dama

Dáma

Dáma je tradiční strategická desková hra s dřevěnými figurkami a herní deskou. Sada obsahuje 24 kamenů, rozkládací desku a český návod. Hra podporuje logické uvažování a je vhodná pro celou rodinu.

  • Nadčasová klasická desková hra s historií
  • Kvalitní dřevěné provedení figurek a desky
  • Rozvíjí strategické myšlení a logiku
  • Vhodná pro všechny věkové kategorie

Objev podobné jako Dáma

LEGO® Minecraft® 21273 Balón v podobě ďasa a útok na vesnici

Stavebnice LEGO Minecraft 21273 zobrazuje scénu útoku na vesnici s balónem v podobě ďasa. Obsahuje 555 dílků, pohyblivé figurky a interaktivní prvky jako vystřelovač. Je určena pro děti od 10 let a nabízí digitální zážitek prostřednictvím aplikace LEGO Builder.

  • Autentická scéna z filmu Minecraft s ikonickými postavami
  • Interaktivní prvky: vystřelovač disků a výbuch fontány
  • Kompatibilita s aplikací LEGO Builder pro 3D návod
  • Vysoká kvalita a detailní zpracování figurek a modelů

Objev podobné jako LEGO® Minecraft® 21273 Balón v podobě ďasa a útok na vesnici

Think Like Da Vinci - Michael Gelb

Kniha představuje sedm základních principů myšlení Leonarda da Vinciho a nabízí praktické způsoby, jak je aplikovat v každodenním životě. Obsahuje četná cvičení, příklady a ilustrace pro rozvoj kreativity, celomozkového myšlení a kontinuálního učení. Je určena všem, kteří chtějí naplnit svůj potenciál a dosáhnout osobní i profesionální renesance.

  • Nové vydání s aktualizovaným úvodem autora
  • Praktické techniky pro rozvoj kreativity a řešení problémů
  • Inspirace renesančním myšlením pro moderní život
  • Vhodné pro osobní i profesionální rozvoj

Objev podobné jako Think Like Da Vinci - Michael Gelb

Byl jednou jeden člověk - Leonardo da Vinci

Naučný komiks představuje život a dílo Leonarda da Vinciho, renesančního génia. Forma komiksu propojená s animovaným seriálem zpřístupňuje téma dětem od 8 let. Kniha má 48 stran v českém jazyce a rozměry 21 x 29 cm.

  • Naučný obsah podaný zábavnou komiksovou formou
  • Propojení s populárním animovaným seriálem České televize
  • Vhodné pro děti od 8 let s českým jazykem
  • Kvalitní rozměry 21x29 cm pro pohodlné čtení

Objev podobné jako Byl jednou jeden člověk - Leonardo da Vinci

Bonaparte Šachy Dáma Mlýn

Sada obsahuje tři klasické deskové hry – šachy, dámu a mlýn – na jednom oboustranném herním plánu. Hra je určena pro dva hráče od 7 let a podporuje rozvoj logického uvažování. Všechny komponenty jsou vyrobeny z dřeva a kartonu v České republice.

  • 3 klasické hry v jedné sadě (šachy, dáma, mlýn)
  • Vyráběno z kvalitního dřeva a kartonu v ČR
  • Rozvíjí logické myšlení a strategické plánování u dětí
  • Oboustranný herní plán pro snadné přecházení mezi hrami

Objev podobné jako Bonaparte Šachy Dáma Mlýn

Efko Pytlíczech Dáma - logická hra do kapsy

Dáma je logická hra uložená v bavlněném pytlíku, vhodná pro cestování. Sada obsahuje 24 dřevěných kamenů, skládací herní plán a návod. Hra je určena pro 2 hráče od 10 let s dobou hraní přibližně 15 minut.

  • Praktický bavlněný pytlík pro snadné přenášení
  • Dřevěné hrací kameny a skládací herní plán
  • Originální design od české designérky Táni Sekerkové
  • Vyrobeno v České republice

Objev podobné jako Efko Pytlíczech Dáma - logická hra do kapsy

VUCH Drop Dana (3997)

Dámská peněženka VUCH Drop Dana z umělé kůže v modré barvě. Disponuje patentovým zapínáním, samostatnou kapsou na mince a přihrádkou na bankovky. Rozměry jsou 9 × 19,5 × 2,5 cm.

  • Zabezpečené patentové zapínání chrání obsah
  • Praktické členění s kapsou na mince a bankovky
  • Stylový modrý design vhodný pro dámy
  • Kompaktní rozměry 9 × 19,5 × 2,5 cm pro každodenní nošení

Objev podobné jako VUCH Drop Dana (3997)

Dáma v rubáši - Bram Stoker

Román Dáma v rubáši je predposledným dielom Brama Stokera z roku 1909, ktoré vychádza v prvom slovenskom preklade. Príbeh kombinuje prvky hororu, romanticko-dobrodružného žánru, sci-fi a politickej utópie. Dej sa odohráva v prostredí tajomného hradu Vissarion v Modrých horách, kde hrdinu Ruperta Sent Legera čakajú četné nástrahy a osudové stretnutie.

