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| data cube technology ppt: Data Mining: Concepts and Techniques Jiawei Han, Micheline Kamber, Jian Pei, 2011-06-09 Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data |
| data cube technology ppt: Data Mining for Beginners Agasti Khatri, 2025-01-03 Data Mining for Beginners: A Programmer’s Guide delves into the world of data mining, a process of discovering patterns and trends in large volumes of data using various algorithms and techniques. This book offers a comprehensive introduction to data mining, focusing on important concepts and their implementation using Python, a popular programming language. We provide step-by-step guidance through Python code to help readers understand and apply data mining techniques. The book covers essential topics like clustering, anomaly detection, data visualization, and processing, making it easier to grasp these concepts and use them in various fields. By the end of the book, readers will be well-versed in data mining concepts and capable of implementing them with Python. What you will learn: • Introduction to data mining and its various concepts. • Data visualization and processing techniques. • The importance of statistics in data mining. • Different data mining algorithms and their implementation in Python. • Cluster analysis and anomaly detection using Python. • Data Cube Technology. • Future trends and research frontiers in data mining. Who the book is for: This book is ideal for programmers seeking to implement data mining algorithms using Python and for students looking for a solid introduction to data mining. |
| data cube technology ppt: OLAP Solutions Erik Thomsen, 2002-10-15 OLAP enables users to access information from multidimensional datawarehouses almost instantly, to view information in any way theylike, and to cleanly specify and carry out sophisticatedcalculations. Although many commercial OLAP tools and products arenow available, OLAP is still a difficult and complex technology tomaster. Substantially updated with expanded coverage of implementationmethods for data storage, access, and calculation; also, newchapters added to combine OLAP with data warehouse, mining, anddecision support tools Teaches the best practices for building OLAP models thatimprove business and organizational decision-making, completelyindependent of commercial tools, using revised case studies Companion Web site provides updates on OLAP standards andtools, code examples, and links to valuable resources |
| data cube technology ppt: Frequent Pattern Mining Charu C. Aggarwal, Jiawei Han, 2016-09-10 This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference. |
| data cube technology ppt: INTRODUCTION TO DATA MINING WITH CASE STUDIES GUPTA, G.K., 2014-06-28 The field of data mining provides techniques for automated discovery of valuable information from the accumulated data of computerized operations of enterprises. This book offers a clear and comprehensive introduction to both data mining theory and practice. It is written primarily as a textbook for the students of computer science, management, computer applications, and information technology. The book ensures that the students learn the major data mining techniques even if they do not have a strong mathematical background. The techniques include data pre-processing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and OLAP. To enhance the understanding of the concepts introduced, and to show how the techniques described in the book are used in practice, each chapter is followed by one or two case studies that have been published in scholarly journals. Most case studies deal with real business problems (for example, marketing, e-commerce, CRM). Studying the case studies provides the reader with a greater insight into the data mining techniques. The book also provides many examples, review questions, multiple choice questions, chapter-end exercises and a good list of references and Web resources especially those which are easy to understand and useful for students. A number of class projects have also been included. |
| data cube technology ppt: Data Mining: Introductory and Advanced Topics Dunham, Sridhar, In this book the author provides the reader with a comprehensive coverage of data mining topics and algorithms. Data base perspective is maintained throughout the book which provides students with a focused discussion of algorithms, data structures, data types and complexity of algorithms and space. It also emphasizes the use of data mining concepts in real-world applications with large database components. |
| data cube technology ppt: 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. |
| data cube technology ppt: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms |
| data cube technology ppt: Mining of Massive Datasets Jure Leskovec, Jurij Leskovec, Anand Rajaraman, Jeffrey David Ullman, 2014-11-13 Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets. |
