement will introduce you to self-service analytics (SSA), which aims to make business users less dependent on IT for their reporting and analytics needs. This book, which teaches how to plan and implement an SSA project, will appeal to a broad range of users including senior executives, business and IT managers, project managers, data analysts, business analysts, developers, casual users, as well as IT professionals. The topics covered in Self-Service Analytics Simplified: How to Plan and Implement include an introduction to self-service analytics, relationship with BI, benefits for different types of users, readiness assessment, planning, data-related topics including metadata and data pipelining, architecture, tools, requirements, implementation, data governance, security, training, data and user onboarding, and barriers to adoption, as well as challenges, best practices, lessons, and tips.
The Self Service Data Roadmap
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Author : Sandeep Uttamchandani
language : en
Publisher: O'Reilly Media
Release Date : 2020-09-10
The Self Service Data Roadmap written by Sandeep Uttamchandani and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Computers categories.
Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization
Performance Dashboards
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Author : Wayne W. Eckerson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-10-27
Performance Dashboards written by Wayne W. Eckerson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-10-27 with Business & Economics categories.
Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution.
Self Service Bi A Roadmap For Empowered Analytics 2025
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Author : AUTHOR: 1- LAXMI VANAM, AUTHOR: 2 - PROF DR. PUNIT GOEL
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Self Service Bi A Roadmap For Empowered Analytics 2025 written by AUTHOR: 1- LAXMI VANAM, AUTHOR: 2 - PROF DR. PUNIT GOEL and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In an era where data is often lauded as the new oil, the true differentiator is not merely its abundance but our ability to transform raw information into actionable insights—quickly, confidently, and at scale. Self-Service BI: A Roadmap for Empowered Analytics charts a comprehensive course for organizations and individuals aiming to democratize data, break down technical barriers, and embed analytics into every decision-making process. Drawing on the latest innovations in real-time and streaming analytics, AI-driven augmentation, embedded machine learning, and collaborative workflows, this volume presents a cohesive narrative of how self-service BI has evolved and where it is headed. Every chapter in this book builds upon extensive research, case studies, and emerging best practices. We explore the foundational principles of empowering non-technical users—from well-governed data catalogs and intuitive visual query builders to guide tutorials that foster data literacy. We delve into the architectural underpinnings that make real-time dashboards possible, demonstrating how event-streaming platforms like Kafka and Flink underpin near-instant updates and proactive alerting. We then examine the seamless integration of AI and AutoML directly within BI interfaces—where forecasting, anomaly detection, and clustering happen alongside everyday chart creation. Further chapters illuminate augmented analytics and natural-language querying, which liberate users from complex syntax by allowing them to speak or type questions in plain English. We unpack the rise of social BI—commenting, tagging, and co-authoring features that foster alignment across distributed teams. Embedded and mobile-first BI sections reveal offline caching, responsive design, and API-driven integrations ensure that analytics travel with the user, whether in a CRM, ERP, or bespoke portal. Advanced visualization techniques—AR/VR overlays and generative AI–powered narratives—offer a glimpse into immersive, next-generation experiences. Amidst these innovations, we never lose sight of governance, security, and ethical imperatives. Robust role-based access controls, row- and column-level security, encryption, and automated policy enforcement ensure that empowerment never comes at the cost of compliance or data integrity. Finally, we look ahead to autonomous decisioning agents—reinforcement-learning systems that not only surface insights but execute decisions and refine strategies autonomously Whether you are a data analyst, an executive leading digital transformation, an IT architect, or a budding citizen data scientist, this book offers both the conceptual framework, and the practical guidance needed to navigate the dynamic landscape of self-service BI. May this roadmap empower you to foster a truly data-driven culture where every stakeholder can glean insights, make informed choices, and drive sustained innovation. Authors Laxmi Vanam Prof. Dr. Punit Goel
Enterprise Information Management In Practice
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Author : Saumya Chaki
language : en
Publisher: Apress
Release Date : 2015-12-19
Enterprise Information Management In Practice written by Saumya Chaki and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-19 with Computers categories.