  • Prvý slovenský preklad predposledného románu autora Draculu
  • Kombinácia viacerých žánrov – horor, dobrodružstvo, sci-fi, utópia
  • Tajomné prostredie hradu Vissarion a Modrých hôr
  • Napínavý príbeh s pozemnými, vzdušnými i morskými súbojmi

Objev podobné jako Dáma v rubáši - Bram Stoker

Rabalux 74073 stolní lampa Dayami, šedá

Šedá stolní keramická lampa Dayami s textilním stínidlem a originálně tvarovanou základnou. Vhodná pro žárovku s paticí E14 s maximálním příkonem 40 W. Ideální pro umístění na noční stolek, komodu nebo do obývacího pokoje.

  • Originální keramická základna s moderním vzorem
  • Šedé textilní stínidlo pro decentní vzhled a rozptýlené světlo
  • Elegantní design vhodný do různých interiérů
  • Možnost použití úsporné LED žárovky s paticí E14

Objev podobné jako Rabalux 74073 stolní lampa Dayami, šedá

Dámy se psy u auta, 40×50 cm, bez rámu a bez vypnutí plátna (6043120)

Sada pro malování podle čísel s motivem dam se psy u auta o rozměrech 40×50 cm. Balení obsahuje lněné plátno, sadu štětců, 34 akrylových barev a vymalovanou předlohu. Velké očíslované plochy usnadňují práci i začátečníkům.

  • Kompletní sada obsahující plátno, štětce, barvy a předlohu
  • Velké očíslované plochy vhodné pro začátečníky
  • 34 akrylových barev pro detailní výsledek
  • Kvalitní lněné plátno s tématem dopravních prostředků

Objev podobné jako Dámy se psy u auta, 40×50 cm, bez rámu a bez vypnutí plátna (6043120)

Big Data Fundamentals - Thomas Erl, Paul Buhler, Wajid Khattak

“This text should be required reading for everyone in contemporary business.” --Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” --Dr. Christopher Starr, PhD “Simply, this is the best Big Data book on the market!” --Sam Rostam, Cascadian IT Group “...one of the most contemporary approaches I’ve seen to Big Data fundamentals...” --Joshua M. Davis, PhD The Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages. Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science Understanding the business motivations and drivers behind Big Data adoption, ... Unknown localization key: "more"

Objev podobné jako Big Data Fundamentals - Thomas Erl, Paul Buhler, Wajid Khattak

Azure Data Engineer Associate Certification Guide - Newton Alex

Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certificationKey FeaturesUnderstand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification examExplore the various Azure services for building end-to-end data solutionsGain a solid understanding of building secure and sustainable data solutions using Azure servicesBook DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout ... Unknown localization key: "more"

Objev podobné jako Azure Data Engineer Associate Certification Guide - Newton Alex

Data Analysis with Python - Rituraj Dixit

An Absolute Beginner''s Guide to Learning Data Analysis Using Python, a Demanding Skill for TodayKey FeaturesHands-on learning experience of Python''s fundamentals.Covers various examples of how to code end-to-end data analysis with easy illustrations.An excellent starting point to begin your data analysis journey with Python programming.DescriptionIn an effort to provide content for beginners, the book Data Analysis with Python provides a concrete first step in learning data analysis. Written by a data professional with decades of experience, this book provides a solid foundation in data analysis and numerous data science processes. In doing so, readers become familiar with common Python libraries and straightforward scripting techniques.Python and many of its well-known data analysis libraries, such as Pandas, NumPy, and Matplotlib, are utilized throughout this book to carry out various operations typical of data analysis projects.Following an introduction to Python programming fundamentals, the book combines well-known numerical calculation and statistical libraries to demonstrate the fundamentals of programming, accompanied by many practical examples. This book provides a solid groundwork for data analysis by teaching Python programming as well as Python''s built-in data analysis capabilities.What you will learnLearn the fundamentals of core Python programming for data analysis.Master Python''s most demanding data analysis and visualization libraries, ... Unknown localization key: "more"