| data cube technology ppt: Mastering Data Warehouse Design Claudia Imhoff, Nicholas Galemmo, Jonathan G. Geiger, 2003 A cutting-edge response to Ralph Kimball's challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing Written by one of the best-known exponents of the Bill Inmon approach to data warehousing Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems Weighs the pros and cons of relational vs. dimensional modeling techniques Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality |
| data cube technology ppt: The Purchasing Chessboard Christian Schuh, Joseph L. Raudabaugh, Robert Kromoser, Michael F. Strohmer, Alenka Triplat, 2011-11-27 The approach used on a given spend item should largely depend on the balance between supply power and demand power. That is the logic behind the bestselling Purchasing Chessboard®, used by hundreds of corporations worldwide to reduce costs and increase value with suppliers. The 64 squares in the Purchasing Chessboard provide a rich reservoir of methods that can be applied either individually or combined. And because many of these methods are not customarily used by procurement, the Purchasing Chessboard is also the perfect tool for helping buyers to think and act outside the box and find new solutions. A well-proven concept that works across all industries and all categories in any given situation, it is little wonder that business leaders and procurement professionals alike are excited by, and enjoy strategizing around, the Purchasing Chessboard. This second edition of The Purchasing Chessboard addresses the new realities of a highly volatile economic environment and describes the many—sometimes surprising—ways in which the Purchasing Chessboard is being used in today's business world. Yet despite all of the great achievements of procurement executives and their teams, they do not always receive the recognition they deserve. In response, the authors have developed and outlined within the book an unequivocal approach to measure procurement’s impact on a company’s performance—Return on Supply Management Assets (ROSMA®). |
| data cube technology ppt: Big Data Min Chen, Shiwen Mao, Yin Zhang, Victor C.M. Leung, 2014-05-05 This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise management, online social networks, healthcare and medical applications, collective intelligence and smart grids. This book concludes with a thoughtful discussion of possible research directions and development trends in the field. Big Data: Related Technologies, Challenges and Future Prospects is a concise yet thorough examination of this exciting area. It is designed for researchers and professionals interested in big data or related research. Advanced-level students in computer science and electrical engineering will also find this book useful. |
| data cube technology ppt: Digital Destiny Shawn DuBravac, 2015-01-12 Our world is about to change. In Digital Destiny: How the New Age of Data Will Change the Way We Live, Work, and Communicate, Shawn DuBravac, chief economist and senior director of research at the Consumer Electronics Association (CEA), argues that the groundswell of digital ownership unfolding in our lives signals the beginning of a new era for humanity. Beyond just hardware acquisition, the next decade will be defined by an all-digital lifestyle and the “Internet of Everything”—where everything, from the dishwasher to the wristwatch, is not only online, but acquiring, analyzing, and utilizing the data that surrounds us. But what does this mean in practice? It means that some of mankind’s most pressing problems, such as hunger, disease, and security, will finally have a solution. It means that the rise of driverless cars could save thousands of American lives each year, and perhaps hundreds of thousands more around the planet. It means a departure from millennia-old practices, such as the need for urban centers. It means that massive inefficiencies, such as the supply chains in Africa allowing food to rot before it can be fed to the hungry, can be overcome. It means that individuals will have more freedom in action, work, health, and pursuits than ever before. |
| data cube technology ppt: Gravel Roads Ken Skorseth, 2000 The purpose of this manual is to provide clear and helpful information for maintaining gravel roads. Very little technical help is available to small agencies that are responsible for managing these roads. Gravel road maintenance has traditionally been more of an art than a science and very few formal standards exist. This manual contains guidelines to help answer the questions that arise concerning gravel road maintenance such as: What is enough surface crown? What is too much? What causes corrugation? The information is as nontechnical as possible without sacrificing clear guidelines and instructions on how to do the job right. |
| data cube technology ppt: Big Data Balamurugan Balusamy, Nandhini Abirami R, Seifedine Kadry, Amir H. Gandomi, 2021-03-15 Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book. |
| data cube technology ppt: Social Science Research Anol Bhattacherjee, 2012-03-16 This book is designed to introduce doctoral and graduate students to the process of scientific research in the social sciences, business, education, public health, and related disciplines. |
