Data Smart

Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Size: 66.71 MB
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Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Smart Data

Author: James A. George
Publisher: John Wiley & Sons
ISBN: 9780470583043
Size: 58.59 MB
Format: PDF, ePub
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The authors advocate attention to smart data strategy as an organizing element of enterprise performance optimization. They believe that “smart data” as a corporate priority could revolutionize government or commercial enterprise performance much like “six sigma” or “total quality” as organizing paradigms have done in the past. This revolution has not yet taken place because data historically resides in the province of the information resources organization. Solutions that render data smart are articulated in “technoid” terms versus the language of the board room. While books such as Adaptive Information by Pollock and Hodgson ably describe the current state of the art, their necessarily technical tone is not conducive to corporate or agency wide qualitative change.

Public Transport Planning With Smart Card Data

Author: Fumitaka Kurauchi
Publisher: CRC Press
ISBN: 1315353334
Size: 11.15 MB
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Collecting fares through "smart cards" is becoming standard in most advanced public transport networks of major cities around the world. Travellers value their convenience and operators the reduced money handling fees. Electronic tickets also make it easier to integrate fare systems, to create complex time and space differentiated fare systems, and to provide incentives to specific target groups. A less-utilised benefit is the data collected through smart cards. Records, even if anonymous, provide for a much better understanding of passengers’ travel behaviour as current literature shows. This information can also be used for better service planning. Public Transport Planning with Smart Card Data handles three major topics: how passenger behaviour can be estimated using smart card data, how smart card data can be combined with other trip databases, and how the public transport service level can be better evaluated if smart card data is available. The book discusses theory as well as applications from cities around the world and will be of interest to researchers and practitioners alike who are interested in the state-of-the-art as well as future perspectives that smart card data will bring.

Data Privacy For The Smart Grid

Author: Rebecca Herold
Publisher: CRC Press
ISBN: 1466573384
Size: 75.94 MB
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Many Smart Grid books include "privacy" in their title, but only touch on privacy, with most of the discussion focusing on cybersecurity. Filling this knowledge gap, Data Privacy for the Smart Grid provides a clear description of the Smart Grid ecosystem, presents practical guidance about its privacy risks, and details the actions required to prote

Smart Data Pricing

Author: Soumya Sen
Publisher: John Wiley & Sons
ISBN: 1118899334
Size: 47.68 MB
Format: PDF, Kindle
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A comprehensive text addressing the high demand for network, cloud, and content services through cutting-edge research on data pricing and business strategies Smart Data Pricing tackles the timely issue of surging demand for network, cloud, and content services and corresponding innovations in pricing these services to benefit consumers, operators, and content providers. The pricing of data traffic and other services is central to the core challenges of network monetization, growth sustainability, and bridging the digital divide. In this book, experts from both academia and industry discuss all aspects of smart data pricing research and development, including economic analyses, system development, user behavior evaluation, and business strategies. Smart Data Pricing: • Presents the analysis of leading researchers from industry and academia surrounding the pricing of network services and content. • Discusses current trends in mobile and wired data usage and their economic implications for content providers, network operators, end users, government regulators, and other players in the Internet ecosystem. • Includes new concepts and background technical knowledge that will help researchers and managers effectively monetize their networks and improve user quality-of-experience. • Provides cutting-edge research on business strategies and initiatives through a diverse collection of perspectives. • Combines academic and industry expertise from multiple disciplines and business organizations. The ideas and background of the technologies and economic principles discussed within these chapters are of real value to practitioners, researchers, and managers in identifying trends and deploying new pricing and network management technologies, and will help support managers in identifying new business directions and innovating solutions to challenging business problems.

Big Data Analytics Strategies For The Smart Grid

Author: Carol L. Stimmel
Publisher: CRC Press
ISBN: 1482218291
Size: 43.97 MB
Format: PDF
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By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments. Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers’ right to privacy while still engaging in forward-looking business practices. The book includes discussions of: SAS for asset management tools The AutoGrid approach to commercial analytics Space-Time Insight’s work at the California ISO (CAISO) This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs. At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.