Objev podobné jako Data Analysis with Python - Rituraj Dixit

Effective Data Storytelling - Brent Dykes

Master the art and science of data storytelling—with frameworks and techniques to help you craft compelling stories with data. The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories. Narratives are more powerful than raw statistics, more enduring than pretty charts. When done correctly, data stories can influence decisions and drive change. Most other books focus only on data visualization while neglecting the powerful narrative and psychological aspects of telling stories with data. Author Brent Dykes shows you how to take the three central elements of data storytelling—data, narrative, and visuals—and combine them for maximum effectiveness. Taking a comprehensive look at all the elements of data storytelling, this unique book will enable you to: Transform your insights and data visualizations into appealing, impactful data storiesLearn the fundamental elements of a data story and key audience driversUnderstand the differences between how the brain ... Unknown localization key: "more"

Objev podobné jako Effective Data Storytelling - Brent Dykes

Data Science Bookcamp - Leonard Apeltsin

Learn data science with Python by building five real-world projects! In Data Science Bookcamp you’ll test and build your knowledge of Python and learn to handle the kind of open-ended problems that professional data scientists work on daily. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career. about the technologyIn real-world practice, data scientists create innovative solutions to novel open ended problems. Easy to learn and use, the Python language has become the de facto language for data science amongst researchers, developers, and business users. But knowing a few basic algorithms is not enough to tackle a vague and thorny problem. It takes relentless practice at cracking difficult data tasks to achieve mastery in the field. That’s just what this book delivers. about the book Data Science Bookcamp is a comprehensive set of challenging projects carefully designed to grow your data science skills from novice to master. Veteran data scientist Leonard Apeltsin sets five increasingly difficult exercises that test your abilities against the kind of problems you’d encounter in the real world. As you solve each challenge, you’ll acquire and expand the ... Unknown localization key: "more"

Objev podobné jako Data Science Bookcamp - Leonard Apeltsin

Building a Scalable Data Warehouse with Data Vault 2.0 - Daniel Linstedt, Michael Olschimke

The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in ... Unknown localization key: "more"

Objev podobné jako Building a Scalable Data Warehouse with Data Vault 2.0 - Daniel Linstedt, Michael Olschimke

DAMA-DMBOK Guide

Written by over 120 data management practitioners, this is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: Data Governance; Data Architecture Management; Data Development; Database Operations Management; Data Security Management; Reference & Master Data Management; Data Warehousing & Business Intelligence Management; Document & Content Management; Meta Data Management; Data Quality Management; Professional Development. As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are: To build consensus for a generally applicable view of data management functions; To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology; To document guiding principles for data management; To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches; To clarify the scope and boundaries of data management; To act as a reference which guides readers to additional resources for further understanding.

Objev podobné jako DAMA-DMBOK Guide

Data and Analytics for Instructional Designers - Megan Torrance

Add Data and Analytics to Your TD ToolkitInstructional design pro Megan Torrance addresses the importance of instructional designers accessing and applying learning and performance data—from how to design learning experiences with data collection in mind to how to use the data to improve and evaluate those experiences. With the advance of new learning technologies and data specifications, instructional designers have access to more and richer data sources than ever before. With that comes the question of what to do with the data. While most data and analytics books focus on their application for measurement and evaluation and assume a prior baseline understanding of what learning data and analytics mean, Data and Analytics for Instructional Designers delves into the foundational concepts that will enable instructional designers and L&D professionals to use data in their roles. Split into two parts, the book first defines key data and analytics terms, data specifications, learning metrics, and statistical concepts. It then lays out a framework for using learning data for planning how to gather data and to building scale and maturity in your data operations. Megan reassures readers that basic math skills with some computer assistance is what you’ll need to get going. So set ... Unknown localization key: "more"

Objev podobné jako Data and Analytics for Instructional Designers - Megan Torrance

Click, Connect, Compute: Data, Big and Small - Dr Dharini Balasubramaniam

Data science fundamentals, using clear, expert explanations and comic illustrations to spark interest and enthusiasm in the next generation of computer scientists!Data, Big and Small delves into the details behind computer science data and information, which help people and organisations to make decisions. Learn how and why data are created, stored and shared. Find out how we make sense of information through graphs, maps and pictures, and understand how machines learn from the data that we feed them. The end of the book fast-forwards to the future of computer science, data and robotics, and considers what it might mean to live in a ''smarter'' world.Contents: What are data? / Data, information and knowledge / Data are vital / Where do data come from? / Getting the format right / Storing all those data / The value is in the processing / Picture it! / Big data / Getting the most out of data / Keeping data secure / A trip into the future of data ... / Pioneer portraits / Further information / Glossary / Quiz yourself! / IndexThe Click, Connect, Compute series untangles the computer science web and teaches children about the essentials of computer software, hardware and digital ... Unknown localization key: "more"

Objev podobné jako Click, Connect, Compute: Data, Big and Small - Dr Dharini Balasubramaniam

Become a Great Data Storyteller - Angelica Lo Duca

Unlock the power of data storytelling to create change Become a Great Data Storyteller: Learn How You Can Drive Change with Data is a transformational journey guided by author and researcher Angelica Lo Duca. This insightful guide challenges the conventional approach to data visualization by emphasizing the creation of compelling data stories. With a focus on understanding the audience's needs, this book offers a unique value proposition: teaching you how to weave raw data into engaging, narrative-driven presentations that can significantly impact decision-making and generate organizational change. The author masterfully demonstrates the process of building a data story, from creating relatable characters with clear objectives to tailoring these narratives for specific audiences. You'll discover your role as a narrative guide, learning how to employ the power of context to make your data-driven stories not just informative but captivating. This book sets itself apart by focusing on the human aspect of data storytelling, ensuring your narratives resonate deeply with your audience. In the book, you'll: Learn to craft engaging data narratives that go beyond charts and graphs, making your presentations memorable and impactfulTailor your data stories to meet the specific needs and interests of your audience, enhancing understanding and engagementPosition yourself ... Unknown localization key: "more"

Objev podobné jako Become a Great Data Storyteller - Angelica Lo Duca

Developing Data Migrations and Integrations with Salesforce - David Masri

Migrate your data to Salesforce and build low-maintenance and high-performing data integrations to get the most out of Salesforce and make it a "go-to" place for all your organization''s customer information.When companies choose to roll out Salesforce, users expect it to be the place to find any and all Information related to a customer-the coveted Client 360° view. On the day you go live, users expect to see all their accounts, contacts, and historical data in the system. They also expect that data entered in other systems will be exposed in Salesforce automatically and in a timely manner. This book shows you how to migrate all your legacy data to Salesforce and then design integrations to your organization''s mission-critical systems. As the Salesforce platform grows more powerful, it also grows in complexity. Whether you are migrating data to Salesforce, or integrating with Salesforce, it is important to understand how these complexities need to be reflected in your design. Developing Data Migrations and Integrations with Salesforce covers everything you need to know to migrate your data to Salesforce the right way, and how to design low-maintenance, high-performing data integrations with Salesforce. This book is written by a practicing Salesforce integration architect ... Unknown localization key: "more"

Objev podobné jako Developing Data Migrations and Integrations with Salesforce - David Masri

Data Storytelling with Generative AI - Angelica Duca

Great data presentations tell a story. Learn how to organize, visualize, and present data using Python, generative AI, and the cutting-edge Altair data analysis toolkit.After you''ve crunched, sliced, and organized your data behind the scenes, you need to present it in a way that tells a story. With Python''s Altair library and generative AI tools like Copilot and ChatGPT, it''s never been easier to create intuitive data presentations.In Data Storytelling with Generative AI you''ll discover: Using Python Altair for data visualization Using Generative AI tools for data storytelling The main concepts of data storytelling Building data stories with the DIKW pyramid approach Transforming raw data into a data story Data Storytelling with Generative AI teaches you how to turn raw data into effective, insightful data stories. You''ll learn exactly what goes into an effective data story, then combine your Python data skills with the Altair library and AI tools to rapidly create amazing visualizations. Your bosses and decision-makers will love your new presentations—and you''ll love how quick Generative AI makes the whole process!

Objev podobné jako Data Storytelling with Generative AI - Angelica Duca

Click, Connect, Compute: Data, Big and Small - Dr Dharini Balasubramaniam

Data science fundamentals, using clear, expert explanations and comic illustrations to spark interest and enthusiasm in the next generation of computer scientists!Data, Big and Small delves into the details behind computer science data and information, which help people and organisations to make decisions. Learn how and why data are created, stored and shared. Find out how we make sense of information through graphs, maps and pictures, and understand how machines learn from the data that we feed them. The end of the book fast-forwards to the future of computer science, data and robotics, and considers what it might mean to live in a ''smarter'' world.Contents: What are data? / Data, information and knowledge / Data are vital / Where do data come from? / Getting the format right / Storing all those data / The value is in the processing / Picture it! / Big data / Getting the most out of data / Keeping data secure / A trip into the future of data ... / Pioneer portraits / Further information / Glossary / Quiz yourself! / IndexThe Click, Connect, Compute series untangles the computer science web and teaches children about the essentials of computer software, hardware and digital ... Unknown localization key: "more"

Objev podobné jako Click, Connect, Compute: Data, Big and Small - Dr Dharini Balasubramaniam

Interactive Visual Data Analysis - Christian Tominski, Heidrun Schumann

In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data.The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis.The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book ... Unknown localization key: "more"

Objev podobné jako Interactive Visual Data Analysis - Christian Tominski, Heidrun Schumann

Big Data Concepts, Technologies, and Applications - Mohammad Shahid Husain, Tamanna Siddiqui, Mohammad Zunnun Khan

With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them.Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include:The advantages, disadvantages and challenges ... Unknown localization key: "more"