| data cube technology ppt: Using Technology with Classroom Instruction That Works Howard Pitler, Elizabeth R. Hubbell, Matt Kuhn, 2012-08-02 Technology is ubiquitous, and its potential to transform learning is immense. The first edition of Using Technology with Classroom Instruction That Works answered some vital questions about 21st century teaching and learning: What are the best ways to incorporate technology into the curriculum? What kinds of technology will best support particular learning tasks and objectives? How does a teacher ensure that technology use will enhance instruction rather than distract from it? This revised and updated second edition of that best-selling book provides fresh answers to these critical questions, taking into account the enormous technological advances that have occurred since the first edition was published, including the proliferation of social networks, mobile devices, and web-based multimedia tools. It also builds on the up-to-date research and instructional planning framework featured in the new edition of Classroom Instruction That Works, outlining the most appropriate technology applications and resources for all nine categories of effective instructional strategies: * Setting objectives and providing feedback * Reinforcing effort and providing recognition * Cooperative learning * Cues, questions, and advance organizers * Nonlinguistic representations * Summarizing and note taking * Assigning homework and providing practice * Identifying similarities and differences * Generating and testing hypotheses Each strategy-focused chapter features examples—across grade levels and subject areas, and drawn from real-life lesson plans and projects—of teachers integrating relevant technology in the classroom in ways that are engaging and inspiring to students. The authors also recommend dozens of word processing applications, spreadsheet generators, educational games, data collection tools, and online resources that can help make lessons more fun, more challenging, and—most of all—more effective. |
| data cube technology ppt: Microsoft Powerpoint 2003 - Illustrated Brief David Beskeen, 2003-11 The visual and flexible way to learn Microsoft PowerPoint skills. |
| data cube technology ppt: Changing the Interface of Education with Revolutionary Learning Technologies Nishikant Sonwalkar Sc. D. MIT, 2004-09 The pedagogy for technology enabled education over last few decades have been influenced by behaviorist, cognitive, and constructivist theories. These theories are debated vigorously by the educational scientists. While the debate is extremely important for the paradigm shift, the need for a framework for instructional designers seeking meaningful incorporation of technology is necessary. With the infusion of new technological methods to deliver education on-line there is an acute need for reinvention of the pedagogical framework. The new design framework to provide a flexible approach for incorporating technology within the context of pedagogy. The interface of education is changing rapidly from classroom to--blend of in-class and on-line activities to--almost completely technology enabled educational environments. The technological shift is taking place now from classroom teaching and learning to asynchronous Web-based and Web-supported learning environments. The dissemination of educational content is surely moving from a teacher-to-student model to a technology-enabled interface. The shift of educational interfaces from, synchronous to asynchronous, passive to interactive, television to desktop computers, keyboard to handwriting recognition systems, mouse to data glove, touch screen to voice recognition systems, real experiments to virtual experiments, real educational space to virtual reality learning environments (VRLE), experiments in labs to teleoperated experiments from remote locations, are all indicative of the technology trends which the educational designers have to face now to provide pedagogically effective educational technology components for learners. |
| data cube technology ppt: Biologically Inspired Robotics Yunhui Liu, Dong Sun, 2011-12-21 Robotic engineering inspired by biology—biomimetics—has many potential applications: robot snakes can be used for rescue operations in disasters, snake-like endoscopes can be used in medical diagnosis, and artificial muscles can replace damaged muscles to recover the motor functions of human limbs. Conversely, the application of robotics technology to our understanding of biological systems and behaviors—biorobotic modeling and analysis—provides unique research opportunities: robotic manipulation technology with optical tweezers can be used to study the cell mechanics of human red blood cells, a surface electromyography sensing system can help us identify the relation between muscle forces and hand movements, and mathematical models of brain circuitry may help us understand how the cerebellum achieves