Datafangst og dataanalyse

In today's data-driven world, understanding statistical models is crucial for effective analysis and decision making. Whether you're a beginner or an experienced user, this book equips you with the foundational knowledge to grasp and implement statistical models within Tableau. Gain the confidence to speak fluently about the models you employ, driving adoption of your insights and analysis across your organization. As AI continues to revolutionize industries, possessing the skills to leverage statistical models is no longer optional--it's a necessity. Stay ahead of the curve and harness the full potential of your data by mastering the ability to interpret and utilize the insights generated by these models. Whether you're a data enthusiast, analyst, or business professional, this book empowers you to navigate the ever-evolving landscape of data analytics with confidence and proficiency. Start your journey toward data mastery today. In this book, you will learn: The basics of foundational statistical modeling with Tableau How to prove your analysis is statistically significant How to calculate and interpret confidence intervals Best practices for incorporating statistics into data visualizations How to connect external analytics resources from Tableau using R and Python

Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guideKey FeaturesInstall, set up, and configure Grafana for real-time data analysis, visualization, and alertingVisualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and ElasticsearchExplore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud MonitoringPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana's latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored.Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You'll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you'll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you'll have gained all the knowledge you need to start building interactive dashboards.What you will learnLearn the techniques of data visualization using GrafanaGet familiar with the major components of Time series visualizationExplore data transformation operations, query inspector, and time interval settingsWork with advanced dashboard features, such as annotations, variable-based templating, and dashboard linking and sharingConnect user authentication through Okta, Google, GitHub, and other external providersDiscover Grafana's monitoring support for cloud service infrastructuresWho this book is forThis book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. You'll also find this book useful if you're looking to create and share interactive dashboards or get up to speed with the latest features of Grafana. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some Python programming experience will help you understand the concepts covered in the book.Table of ContentsIntroducing Data Visualization with GrafanaTouring the Grafana InterfaceDiving into Grafana's Time Series VisualizationConnecting Grafana to a Prometheus Data SourceExtracting and Visualizing Data with InfluxDB and GrafanaShaping Data with Grafana TransformationsSurveying Key Grafana VisualizationsSurveying Additional Grafana VisualizationsCreating Insightful DashboardsWorking with Advanced Dashboard Features and Elasticsearch(N.B. Please use the Look Inside option to see further chapters)

Information Modeling and Relational Databases provides an introduction to ORM (Object Role Modeling)-and much more. In fact, it's the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. Inside, ORM authority Terry Halpin blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives.The most in-depth coverage of Object Role Modeling available anywhere-written by a pioneer in the development of ORM.Provides additional coverage of Entity Relationship (ER) modeling and the Unified Modeling Language-all from an ORM perspective.Intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, instructors, managers, and programmers.Explains and illustrates required concepts from mathematics and set theory.

The Importance of Data in Health CareIn the world of health care, data plays a crucial role in ensuring the delivery of efficient and effective services. From patient records to clinical trials, numerical data is invaluable in shaping policies, making informed decisions, and improving health outcomes. As students embarking on a journey in data analysis within the health care field, understanding the importance of data is essential.One of the primary uses of numerical data in health care is in patient care. By collecting and analyzing data on patients' medical history, symptoms, and treatment plans, healthcare professionals can gain insights into patterns and trends. This information enables them to make accurate diagnoses, develop personalized treatment plans, and monitor the progress of patients over time. Moreover, data analysis helps identify risk factors and predict potential health issues, allowing for proactive interventions and preventive measures.Another critical aspect of data in health care is research and development. Clinical trials and studies collect vast amounts of numerical data to test the efficacy and safety of new treatments, medications, and medical devices. This data is analyzed to determine the effectiveness of interventions, identify side effects, and provide evidence for regulatory approvals. Through rigorous data analysis, researchers can contribute to medical advancements, shaping the future of health care.Furthermore, data plays a crucial role in health care management. Administrators and policymakers rely on data to evaluate the performance of healthcare facilities, identify areas for improvement, and allocate resources effectively. By analyzing data on patient satisfaction, wait times, and cost-effectiveness, administrators can enhance the quality of care, streamline operations, and optimize resource allocation. This not only ensures better patient outcomes but also contributes to the overall sustainability of the health care system.

Text mining has emerged as one of the most important data processing activities over the last few decades. While it makes the life of millions of everyday users of digital plat- forms and applications much easier, it is a domain that also challenges researchers in numerous ways. The challenges are many fold - ranging from the volume of the data that needs to be processed, storage issues, language identi¿cation challenges and many more. The work in this thesis focuses on one particular aspect of text mining e.g. Key- word identi¿cation for a document. While this may seem to be quite a trivial activity for short passages, it is quite dif¿cult to successfully identify keywords for extremely long text documents. Doing so using an automated systems only adds to the challenge. Everyone in today's world understands the importance of data. In the context of business, data is used to analyze market trends or can be used to understand customer needs. It also helps to understand the user's perspectives and choices. There are var-ious ways that data plays a crucial role in our everyday lives. Most businesses would be bound to fail if they could not comprehend the data that was available. This data could vary from stock indices, to customer feedback, to worker sentiments and numerous other insights. Analyzing data also helps in advertisement noti¿cations or to suggest a piece of relevant information to the user. It also helps to understand the likes and dislikes of a user. It can make for a world with a better user experience in terms of an individuals needs, e.g., if a user is more interested in cricket, we can provide targeted insight to the user about cricket. A customized user experience for a user is more at- tractive than a bland user experience which is homogeneous for everyone. Everyone's needs are different from others as everyone has different perspectives and opinions. We offered examples of keyword extraction, the challenges involved and the major issues faced by designers of keyword extraction algorithms. Finally about some common application areas where keyword extraction is being used in real life scenarios. Attracting users and providing them with better services through relevant data also helps the system to understand the users' needs. A user consciously or unknowingly provides his information for use in business or expresses his views on various platforms. If a user expresses some political opinions, it helps us to tailor his experience better the next time he uses the system.

The general format of this book is I'll start with each concept, explaining it in a bunch of sections and graphical examples. I will introduce you to some of the notations and fancy terminologies that data scientists like to use so you can talk the same language, but the concepts themselves are generally pretty simple. After that, I'll throw you into some actual Python code that actually works that we can run and mess around with, and that will show you how to actually apply these ideas to actual data.

Master the art of machine learning by using the one-of-a-kind Qlik platform, and take your data analytics skills to the next levelKey FeaturesGain a solid understanding of machine learning concepts and learn to effectively define a problemExplore the application of machine learning principles within the Qlik platformApply your knowledge of ML to real-world scenarios with the help of practical examplesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe ability to forecast future trends through data prediction, coupled with the integration of ML and AI, has become indispensable to global enterprises. Qlik, with its extensive machine learning capabilities, stands out as a leading analytics platform enabling businesses to achieve exhaustive comprehension of their data. This book helps you maximize these capabilities by using hands-on illustrations to improve your ability to make data-driven decisions.You'll begin by cultivating an understanding of machine learning concepts and algorithms, and build a foundation that paves the way for subsequent chapters. The book then helps you navigate through the process of framing machine learning challenges and validating model performance. Through the lens of Qlik Sense, you'll explore data preprocessing and analysis techniques, as well as find out how to translate these techniques into pragmatic machine learning solutions. The concluding chapters will help you get to grips with advanced data visualization methods to facilitate a clearer presentation of findings, complemented by an array of real-world instances to bolster your skillset.By the end of this book, you'll have mastered the art of machine learning using Qlik tools and be able to take your data analytics journey to new heights.What you will learnFind out how to build practical machine learning solutions with the Qlik platformDevelop the skills needed to generate and verify machine learning models using the Qlik platformDiscover techniques used for preparing and investigating data to craft machine learning solutionsUnderstand how to transform real-world business problems into machine learning modelsExpand your potential to new use cases with data analyticsExplore advanced visualization techniques to make your models come aliveWho this book is forIf you're interested in data and analytics and are looking to extend your skillset to machine learning, this book is for you. Basic working knowledge of data, preferably with Qlik tools, will help you get started with this book. This is an excellent guide for anyone who wants to start using machine learning as part of their data analytics journey.Table of ContentsIntroduction to Machine Learning with QlikMachine Learning Algorithms and Models with QlikData Literacy in Machine Learning ContextCreating a Good Machine Learning Solution with the Qlik PlatformSetting Up the EnvironmentsPreprocessing and Exploring Data with Qlik SenseDeploying and Monitoring Machine Learning ModelsUtilizing Qlik AutoMLAdvanced Data Visualisation Techniques for Machine Learning SolutionsExamples and Case StudiesFuture Direction

When you enter the world of time series analysis, you step into a labyrinth of numerical patterns, where each turn you take unveils another layer of complexity. Here, simple mathematical or statistical models struggle to keep pace.Reality is riddled with complex patterns in time series data, which, like cryptic pieces of a jigsaw puzzle, hold the key to unraveling insightful predictions. These complex patterns include non-linearity, non-stationarity, long memory or dependence, asymmetry, and stochasticity.But what creates these intricate patterns? Raghurami Reddy Etukuru, Ph.D., a distinguished and adaptable specialist in data science and artificial intelligence, delves into that question in this groundbreaking book, explaining that the factors are numerous and multifaceted, each adding their own measure of challenge. He doesn't just discuss problems but also addresses the forecasting of time series amidst intricate patterns.Take a deep dive deep into the world of numbers and patterns, so you can unravel complexities and leverage the power of artificial intelligence to enhance predictive capabilities. More than just a theoretical guide, this book is a practical companion in the often-turbulent journey of understanding and predicting complex time series data.

Through the application of cutting-edge techniques like Big Data, Data Mining, and Data Science, it is possible to extract insights from massive datasets. These methodologies are crucial in enabling informed decision-making and driving transformative advancements across many fields, industries, and domains. This book offers an overview of latest tools, methods and approaches while also highlighting their practical use through various applications and case studies.

Une bible magistrale sur SASCe livre présente le socle de connaissances communes à tous les utilisateurs de SAS, le progiciel d'informatique décisionnelle le plus utilisé au monde. Il traite tout particulièrement des fonctionnalités de Base SAS, module au c1/2ur du système SAS. Pédagogique et complet, il peut servir aussi bien de guide d'initiation pour les utilisateurs débutants que d'ouvrage de référence pour les plus expérimentés, et concerne aussi bien les utilisateurs de SAS Foundation que ceux de SAS Enterprise Guide, SAS Studio et SAS University Edition.Cet ouvrage couvre les programmes des certifications SAS Certified Specialist: Base Programming Using SAS 9.4 et Advanced Programming for SAS 9.Parmi les sujets développés: la création, la manipulation et la gestion des tables de données;les procédures d'exploration des données: construction de tableaux, de rapports, de graphiques au moyen des procédures ODS Graphics;la production de documents au format HTML, PowerPoint, RTF, XLSX ou PDF avec ODS;la procédure PROC SQL et le langage SQL de SAS;le langage macro spécifique à SAS.Pour vous aider à bien assimiler tous les concepts, le livre comprend près de 500 programmes d'exemples, plus de 150 exercices et des liens vers une centaine d'articles en ligne.Une 4e édition mise à jour et augmentéeEnrichie de plus d'une centaine de pages, cette nouvelle édition propose des mises à jour importantes sur: les passerelles entre SAS et Excel;l'optimisation des ressources;la production de graphiques au moyen de PROC SGPLOT et PROC SGPANEL;la création et gestion de vos tables au moyen de PROC SQL.Le livre, qui porte essentiellement sur la version 9.4 de SAS, est également compatible avec les versions 9.2 et 9.3.Ce livre a le soutien de SAS France.À qui s'adresse cet ouvrage ?Aux professionnels souhaitant découvrir ou approfondir leurs connaissances de la programmation SASAux étudiants qui débutent avec SAS ou qui souhaitent préparer les examens de certification SAS Cert

Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on recent, up-to-date technologies, combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

This report explores how machine learning can be leveraged to enable military decisionmaking at the operational level of competition and conflict as a collaboration between machine learning tools and human analysts.

Smart Spaces covers the latest concepts and technologies surrounding smart spaces, providing technical personnel engaged in smart space related research and industries a more in-depth understanding of smart spaces. This book can be used as a reference for practicing this emerging discipline, but it will also be useful for researchers, scientists, developers, practitioners, and graduate students working in the fields of smart spaces and artificial intelligence. It combines the study of working or living spaces with computing, information equipment, and multimodal sensing devices, and with natural and convenient interactive interfaces to support how people can easily obtain services from computer systems. People's work and life in smart spaces use computer systems; it is a process of uninterrupted interaction between people and the computer system. In this process, the computer is no longer just an information processing tool that passively executes explicit human operation commands but a collaborator with people to complete tasks - a partner to human beings. International research on smart spaces is quite extensive, which shows the important role of smart spaces in ubiquitous computing research.

Identify data quality issues, leverage real-world examples and templates to drive change, and unlock the benefits of improved data in processes and decision-makingKey Features:Get a practical explanation of data quality concepts and the imperative for change when data is poorGain insights into linking business objectives and data to drive the right data quality prioritiesExplore the data quality lifecycle and accelerate improvement with the help of real-world examplesPurchase of the print or Kindle book includes a free PDF eBookBook Description:Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating.Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you'll work with real-world examples and utilize re-usable templates to accelerate your initiatives.By the end of this book, you'll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.What You Will Learn:Explore data quality and see how it fits within a data management programmeDifferentiate your organization from its peers through data quality improvementCreate a business case and get support for your data quality initiativeFind out how business strategy can be linked to processes, analytics, and data to derive only the most important data quality rulesMonitor data through engaging, business-friendly data quality dashboardsIntegrate data quality into everyday business activities to help achieve goalsAvoid common mistakes when implementing data quality practicesWho this book is for:This book is for data analysts, data engineers, and chief data officers looking to understand data quality practices and their implementation in their organization. This book will also be helpful for business leaders who see data adversely affecting their success and data teams that want to optimize their data quality approach. No prior knowledge of data quality basics is required.

Your life online is their product.In the past, colonialism was a landgrab of natural resources, exploitative labour and private property from countries around the world. It promised to modernise and civilise, but actually sought to control. It stole from native populations and made them sign contracts they didn't understand. It took resources just because they were there.Colonialism has not disappeared - it has taken on a new form.In the new world order, data is the new oil. Big Tech companies are grabbing our most basic natural resources - our data - exploiting our labour and connections, and repackaging our information to control our views, track our movements, record our conversations and discriminate against us. Every time we unthinkingly click 'Accept' on Terms and Conditions, we allow our most personal information to kept indefinitely, repackaged by big Tech companies to control and exploit us for their own profit.In this searing, cutting-edge guide, two leading global researchers - and founders of the concept of data colonialism - reveal how history can help us both to understand the emerging future and to fight back.

Prior to the events of February 2022, political interference was one of the most significant challenges in Russia-West relations. These proceedings reflect a series of discussions among U.S., Russian, and European Union nongovernmental experts who were convened in 2020-2021 to discuss mutual concerns regarding political interference and to find common ground on measures to address them. Even before February 2022, the European Union, the United States, and Russia had divergent interests, values, and worldviews, as well as significant mutual grievances. Despite these divergences and grievances, the assembled experts came to the view that all parties would have benefited from the establishment of mutually agreed-upon measures to mitigate the destabilizing impacts of political interference. In a text agreed on in January 2022, the expert group proposed the following measures: (1) increase transparency regarding interpretations of prohibited interference, (2) enhance dialogue on interference, (3) establish self-restraint commitments (regarding election-related infrastructure and hack-and-leak operations), (4) develop technical measures to demonstrate compliance with self-restraint commitments, (5) create guidelines to limit cross-border manipulation of social media, (6) relax restrictions on foreign broadcasters, and (7) formulate declarations of intent not to interfere.

Work through practical examples to unlock the full potential of web scraping with Python and gain valuable insights from high-quality dataKey Features:Build an initial portfolio of web scraping projects with detailed explanationsGrasp Python programming fundamentals related to web scraping and data extractionAcquire skills to code web scrapers, store data in desired formats, and employ the data professionallyPurchase of the print or Kindle book includes a free PDF eBookBook Description:Web scraping is a powerful tool for extracting data from the web, but it can be daunting for those without a technical background. Designed for novices, this book will help you grasp the fundamentals of web scraping and Python programming, even if you have no prior experience.Adopting a practical, hands-on approach, this updated edition of Hands-On Web Scraping with Python uses real-world examples and exercises to explain key concepts. Starting with an introduction to web scraping fundamentals and Python programming, you'll cover a range of scraping techniques, including requests, lxml, pyquery, Scrapy, and Beautiful Soup. You'll also get to grips with advanced topics such as secure web handling, web APIs, Selenium for web scraping, PDF extraction, regex, data analysis, EDA reports, visualization, and machine learning.This book emphasizes the importance of learning by doing. Each chapter integrates examples that demonstrate practical techniques and related skills. By the end of this book, you'll be equipped with the skills to extract data from websites, a solid understanding of web scraping and Python programming, and the confidence to use these skills in your projects for analysis, visualization, and information discovery.What You Will Learn:Master web scraping techniques to extract data from real-world websitesImplement popular web scraping libraries such as requests, lxml, Scrapy, and pyqueryDevelop advanced skills in web scraping, APIs, PDF extraction, regex, and machine learningAnalyze and visualize data with Pandas and PlotlyDevelop a practical portfolio to demonstrate your web scraping skillsUnderstand best practices and ethical concerns in web scraping and data extractionWho this book is for:This book is for beginners who want to learn web scraping and data extraction using Python. No prior programming knowledge is required, but a basic understanding of web-related concepts such as websites, browsers, and HTML is assumed. If you enjoy learning by doing and want to build a portfolio of web scraping projects and delve into data-related studies and application, then this book is tailored for your needs.