Objev podobné jako Big Data Concepts, Technologies, and Applications - Mohammad Shahid Husain, Tamanna Siddiqui, Mohammad Zunnun Khan

Data Mesh in Action - Marian Siwiak, Jacek Majchrzak, Sven Balnojan

About The BookRevolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size.Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You''ll see a data mesh in action as you explore both an extended case study and multiple real-world examples. As you go, you''ll be expertly guided through discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-product system.About the technologyA data mesh decentralizes data ownership and keeps it close to decision makers and domain experts. The results are clear: better description and structuring, easier scaling, and removing the bottlenecks of centralized monolithic data architecture. Best of all, you won''t need any new technology—his book shows you how to immediately start implementing a data mesh with flexible processes and organizational change.- Move from your current data architecture to a data mesh- Identify data domains, and decompose an organization into smaller, manageable domains - Set up the central governance and local governance levels over data - Balance responsibilities between the two levels of governance - Establish a platform that allows ... Unknown localization key: "more"

Objev podobné jako Data Mesh in Action - Marian Siwiak, Jacek Majchrzak, Sven Balnojan

SQL for Data Scientists - Renee M. P. Teate

Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on ... Unknown localization key: "more"

Objev podobné jako SQL for Data Scientists - Renee M. P. Teate

Mastering Marketing Data Science - Iain Brown

Unlock the Power of Data: Transform Your Marketing Strategies with Data Science In the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers, Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively. Comprehensive Coverage: From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science. Practical Applications: Engage with real-world examples, hands-on exercises in both Python & SAS, and actionable insights to apply in your marketing campaigns. Expert Guidance: Benefit from Dr. Iain Brown's decade of experience as he shares ... Unknown localization key: "more"

Objev podobné jako Mastering Marketing Data Science - Iain Brown

Exam Ref 70-767 Implementing a SQL Data Warehouse - Jose Chinchilla, Raj Uchhana

Prepare for Microsoft Exam 70-767–and help demonstrate your real-world mastery of skills for managing data warehouses. This exam is intended for Extract, Transform, Load (ETL) data warehouse developers who create business intelligence (BI) solutions. Their responsibilities include data cleansing as well as ETL and data warehouse implementation. The reader should have experience installing and implementing a Master Data Services (MDS) model, using MDS tools, and creating a Master Data Manager database and web application. The reader should understand how to design and implement ETL control flow elements and work with a SQL Service Integration Services package. Focus on the expertise measured by these objectives: • Design, and implement, and maintain a data warehouse • Extract, transform, and load data • Build data quality solutionsThis Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have working knowledge of relational database technology and incremental database extraction, as well as experience with designing ETL control flows, using and debugging SSIS packages, accessing and importing or exporting data from multiple sources, and managing a SQL data warehouse. Implementing a SQL Data Warehouse About the Exam Exam 70-767 focuses on skills and knowledge ... Unknown localization key: "more"

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Graph Algorithms for Data Science - Bratanic Tomaz

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It''s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You''ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don''t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal ... Unknown localization key: "more"

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Halo Data - Peter Jackson, Caroline Carruthers

The past two decades have seen an explosion both in the volume of data we use, and our understanding of its management.However, while techniques and technology for manipulating data have advanced rapidly in this time, the concepts around the value of our data have not. This lack of progress has made it increasingly difficult for organisations to understand the value in their data, the value of their data and how exploit that value. Halo Data proposes a paradigm shift in methodology for organisations to properly appreciate and leverage the value of their data. Written by an author team with many years’ experience in data strategy, management and technology, the book will first review the current state of our understanding of data. This opening will demonstrate the limitations of this status quo, including a discussion on metadata and its limitations, data monetisation and data-driven business models. Following this, the book will present a new concept and framework for understanding and quantifying value in an organisation’s data and a practical methodology for using this in practice.Ideal for data leaders and executives who are looking to leverage the data at their fingertips.

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R for Data Science - Grolemund Garrett, Hadley Wickham, Mine Cetinkaya-Rundel

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse-a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Each section in this edition includes exercises to help you practice what you've learned along the way.Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools. You'll learn how to:Visualize-create plots for data exploration and communication of resultsTransform-discover types of variables and the tools you can use to work with themImport-get data into R and in a form convenient for analysisProgram-learn R tools for solving data problems with ... Unknown localization key: "more"

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Data Governance For Dummies - Jonathan Reichental

How to build and maintain strong data organizations—the Dummies way Data Governance For Dummies offers an accessible first step for decision makers into understanding how data governance works and how to apply it to an organization in a way that improves results and doesn't disrupt. Prep your organization to handle the data explosion (if you know, you know) and learn how to manage this valuable asset. Take full control of your organization’s data with all the info and how-tos you need. This book walks you through making accurate data readily available and maintaining it in a secure environment. It serves as your step-by-step guide to extracting every ounce of value from your data. Identify the impact and value of data in your businessDesign governance programs that fit your organizationDiscover and adopt tools that measure performance and needAddress data needs and build a more data-centric business cultureThis is the perfect handbook for professionals in the world of data analysis and business intelligence, plus the people who interact with data on a daily basis. And, as always, Dummies explains things in terms anyone can understand, making it easy to learn everything you need to know.