movement control. Biologically Inspired Robotics contains cutting-edge material—considerably expanded and with additional analysis—from the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). These 16 chapters cover both biomimetics and biorobotic modeling/analysis, taking readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems. Contributors examine a wide range of topics, including: A method for controlling the motion of a robotic snake The design of a bionic fitness cycle inspired by the jaguar The use of autonomous robotic fish to detect pollution A noninvasive brain-activity scanning method using a hybrid sensor A rehabilitation system for recovering motor function in human hands after injury Human-like robotic eye and head movements in human–machine interactions A state-of-the-art resource for graduate students and researchers in the fields of control engineering, robotics, and biomedical engineering, this text helps readers understand the technology and principles in this emerging field. |
| data cube technology ppt: PR Technology, Data and Insights Mark Weiner, 2021-04-03 Data, technology and insights have forever changed the public relations and corporate communications function. Failure to adapt is more a matter of willingness than inability. Now, technology, data and insights inform more meaningful objectives and elevate performance evaluation. The result is a positive return on PR investment, reduced reputational risk and optimal efficiency. By ignoring these essential assets, PR professionals risk losing executive attention and organizational investment. While building buzz or breaking through the media clutter may have been adequate measures of success in the past, the top executives who fund and evaluate corporate communications expect much more, including a quantifiable and positive return on PR investment. Leaders assume that corporate communications and PR professionals already understand the fundamentals of business, and they expect an ability to contextualize PR objectives, outputs and outcomes in the language of business. PR Technology, Data and Insights helps communications professionals understand the purpose-built technologies, data assets and actionable insights available to them while sharing best practices to apply these assets for improved PR performance over time, versus objectives and against competitors. Using case studies from industries as varied as financial services, technology, travel, automotive and more, along with best practice examples from Adobe, Mastercard, Southwest, Ford and other world class organizations, PR Technology, Data and Insights shows professional communicators how to optimize technology, lead with data, quantify PR's ability to convert public relations outputs to business outcomes, and deliver insights that empower executive decision-making. |
| data cube technology ppt: FUNDAMENTALS OF BUSINESS ANALYTICS (With CD ) R. N. Prasad, Seema Acharya, 2011-08 Market_Desc: Primary MarketEngineering (BE/BTech)/ME/MTech students who are interested to develop conceptual level subject knowledge with examples of industrial strength applications.Secondary MarketMCA/MBA/Business users/business analysts Special Features: · Foreword by Prof R Natarajan, Former Chairman, AICTE, Former Director, IIT Madras.· Excellent authorship.· Single source of introductory knowledge on business intelligence (BI).· Provides a good start for first-time learners typically from the engineering and management discipline.· Covers the complete life cycle of BI/Analytics Application development project.· Helps develop deeper understanding of the subject with an enterprise context, and discusses its application in businesses.· Explains concepts with the help of illustrations, application to real-life scenarios and provides opportunities to test understanding.· States the pre-requisites for each chapter and different reference sources available.· In addition the book also has the following pedagogical features:· Industrial application case studies.· Crossword puzzles/do it yourself exercises/assignments to help with self-assessment. The solutions to these have also been provided. · Glossary of terms.· References/web links/bibliography - generally at the end of every concept.CD Companion:To ensure that concepts can be practiced for deeper understanding at low cost, the book is accompanied with a CD containing:· Step-by-step Hands-On manual on:ü An open source tool, Pentaho Data Integrator (PDI) to explain the process of extraction of data from multiple varied sources.ü MS Excel to explain the concept of analysis.ü MS Access to generate reports on the analyzed data.· An integrated project that encompasses the complete life cycle of a BI project. About The Book: The book promises to be a single source of introductory knowledge on business intelligence which can be taught in one semester. It will provide a good start for first time learners typically from the engineering and management discipline. Business Intelligence subject cannot be studied in isolation. The book provides a holistic coverage beginning with an enterprise context, developing deeper understanding through the use of tools, touching a few domains where BI is embraced and discussing the problems that BI can help solve. It covers the complete life cycle of BI/Analytics project: Covering operational/transactional data sources, data transformation, data mart/warehouse design-build, analytical reporting, and dashboards. To ensure that concepts can be practiced for deeper understanding at low cost, the book is accompanied with step-by-step hands-on manual in the CD. |