Learn how to form and execute an enterprise information strategy: topics include data governance strategy, data architecture strategy, information security strategy, big data strategy, and cloud strategy. Manage information like a pro, to achieve much better financial results for the enterprise, more efficient processes, and multiple advantages over competitors. As you’ll discover in Enterprise Information Management in Practice, EIM deals with both structured data (e.g. sales data and customer data) as well as unstructured data (like customer satisfaction forms, emails, documents, social network sentiments, and so forth). With the deluge of information that enterprises face given their global operations and complex business models, as well as the advent of big data technology, it is not surprising that making sense of the large piles of data is of paramount importance. Enterprises must therefore put much greater emphasis on managing and monetizing both structured andunstructured data. As Saumya Chaki—an information management expert and consultant with IBM—explains in Enterprise Information Management in Practice, it is now more important than ever before to have an enterprise information strategy that covers the entire life cycle of information and its consumption while providing security controls. With Fortune 100 consultant Saumya Chaki as your guide, Enterprise Information Management in Practice covers each of these and the other pillars of EIM in depth, which provide readers with a comprehensive view of the building blocks for EIM. Enterprises today deal with complex business environments where information demands take place in real time, are complex, and often serve as the differentiator among competitors. The effective management of information is thus crucial in managing enterprises. EIM has evolved as a specialized discipline in the business intelligence and enterprise data warehousing space to address the complex needs of information processing and delivery—and to ensure the enterprise is making the most of its information assets.
Cyber Security Intelligence And Analytics
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Author : Zheng Xu
language : en
Publisher: Springer Nature
Release Date : 2020-03-19
Cyber Security Intelligence And Analytics written by Zheng Xu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-19 with Technology & Engineering categories.
This book presents the outcomes of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), which was dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly those focusing on threat intelligence, analytics, and preventing cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods, and applications concerning all aspects of cyber security intelligence and analytics. CSIA 2020, which was held in Haikou, China on February 28–29, 2020, built on the previous conference in Wuhu, China (2019), and marks the series’ second successful installment.
Big Data Infrastructure Technologies For Data Analytics
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Author : Yuri Demchenko
language : en
Publisher: Springer Nature
Release Date : 2024-10-25
Big Data Infrastructure Technologies For Data Analytics written by Yuri Demchenko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-25 with Computers categories.
This book provides a comprehensive overview and introduction to Big Data Infrastructure technologies, existing cloud-based platforms, and tools for Big Data processing and data analytics, combining both a conceptual approach in architecture design and a practical approach in technology selection and project implementation. Readers will learn the core functionality of major Big Data Infrastructure components and how they integrate to form a coherent solution with business benefits. Specific attention will be given to understanding and using the major Big Data platform Apache Hadoop ecosystem, its main functional components MapReduce, HBase, Hive, Pig, Spark and streaming analytics. The book includes topics related to enterprise and research data management and governance and explains modern approaches to cloud and Big Data security and compliance. The book covers two knowledge areas defined in the EDISON Data Science Framework (EDSF): Data Science Engineering and Data Management and Governance and can be used as a textbook for university courses or provide a basis for practitioners for further self-study and practical use of Big Data technologies and competent evaluation and implementation of practical projects in their organizations.
Information Technology For Management
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Author : Efraim Turban
language : en
Publisher: John Wiley & Sons
Release Date : 2021
Information Technology For Management written by Efraim Turban and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.
Information Technology for Management provides students with a comprehensive understanding of the latest technological developments in IT and the critical drivers of business performance, growth, and sustainability. Integrating feedback from IT managers and practitioners from top-level organizations worldwide, the International Adaptation of this well-regarded textbook features thoroughly revised content throughout to present students with a realistic, up-to-date view of IT management in the current business environment. This text covers the latest developments in the real world of IT management with the addition of new case studies that are contemporary and more relevant to the global scenario. It offers a flexible, student-friendly presentation of the material through a pedagogy that is designed to help students easily comprehend and retain information. There is new and expanded coverage of Artificial Intelligence, Robotics, Quantum Computing, Blockchain Technology, IP Intelligence, Big Data Analytics, IT Service Management, DevOps, etc. It helps readers learn how IT is leveraged to reshape enterprises, engage and retain customers, optimize systems and processes, manage business relationships and projects, and more.
Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16
Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.