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Afterlives of Data - Mary F.E. Ebeling

What our health data tell American capitalism about our value—and how that controls our lives. Afterlives of Data follows the curious and multiple lives that our data live once they escape our control. Mary F. E. Ebeling's ethnographic investigation shows how information about our health and the debt that we carry becomes biopolitical assets owned by healthcare providers, insurers, commercial data brokers, credit reporting companies, and platforms. By delving into the oceans of data built from everyday medical and debt traumas, Ebeling reveals how data about our lives come to affect our bodies and our life chances and to wholly define us. Investigations into secretive data collection and breaches of privacy by the likes of Cambridge Analytica have piqued concerns among many Americans about exactly what is being done with their data. From credit bureaus and consumer data brokers like Equifax and Experian to the secretive military contractor Palantir, this massive industry has little regulatory oversight for health data and works to actively obscure how it profits from our data. In this book, Ebeling traces the health data—medical information extracted from patients' bodies—that are digitized and repackaged into new data commodities that have afterlives in database lakes and oceans, algorithms, ... Unknown localization key: "more"

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The Health Care Data Guide - Lloyd P. Provost, Sandra K. Murray

An Essential text on transforming raw data into concrete health care improvements Now in its second edition, The Health Care Data Guide: Learning from Data for Improvement delivers a practical blueprint for using available data to improve healthcare outcomes. In the book, a team of distinguished authors explores how health care practitioners, researchers, and other professionals can confidently plan and implement health care enhancements and changes, all while ensuring those changes actually constitute an improvement. This book is the perfect companion resource to The Improvement Guide: A Practical Approach to Enhancing Organizational Peformance, Second Edition, and offers fulsome discussions of how to use data to test, adapt, implement, and scale positive organizational change. The Health Care Data Guide: Learning from Data for Improvement, Second Edition provides: Easy to use strategies for learning more readily from existing health care data Clear guidance on the most useful graph for different types of data used in health care A step-by-step method for making use of highly aggregated data for improvement Examples of using patient-level data in care Multiple methods for making use of patient and other feedback data A vastly better way to view data for executive leadership Solutions for working with rare ... Unknown localization key: "more"

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Thinking Clearly with Data - Anthony Fowler, Ethan Bueno de Mesquita

An engaging introduction to data science that emphasizes critical thinking over statistical techniquesAn introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives. Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel. Above all ... Unknown localization key: "more"

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Data-Driven Decisions - Amy Stubbing

Data-Driven Decisions: A Practical Toolkit for Library and Information Professionals is a simple, jargon-free guide to using data for decision making in library services. The book walks readers step-by-step through each stage of implementing, reviewing and embedding data-driven decisions in their organisation, providing accessible visualisations, top tips, and downloadable tools to support readers on their data journey. Starting with the absolute basics of using data, the author creates a framework for building skills and knowledge slowly until the reader is comfortable with even complex uses of data. The book begins with an exploration of the foundations of data-driven decisions in libraries including a look at the impact of the current financial climate on resources, theoretical foundations of data collection and analysis, and how this book can be used in practice. The next section takes readers through the data-driven decisions model, providing a guide for understanding and a manual for implementation of the model. Finally, the book provides further perspectives and reading surrounding analysis and implementation of data-driven decisions. This section aims to give supplementary and focused information on different areas of data-driven decisions which can be included in processes once the reader understands the foundation of the book from earlier ... Unknown localization key: "more"

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Storytelling with Data - Cole Nussbaumer Knaflic

International bestseller with over half a million copies sold! Celebrate a decade of data storytelling with this special 10th anniversary edition of Storytelling with Data. Featuring refreshed visuals, expanded content, and new insights, this collector's edition builds on the classic's foundational lessons, empowering you to craft persuasive data stories. Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audienceDetermine the appropriate type of graph for your situationRecognize and eliminate the clutter clouding your informationDirect your ... Unknown localization key: "more"

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Foundations of Data Science with Python - John M. Shea

Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality.This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a ... Unknown localization key: "more"

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A General Introduction to Data Analytics - Tomáš Horváth, Andre Carvalho, Joao Moreira

A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniquesA unique illustrative example that extends throughout all the chaptersExercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in ... Unknown localization key: "more"

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Data-First Marketing - Janet Driscoll Miller, Julia Lim