From Big To Smart Data How Can Data Analytics Support Strategic Decisions To Gain Competitive Advantage

Author: Alexej Eichmann
Publisher: GRIN Verlag
ISBN: 3668074704
Size: 59.10 MB
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Research Paper (postgraduate) from the year 2015 in the subject Business economics - Operations Research, grade: 1, University of Applied Sciences Essen, language: English, abstract: One of the biggest challenges currently and in the upcoming years is the amount of data generated worldwide, which will increase exponentially by factor 10. The challenge for business leaders in the era of Big Data will be to identify and to use the most relevant data for decision-making in the context of Strategic Management. This assignment analysis which relevance data analytics of Big respectively Smart Data nowadays has and how it can be utilized in enterprises to gain a higher degree of competitive advantage. Therefore a few selected examples and use cases are provided on the Corporate, Business and Functional level of Strategic Management. Business leaders are using data analytics to understand cost and revenue drivers, to evaluate risks and to predict trends to improve business performance and to foster innovation. Studies show, that Big Data will revolutionize business operations and change the way of doing business. Companies not dealing with Big Data will lose their competitive advantage. With a deeper understanding of customers’ behavior and demands through analysis of Big Data, companies can find new ways to approach existing and potential customers by improved or new products. Criticism related to this is the debate about data security and data privacy and the misuse of personal data.

Querying Over Encrypted Data In Smart Grids

Author: Mi Wen
Publisher: Springer
ISBN: 3319063553
Size: 73.87 MB
Format: PDF, ePub
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This SpringerBrief presents the concept of the smart grid architecture and investigates the security issues of the smart grid and the existing encrypted data query techniques. Unique characteristics of smart grid impose distinguished challenges on this investigation, such as multidimensional attributes in metering data and finer grained query on each dimension. Three kinds of queries are introduced, namely, equality query, conjunctive query and range query. For the equality query over encrypted metering data, an efficient searchable encryption scheme is introduced and can be applied for auction in emerging smart grid marketing. Later chapters examine the conjunctive query and range query over encrypted data. Different techniques are used, including the Public key Encryption with Keyword Search (PEKS) and Hidden Vector Encryption (HVE), to construct the comparison predicate and range query predicate. Their correctness is demonstrated in the book. Concise and practical, Encrypted Data Querying in Smart Grids is valuable for professionals and researchers involved in data privacy or encryption. It is also useful for graduate students interested in smart grid and related technologies.

Energy Management Of Internet Data Centers In Smart Grid

Author: Tao Jiang
Publisher: Springer
ISBN: 3662456761
Size: 80.50 MB
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This book reports the latest findings on intelligent energy management of Internet data centers in smart-grid environments. The book gathers novel research ideas in Internet data center energy management, especially scenarios with cyber-related vulnerabilities, power outages and carbon emission constraints. The book will be of interest to university researchers, R&D engineers and graduate students in communication and networking areas who wish to learn the core principles, methods, algorithms, and applications of energy management of Internet data centers in smart grids.

Big Data And Internet Of Things A Roadmap For Smart Environments

Author: Nik Bessis
Publisher: Springer
ISBN: 331905029X
Size: 32.33 MB
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This book presents current progress on challenges related to Big Data management by focusing on the particular challenges associated with context-aware data-intensive applications and services. The book is a state-of-the-art reference discussing progress made, as well as prompting future directions on the theories, practices, standards and strategies that are related to the emerging computational technologies and their association with supporting the Internet of Things advanced functioning for organizational settings including both business and e-science. Apart from inter-operable and inter-cooperative aspects, the book deals with a notable opportunity namely, the current trend in which a collectively shared and generated content is emerged from Internet end-users. Specifically, the book presents advances on managing and exploiting the vast size of data generated from within the smart environment (i.e. smart cities) towards an integrated, collective intelligence approach. The book also presents methods and practices to improve large storage infrastructures in response to increasing demands of the data intensive applications. The book contains 19 self-contained chapters that were very carefully selected based on peer review by at least two expert and independent reviewers and is organized into the three sections reflecting the general themes of interest to the IoT and Big Data communities: Section I: Foundations and Principles Section II: Advanced Models and Architectures Section III: Advanced Applications and Future Trends The book is intended for researchers interested in joining interdisciplinary and transdisciplinary works in the areas of Smart Environments, Internet of Things and various computational technologies for the purpose of an integrated collective computational intelligence approach into the Big Data era.