| data cube technology ppt: Data Mining and Data Warehousing S. K. Mourya, Shalu Gupta, 2013 Data mining (if you haven't heard of it before), is the Automated Extraction of Hidden Predictive Information from Databases. This book discusses in a step by step approach instructions for the entire data modeling process, with special emphasis on the business knowledge necessary for effective results giving quick introductions to database and data mining concepts with particular emphasis on data analysis followed by concepts and techniques that underlie classification, prediction, association, and clustering. These topics are presented with examples and algorithms for each problem. The Socratic presentation style is both very readable and very informative. The purpose of this book is to serve as a handbook for analysts, data miners, and marketing managers at all levels. |
| data cube technology ppt: Microsoft Office Power Point 2003 Basic David W. Beskeen, 2004-04 Help users master computer skills quickly and easily with this colorful, highly-visual Illustrated Course Guide for PowerPoint 2003. Lessons are presented in an easy-to-follow 2-page spread that introduces step-by-step instructions on the left page and large screenshots and illustrations on the right. This signature, streamlined approach allows continuing education students learn quickly, while also serving as an excellent reference tool. |
| data cube technology ppt: Advanced Calculus Lynn H. Loomis, Shlomo Sternberg, 2014 An authorised reissue of the long out of print classic textbook, Advanced Calculus by the late Dr Lynn Loomis and Dr Shlomo Sternberg both of Harvard University has been a revered but hard to find textbook for the advanced calculus course for decades. This book is based on an honors course in advanced calculus that the authors gave in the 1960's. The foundational material, presented in the unstarred sections of Chapters 1 through 11, was normally covered, but different applications of this basic material were stressed from year to year, and the book therefore contains more material than was covered in any one year. It can accordingly be used (with omissions) as a text for a year's course in advanced calculus, or as a text for a three-semester introduction to analysis. The prerequisites are a good grounding in the calculus of one variable from a mathematically rigorous point of view, together with some acquaintance with linear algebra. The reader should be familiar with limit and continuity type arguments and have a certain amount of mathematical sophistication. As possible introductory texts, we mention Differential and Integral Calculus by R Courant, Calculus by T Apostol, Calculus by M Spivak, and Pure Mathematics by G Hardy. The reader should also have some experience with partial derivatives. In overall plan the book divides roughly into a first half which develops the calculus (principally the differential calculus) in the setting of normed vector spaces, and a second half which deals with the calculus of differentiable manifolds. |
| data cube technology ppt: Market Data Analysis Using JMP Walter R. Paczkowski, 2016-12-19 With the powerful interactive and visual functionality of JMP, you can dynamically analyze market data to transform it into actionable and useful information with clear, concise, and insightful reports and displays. Market Data Analysis Using JMP is a unique example-driven book because it has a specific application focus: market data analysis. A working knowledge of JMP will help you turn your market data into vital knowledge that will help you succeed in a highly competitive, fast-moving, and dynamic business world. This book can be used as a stand-alone resource for working professionals, or as a supplement to a business school course in market data research. Anyone who works with market data will benefit from reading and studying this book, then using JMP to apply the dynamic analytical concepts to their market data. After reading this book, you will be able to quickly and effortlessly use JMP to: prepare market data for analysis use and interpret sophisticated statistical methods build choice models estimate regression models to turn data into useful and actionable information Market Data Analysis Using JMP will teach you how to use dynamic graphics to illustrate your market data analysis and explore the vast possibilities that your data can offer! |
| data cube technology ppt: Pedagogical Documentation in Early Childhood Susan Stacey, 2015-05-11 An inspiring step-by-step guide to documenting children's ideas, questions, and learning in a way that enhances teacher's thinking and understanding |
| data cube technology ppt: Planning Algorithms Steven M. LaValle, 2006-05-29 Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations. |
| data cube technology ppt: Data Mining and Knowledge Discovery Handbook Oded Maimon, Lior Rokach, 2006-05-28 Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management. |
| data cube technology ppt: Microsoft Office PowerPoint 2003 David W. Beskeen, 2005-04 The visual and flexible way to learn Microsoft PowerPoint skills. |
| data cube technology ppt: Introduction to Probability Joseph K. Blitzstein, Jessica Hwang, 2014-07-24 Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment. |
| data cube technology ppt: The Sciences of the Artificial, third edition Herbert A. Simon, 1996-09-26 Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial intelligence adds a chapter that sorts out the current themes and tools—chaos, adaptive systems, genetic algorithms—for analyzing complexity and complex systems. There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter Economic Reality has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems. |
| data cube technology ppt: Physics for Scientists and Engineers, Volume 1 Raymond A. Serway, John W. Jewett, 2013-01-01 Achieve success in your physics course by making the most of what PHYSICS FOR SCIENTISTS AND ENGINEERS has to offer. From a host of in-text features to a range of outstanding technology resources, you'll have everything you need to understand the natural forces and principles of physics. Throughout every chapter, the authors have built in a wide range of examples, exercises, and illustrations that will help you understand the laws of physics AND succeed in your course! Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |
| data cube technology ppt: Modern Robotics Kevin M. Lynch, Frank C. Park, 2017-05-25 This introduction to robotics offers a distinct and unified perspective of the mechanics, planning and control of robots. Ideal for self-learning, or for courses, as it assumes only freshman-level physics, ordinary differential equations, linear algebra and a little bit of computing background. Modern Robotics presents the state-of-the-art, screw-theoretic techniques capturing the most salient physical features of a robot in an intuitive geometrical way. With numerous exercises at the end of each chapter, accompanying software written to reinforce the concepts in the book and video lectures aimed at changing the classroom experience, this is the go-to textbook for learning about this fascinating subject. |
| data cube technology ppt: Microsoft Office 2003-Illustrated Introductory David Beskeen, Lisa Friedrichsen, David W. Beskeen, Jennifer Duffy, Carol M. Cram, Elizabeth Eisner Reding, Cram, Duffy, Friedrichsen, Reding, 2004 Updated textbook for Microsoft Office 2003 includes coverage of the new features in Word, Excel, Access, and PowerPoint. It contains three Portfolio Project Sections, Advanced Challenge Exercises and higher level tasks. |
| data cube technology ppt: Introducing Microsoft Power BI Alberto Ferrari, Marco Russo, 2016 |
| data cube technology ppt: Decision Support Systems and Intelligent Systems Efraim Turban, Jay E. Aronson, Ting-Peng Liang, 2005 A guide to management support system technologies, and how they can be used for better decision making. It focuses on Web-enabled tools, performance analysis, knowledge management, and other innovations. |
| data cube technology ppt: Science And Technology In Deep Underground Laboratories Aldo Ianni, Sean M. Paling, Carlos Peña Garay, Jeter Hall, 2024-12-31 Deep Underground Laboratories are multidisciplinary research infrastructures with a rock overburden that goes from a few hundred meters to a few kilometers. Presently, there are 13 laboratories in operation on three Continents (North America, Europe, Asia, Australia) for a global excavation volume of order 10^6 m3. New laboratories are being constructed/proposed including a new one in South America. The main reason to develop an underground infrastructure is related to operate in a less radioactive environment where in particular muons from cosmic rays are strongly suppressed. This low background environment opens the possibility to search for very rare events such as low energy neutrino interactions, dark matter direct detection, and neutrinoless double beta decay. These are crucial studies to enhance our understanding of the Universe. In addition, these special environments in which these infrastructures are located provide opportunities to carry out many and varied studies on geology, geophysics, biology and planetary exploration of significant interest and impact in both pure and applied science. A number of technological challenges over the last decades have been faced by scientists working in these infrastructures. As a consequence, state-of-the-art facilities are in operation in Underground Laboratories for radio-purity assay, ultra-low temperature detectors, quantum computing, radon suppression and mitigation, advanced machining, and next-generation gravitational wave detectors. |
| data cube technology ppt: Cryptography and Network Security William Stallings, 2016-02-18 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. The Principles and Practice of Cryptography and Network Security Stallings’ Cryptography and Network Security, Seventh Edition, introduces the reader to the compelling and evolving field of cryptography and network security. In an age of viruses and hackers, electronic eavesdropping, and electronic fraud on a global scale, security is paramount. The purpose of this book is to provide a practical survey of both the principles and practice of cryptography and network security. In the first part of the book, the basic issues to be addressed by a network security capability are explored by providing a tutorial and survey of cryptography and network security technology. The latter part of the book deals with the practice of network security: practical applications that have been implemented and are in use to provide network security. The Seventh Edition streamlines subject matter with new and updated material — including Sage, one of the most important features of the book. Sage is an open-source, multiplatform, freeware package that implements a very powerful, flexible, and easily learned mathematics and computer algebra system. It provides hands-on experience with cryptographic algorithms and supporting homework assignments. With Sage, the reader learns a powerful tool that can be used for virtually any mathematical application. The book also provides an unparalleled degree of support for the reader to ensure a successful learning experience. |
| data cube technology ppt: Materialized Views Ashish Gupta, Inderpal Singh Mumick, 1999 When an application is built, an underlying data model is chosen to make that application effective. Frequently, other applications need the same data, only modeled differently. The na�ve solution of copying the underlying data and modeling is costly in terms of storage and makes data maintenance and evolution impossible. View mechanisms are a technique to model data differently for various applications without affecting the underlying format and structure of the data. The technique enables applications to customize shared data objects without affecting other applications that use the same objects. The growing data-manipulation needs of companies cannot be met by existing legacy systems that contain valuable data. Thus view mechanisms are becoming increasingly important as a way to model and use legacy data in new applications.Materialized views are views that have been computed and stored in databases. Because they reduce the need to recompute the view and/or data being queried, they speed up the querying of large amounts of data. Further, because they provide a systematic way to describe how to recompute the data, maintenance and evolution can be automated. Materialized views are especially useful in data warehousing, query optimization, integrity constraint maintenance, online analytical processing, and applications such as billing, banking, and retailing. This comprehensive volume, with a foreword by Jeff Ullman of Stanford University, will serve as a reference for students and commercial users, and encourage further use and development of materialized views. |
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Mosquitoes populations modelling for early warning system and …
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen science technology co-developed with local stakeholders for reporting locations of …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Data and Digital Outputs Management Annex (Full)
Released 5 May, 2017 This is the official Data and Digital Outputs Management Annex used by the Science Driven e-Infrastructures CRA. Includes questions to be answered during pre …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data and Digital Outputs Management Plan Template
Data and Digital Outputs Management Plan to ensure ethical approaches and compliance with the Belmont Forum Open Data Policy and Principles , as well as the F AIR Data Principles …
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Mosquitoes populations modelling for early warning system and …
Jun 10, 2020 · This technology will include the use of mobile surveillance apps using gamification and citizen science technology co-developed with local stakeholders for reporting locations of …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Data and Digital Outputs Management Annex (Full)
Released 5 May, 2017 This is the official Data and Digital Outputs Management Annex used by the Science Driven e-Infrastructures CRA. Includes questions to be answered during pre …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data and Digital Outputs Management Plan Template
Data and Digital Outputs Management Plan to ensure ethical approaches and compliance with the Belmont Forum Open Data Policy and Principles , as well as the F AIR Data Principles …