Supercharge your marketing strategy with data analytics In Data-First Marketing: How to Compete & Win in the Age of Analytics, distinguished authors Miller and Lim demystify the application of data analytics to marketing in any size business. Digital transformation has created a widening gap between what the CEO and business expect marketing to do and what the CMO and the marketing organization actually deliver. The key to unlocking the true value of marketing is data – from actual buyer behavior to targeting info on social media platforms to marketing’s own campaign metrics. Data is the next big battlefield for not just marketers, but also for the business because the judicious application of data analytics will create competitive advantage in the Age of Analytics. Miller and Lim show marketers where to start by leveraging their decades of experience to lay out a step-by-step process to help businesses transform into data-first marketing organizations. The book includes a self-assessment which will help to place your organization on the Data-First Marketing Maturity Model and serve as a guide for which steps you might need to focus on to complete your own transformation. Data-First Marketing: How to Compete & Win in the Age of Analytics ... Unknown localization key: "more"

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An Introduction to Secondary Data Analysis with IBM SPSS Statistics - John MacInnes

Many professional, high-quality surveys collect data on people′s behaviour, experiences, lifestyles and attitudes. The data they produce is more accessible than ever before. This book provides students with a comprehensive introduction to using this data, as well as transactional data and big data sources, in their own research projects. Here you will find all you need to know about locating, accessing, preparing and analysing secondary data, along with step-by-step instructions for using IBM SPSS Statistics. You will learn how to: Create a robust research question and design that suits secondary analysis Locate, access and explore data online Understand data documentation Check and ′clean′ secondary data Manage and analyse your data to produce meaningful results Replicate analyses of data in published articles and books Using case studies and video animations to illustrate each step of your research, this book provides you with the quantitative analysis skills you′ll need to pass your course, complete your research project and compete in the job market. Exercises throughout the book and on the book′s companion website give you an opportunity to practice, check your understanding and work hands on with real data as you′re learning.

Objev podobné jako An Introduction to Secondary Data Analysis with IBM SPSS Statistics - John MacInnes

Data-Oriented Programming - Yehonathan Sharvit

Eliminate the unavoidable complexity of object-oriented designs. Using the persistent data structures built into most modern programming languages, Data-oriented programming cleanly separates code and data, which simplifies state management and eases concurrency. In Data-Oriented Programming you will learn how to: Separate code from data Effectively manage state using immutable data Represent data with generic data structures Manipulate data with general-purpose functions Control concurrency in highly scalable systems Specify the shape of your data Benefit from polymorphism without objects Debug programs without a debugger Distinguish data-oriented programming from functional and OO programming Data-Oriented Programming teaches you to design applications using the data-oriented paradigm. These powerful new ideas are presented through conversations, code snippets, diagrams, and even songs to help you quickly grok what''s great about DOP. You''ll learn to write DOP code that can be implemented in languages like JavaScript, Ruby, Python, Clojure and also in traditional OO languages like Java or C#.

Objev podobné jako Data-Oriented Programming - Yehonathan Sharvit

Driving Data Projects - Christine Haskell

Digital transformation and data projects are not new and yet, for many, they are a challenge. Driving Data Projects is a compelling guide that empowers data teams and professionals to navigate the complexities of data projects, fostering a more data-informed culture within their organizations.With practical insights and step-by-step methodologies, this guide provides a clear path how to drive data projects effectively in any organization, regardless of its sector or maturity level whilst also demonstrating how to overcome the overwhelming feelings of where to start and how to not lose momentum. This book offers the keys to identifying opportunities for driving data projects and how to overcome challenges to drive successful data initiatives.Driving Data Projects is highly practical and provides reflections, worksheets, checklists, activities, and tools making it accessible to students new to driving data projects and culture change. This book is also a must-have guide for data teams and professionals committed to unleashing the transformative power of data in their organizations.

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Data Mesh - Pradeep Menon

"Data Mesh: Principles, patterns, architecture, and strategies for data-driven decision making" introduces Data Mesh which is a macro data architecture pattern designed to harmonize governance with flexibility. This book guides readers through the nuances of Data Mesh topologies, explaining how they can be tailored to meet specific organizational needs while balancing central control with domain-specific autonomy. The book delves into the Data Mesh governance framework, which provides a structured approach to manage and control decentralized data assets effectively. It emphasizes the importance of a well-implemented governance structure that ensures data quality, compliance, and access control across various domains. Additionally, the book outlines robust data cataloging and sharing strategies, enabling organizations to improve data discoverability, usage, and interoperability between cross-functional teams. Securing Data Mesh architectures is another critical focus. The text explores comprehensive security strategies that protect data across different layers of the architecture, ensuring data integrity and protecting against breaches.

