Data Power


Book Description

An introduction to learning how to protect ourselves and organise against Big Data




Big Data Application in Power Systems


Book Description

Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data




M Is for (Data) Monkey


Book Description

Power Query is one component of the Power BI (Business Intelligence) product from Microsoft, and "M" is the name of the programming language created by it. As more business intelligence pros begin using Power Pivot, they find that they do not have the Excel skills to clean the data in Excel; Power Query solves this problem. This book shows how to use the Power Query tool to get difficult data sets into both Excel and Power Pivot, and is solely devoted to Power Query dashboarding and reporting.




Industry Unbound


Book Description

Privacy law isn't working. Waldman's groundbreaking work explains why, showing how tech companies manipulate us, our behavior, and our law.




Privacy is Power


Book Description

An Economist Book of the Year Every minute of every day, our data is harvested and exploited… It is time to pull the plug on the surveillance economy. Governments and hundreds of corporations are spying on you, and everyone you know. They're not just selling your data. They're selling the power to influence you and decide for you. Even when you've explicitly asked them not to. Reclaiming privacy is the only way we can regain control of our lives and our societies. These governments and corporations have too much power, and their power stems from us--from our data. Privacy is as collective as it is personal, and it's time to take back control. Privacy Is Power tells you how to do exactly that. It calls for the end of the data economy and proposes concrete measures to bring that end about, offering practical solutions, both for policymakers and ordinary citizens.




DataPower SOA Appliance Administration, Deployment, and Best Practices


Book Description

This IBM® Redbooks® publication focuses on operational and managerial aspects for DataPower® appliance deployments. DataPower appliances provide functionality that crosses both functional and organizational boundaries, which introduces unique management and operational challenges. For example, a DataPower appliance can provide network functionality, such as load balancing, and at the same time, provide enterprise service bus (ESB) capabilities, such as transformation and intelligent content-based routing. This IBM Redbooks publication provides guidance at both a general and technical level for individuals who are responsible for planning, installation, development, and deployment. It is not intended to be a "how-to" guide, but rather to help educate you about the various options and methodologies that apply to DataPower appliances. In addition, many chapters provide a list of suggestions.




Data Power


Book Description




Master Your Data with Power Query in Excel and Power BI


Book Description

Power Query is the amazing new data cleansing tool in both Excel and Power BI Desktop. Do you find yourself performing the same data cleansing steps day after day? Power Query will make it faster to clean your data the first time. While Power Query is powerful, the interface is subtle—there are tools hiding in plain sight that are easy to miss. Go beyond the obvious and take Power Query to new levels with this book.




A Combined Data and Power Management Infrastructure


Book Description

This book describes the development and design of a unique combined data and power management infrastructure The use in small satellites gives some particular requirements to the systems like potential hardware failure robustness and handling of different types of external analog and digital interfaces. These requirements lead to a functional merge between On Board Computer and the satellite's Power Control and Distribution Unit, which results in a very innovative design and even a patent affiliation. This book provides system engineers and university students with the technical knowledge as mix between technical brochure and a user guide.




Machine Learning and Data Science in the Power Generation Industry


Book Description

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. - Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful - Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them - Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems - Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls