Products related to Smart:
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Qlik Sense: Advanced Data Visualization for Your Organization : Create smart data visualizations and predictive analytics solutions
Perform Interactive Data Analysis with Smarter Visualizations and Support your Enterprise-wide Analytical Needs Key Features Get a practical demonstration of discovering data for sales, human resources, and more using Qlik Sense Create dynamic dashboards for business intelligence and predictive analytics Create and collaborate comprehensive analytical solutions using Rattle and Qlik Sense Book Description Qlik Sense is powerful and creative visual analytics software that allows users to discover data, explore it, and dig out meaningful insights in order to make a profit and make decisions for your business.This course begins by introducing you to the features and functions of the most modern edition of Qlik Sense so you get to grips with the application. The course will teach you how to administer the data architecture in Qlik Sense, enabling you to customize your own Qlik Sense application for your business intelligence needs.It also contains numerous recipes to help you overcome challenging situations while creating fully featured desktop applications in Qlik Sense.It explains how to combine Rattle and Qlik Sense Desktop to apply predictive analytics to your data to develop real-world interactive data applications.The course includes premium content from three of our most popular books: [*] Learning Qlik Sense: The Official Guide Second Edition [*] Qlik Sense Cookbook [*] Predictive Analytics using Rattle and Qlik Sense On completion of this course, you will be self-sufficient in improving your data analysis and will know how to apply predictive analytics to your datasets.Through this course, you will be able to create predictive models and data applications, allowing you to explore your data insights much deeper. What you will learn Build simple visualization models with Rattle and Qlik Sense Desktop Get to grips with the life cycle and new visualization functions of a Qlik Sense application Discover simple ways to examine data and get it ready for analysis Visualize your data with Qlik Sense's engaging and informative graphs Build efficient and responsive Associative Models Optimize Qlik Sense for sales, human resources, and demographic data discovery Explore various tips and tricks of navigation for the Qlik Sense® front end Develop creative extensions for your Qlik Sense® dashboardWho this book is for This course is for anyone who wishes to understand and utilize the various new approaches to business intelligence actively in their business practice.Knowing the basics of business intelligence concepts would be helpful when picking up this course, but is not mandatory.
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Smart Trajectories : Metamodeling, Reactive Architecture for Analytics, and Smart Applications
This book highlights the developments, discoveries, and practical and advanced experiences related to responsive distributed computing and how it can support the deployment of trajectory-based applications in smart systems.Smart Trajectories: Metamodeling, Reactive Architecture for Analytics and Smart Applications deals with the representation and manipulation of smart trajectories in various applications and scenarios.Presented in three parts, the book first discusses the foundation and principles for spatial information systems, complex event processing, and building a reactive architecture.Next, the book discusses modeling and architecture in relation to smart trajectory metamodeling, mining and big trajectory data, and clustering trajectories.The final section discusses advanced applications and trends in the field, including congestion trajectory analytics and real-time Big Data analytics in cloud ecosystems.Metamodeling, distributed architectures, reactive programming, Big Data analytics, NoSQL databases, connected objects, and edge-fog-cloud computing form the basis of the concepts and applications discussed.The book also presents a number of case studies to demonstrate smart trajectories related to spatiotemporal events such as traffic congestion and pedestrian accidents.This book is intended for graduate students in computer engineering, spatial databases, complex event processing, distributed systems, and geographical information systems (GIS).The book will also be useful for practicing traffic engineers, city managers, and environmental engineers interested in monitoring and security analysis.
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Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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Is spatial visualization important for engineers?
Yes, spatial visualization is important for engineers as it allows them to mentally manipulate and understand complex 3D objects and structures. Engineers often need to design and analyze various components and systems, and spatial visualization skills help them to conceptualize and communicate their ideas effectively. Whether it's designing a new product, creating blueprints for a building, or solving complex problems, spatial visualization is a crucial skill that allows engineers to think critically and innovate in their field.
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Can one improve their spatial visualization skills?
Yes, it is possible to improve spatial visualization skills through practice and training. Engaging in activities such as puzzles, building models, and playing spatial reasoning games can help develop these skills. Additionally, practicing mental rotation exercises and regularly challenging oneself with spatial tasks can also contribute to improvement. With consistent effort and dedication, individuals can enhance their spatial visualization abilities over time.