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Collect, Combine, and Transform Data Using Power Query in Power BI and Excel - Daniil Maslyuk, Gil Raviv

Transform your data analysis experience with Power Query, the ultimate tool for importing, reshaping, and cleansing data through a user-friendly interface. Whether you’re using Power BI, Excel, or other Microsoft products, Power Query’s capabilities are at your fingertips. Renowned Power Query experts Daniil Maslyuk and Gil Raviv guide you through mastering this indispensable tool, helping you eliminate tedious manual data preparation, tackle common issues, and avoid potential pitfalls. In this updated edition, you’ll delve into comprehensive analytics challenges, seamlessly integrating your skills into a realistic, final project. By the end, you’ll possess the expertise to handle any data and convert it into actionable insights. You will learn how to: Effortlessly prepare data by utilizing Power Query in Power BI and Excel to transform your data quickly and efficiently Overcome common data preparation problems with intuitive mouse clicks and straightforward formula edits Combine data from various sources, multiple queries, and mismatched tables with ease Reshape tables to suit your analysis needs Use the Power Query M formula language to create flexible data mashups and tailor transformations to your requirements Address and overcome collaboration challenges by using Power Query’s powerful features Gain crucial insights from text feeds by enhancing your data analysis ... Unknown localization key: "more"

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The Data Science Handbook - Field Cady

Practical, accessible guide to becoming a data scientist, updated to include the latest advances in data science and related fields. Becoming a data scientist is hard. The job focuses on mathematical tools, but also demands fluency with software engineering, understanding of a business situation, and deep understanding of the data itself. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. The focus of The Data Science Handbook is on practical applications and the ability to solve real problems, rather than theoretical formalisms that are rarely needed in practice. Among its key points are: An emphasis on software engineering and coding skills, which play a significant role in most real data science problems. Extensive sample code, detailed discussions of important libraries, and a solid grounding in core concepts from computer science (computer architecture, runtime complexity, and programming paradigms). A broad overview of important mathematical tools, including classical techniques in statistics, stochastic modeling, regression, numerical optimization, and more. Extensive tips about the practical realities of working as a data scientist, including understanding related jobs functions, project life cycles, and the varying roles of data science in an organization. Exactly the right amount of ... Unknown localization key: "more"

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The Data Hero Playbook - Malcolm Hawker

For thirty years, “best practices” in data have delivered bigger platforms, thicker slide decks, and disappointing outcomes. The problem isn’t technology. It’s mindset. The Data Hero Playbook reveals how limiting beliefs—learned helplessness, all-or-nothing thinking, externalized blame—have kept data from becoming truly transformational. The cure is a growth mindset, put into action through practical steps any data professional can take. You’ll discover how to: Put customers at the center of every decision. Apply product management principles to data work. Quantify value in revenue, cost savings, and risk reduction. Run data as if it were a P&L. Deliver fast wins with a Data Strategy MVP in weeks, not months. Unflinching about what hasn’t worked yet unapologetically hopeful about what’s next, this book is a call to arms for data leaders ready to escape the status quo. If you want to stop explaining why data should matter and start proving it with measurable results, The Data Hero Playbook is your guide. Become the data hero your company actually needs.

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Data for All - John K. Thompson

Gain in-depth knowledge about how companies manipulate and exploit personal data. A book that does not require particular technical knowledge – just mere curiosity to explore the subject. From tech experts to the general public, Data for All is the ground-breaking guide to help with the ways third parties use personal data. Written by bestselling author John K Thompson, this edition will aid your understanding of areas, such as The types of data you generate with every action, every day Where your data is stored, who controls it, and how much money they make from it How you can manage access and monetisation of your own data Restricting data access to only companies and organisations you want to support The history of how we think about data, and why that is changing The new data ecosystem is being built right now for your benefit About the technology For years, companies have had free rein to use every click, purchase, and “like” you make, to earn money. Now, across the globe, new laws have been written, passed, and are coming into force, giving individuals the right to access, delete, and monetise their own data. This book provides a vision of how ... Unknown localization key: "more"

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Making Data

For many outside of the scientific community, big data and the forms it takes, such as statistical lists, spreadsheets and graphs, often seem abstract and unintelligible. This book investigates how digital fabrication and traditional making approaches are being used to present data in newly engaging and interesting ways.The first part of the book introduces the basic premise of the data object and the concept of making digital data into a physical form. Contributors cover topics such as biometrics, new technology, the economics of data and open and community uses of data. The second part presents a selection of exemplar forms and contexts for the application of data-objects, such as smart surfaces, smart cities, augmented reality techniques and next generation technical interfaces that blend physical and digital elements.Making Data delivers the importance and likely future prevalence of physical representations of data. It explores the creative methods, processes, theories and cultural histories of making physical representations of information and proposes that the making of data into physical objects is the next important development in the data visualisation phenomenon.

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