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What are problems with spatial visualization skills?
Some problems with spatial visualization skills include difficulty in understanding and interpreting maps, graphs, and diagrams. Individuals with poor spatial visualization skills may struggle with tasks such as navigating through unfamiliar environments, understanding 3D objects, and mentally rotating objects. This can impact their performance in subjects such as math, science, and engineering, as well as in everyday activities such as driving and assembling furniture. Additionally, poor spatial visualization skills can lead to frustration and decreased confidence in one's abilities.
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Mapping Society : The Spatial Dimensions of Social Cartography
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Building Smart Cities : Analytics, ICT, and Design Thinking
The term "smart city" defines the new urban environment, one that is designed for performance through information and communication technologies.Given that the majority of people across the world will live in urban environments within the next few decades, it's not surprising that massive effort and investment is being placed into efforts to develop strategies and plans for achieving "smart" urban growth.Building Smart Cities: Analytics, ICT, and Design Thinking explains the technology and a methodology known as design thinking for building smart cities. Information and communications technologies form the backbone of smart cities.A comprehensive and robust data analytics program enables the right choices to be made in building these cities.Design thinking helps to create smart cities that are both livable and able to evolve.This book examines all of these components in the context of smart city development and shows how to use them in an integrated manner. Using the principles of design thinking to reframe the problems of the smart city and capture the real needs of people living in a highly efficient urban environment, the book helps city planners and technologists through the following:Presentation of the relevant technologies required for coordinated, efficient citiesExploration of the latent needs of community stakeholders in a culturally appropriate contextDiscussion of the tested approaches to ideation, design, prototyping, and building or retrofitting smart citiesProposal of a model for a viable smart city projectThe smart city vision that we can create an optimized society through technology is hypothetical at best and reflects the failed repetition through the ages of equating scientific progress with positive social change.Up until now, despite our best hopes and efforts, technology has yet to bring an end to scarcity or suffering.Technical innovation, instead, can and should be directed in the service of our shared cultural values, especially within the rapidly growing urban milieu.In Building Smart Cities: Analytics, ICT, and Design Thinking, the author discusses the need to focus on creating human-centered approaches to our cities that integrate our human needs and technology to meet our economic, environmental, and existential needs.The book shows how this approach can lead to innovative, livable urban environments that are realizable, practical, and economically and environmentally sustainable.
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Spatial Epidemiological Approaches in Disease Mapping and Analysis
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.
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Crime Mapping and Spatial Data Analysis using R
Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
Price: 76.99 £ | Shipping*: 0.00 £
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What is the function of spatial visualization ability?
Spatial visualization ability allows individuals to mentally manipulate and understand spatial relationships between objects. This ability is crucial in fields such as engineering, architecture, and design, where individuals need to visualize and manipulate complex 3D objects and structures. It also plays a key role in tasks such as navigation, map reading, and understanding geometric concepts. Overall, spatial visualization ability is important for problem-solving, creativity, and understanding the physical world.
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What does it mean if someone lacks spatial visualization skills?
If someone lacks spatial visualization skills, it means that they have difficulty mentally manipulating and understanding spatial relationships between objects and shapes. This can manifest as challenges in tasks such as reading maps, understanding 3D objects, or visualizing how objects fit together in space. People with this difficulty may struggle with activities such as assembling furniture, reading graphs, or understanding geometric concepts. It's important to note that lacking spatial visualization skills does not indicate a lack of intelligence, but rather a specific cognitive challenge in this area.
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Is one also smart if they have smart friends?
Having smart friends can certainly influence one's own intelligence and knowledge. Interacting with intelligent individuals can lead to engaging discussions, exposure to new ideas, and opportunities for learning. However, one's own intelligence is ultimately determined by their own abilities, efforts, and experiences. While having smart friends can be beneficial, it does not automatically make someone smart.
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Do boys prefer smart girls over less smart ones?
Preferences can vary among boys, as some may prefer smart girls while others may not prioritize intelligence as much. Some boys may find intelligence attractive and value a partner who can engage in stimulating conversations and offer unique perspectives. However, it ultimately depends on the individual and what qualities they prioritize in a potential partner. Intelligence is just one aspect of a person, and different boys may have different preferences when it comes to what they find attractive in a girl.
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