Build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and KafkaKey Features:Develop modern data skills used in emerging technologiesLearn pragmatic design methodologies such as Data Mesh and data lakehousesGain a deeper understanding of data governancePurchase of the print or Kindle book includes a free PDF eBookBook Description:Modern Data Architectures with Python will teach you how to seamlessly incorporate your machine learning and data science work streams into your open data platforms. You'll learn how to take your data and create open lakehouses that work with any technology using tried-and-true techniques, including the medallion architecture and Delta Lake.Starting with the fundamentals, this book will help you build pipelines on Databricks, an open data platform, using SQL and Python. You'll gain an understanding of notebooks and applications written in Python using standard software engineering tools such as git, pre-commit, Jenkins, and Github. Next, you'll delve into streaming and batch-based data processing using Apache Spark and Confluent Kafka. As you advance, you'll learn how to deploy your resources using infrastructure as code and how to automate your workflows and code development. Since any data platform's ability to handle and work with AI and ML is a vital component, you'll also explore the basics of ML and how to work with modern MLOps tooling. Finally, you'll get hands-on experience with Apache Spark, one of the key data technologies in today's market.By the end of this book, you'll have amassed a wealth of practical and theoretical knowledge to build, manage, orchestrate, and architect your data ecosystems.What You Will Learn:Understand data patterns including delta architectureDiscover how to increase performance with Spark internalsFind out how to design critical data diagramsExplore MLOps with tools such as AutoML and MLflowGet to grips with building data products in a data meshDiscover data governance and build confidence in your dataIntroduce data visualizations and dashboards into your data practiceWho this book is for:This book is for developers, analytics engineers, and managers looking to further develop a data ecosystem within their organization. While they're not prerequisites, basic knowledge of Python and prior experience with data will help you to read and follow along with the examples.

Ethics in Online AI-Based Systems: Risks and Opportunities in Current Technological Trends creates a space to explore the ethical relevance that new technologies under development may have. Stimulating reflection and considerations with respect to the design, deployment, and use of technology helps readers guide current and future technological advancements from an ethically informed position to ensure that such advancements contribute towards solving current global and social challenges that we, as a society, have today. This will not only be useful for researchers and professional engineers, but also for educators, policy makers, and ethicists. Recent technological advancements have deeply transformed society and the way people interact with each other. Instantaneous communication platforms have allowed connections with other people, forming global communities and creating unprecedented opportunities in many sectors, making access to online resources more ubiquitous by reducing limitations imposed by geographical distance and temporal constrains. These technological developments bear ethically relevant consequences with their deployment, and legislations often lag behind such advancements. Because the appearance and deployment of these technologies happen much faster than legislative procedures, the way these technologies affect social interactions have profound ethical effects before any legislative regulation can be built in order to prevent and mitigate those effects.

Dive into the world of cutting-edge data science with this captivating and comprehensive guide. Unveil the power of data analysis and interpretation as you embark on a journey through the realm of Julia programming. Whether you're a seasoned data enthusiast or a curious newcomer, this book is your ultimate companion to mastering the art of extracting insights from complex datasets.Inside these pages, you'll discover a treasure trove of techniques that unlock the true potential of data. From foundational concepts to advanced methodologies, the author expertly navigates through the intricacies of Julia, leading you towards data-driven discoveries. With a focus on practicality, each chapter seamlessly blends theory with real-world applications, making learning an exhilarating and fruitful experience.Breathe life into your analytical prowess as you explore essential topics such as machine learning, statistical modeling, and data visualization. Through hands-on examples and engaging exercises, you'll effortlessly grasp complex ideas, transforming them into tangible results. Harness the potential of Julia's high-performance capabilities and harness the insights hidden within your data like never before.What sets this book apart is its unparalleled dedication to demystifying the data science landscape. You'll uncover a holistic approach that not only hones your technical skills but also nurtures your creative problem-solving abilities. As you progress, you'll find yourself seamlessly transitioning from a reader to a practitioner, equipped with the confidence to tackle real-world challenges head-on.Whether you're a data scientist, analyst, researcher, or simply someone intrigued by the world of data, this book promises to be your beacon of knowledge. Let your curiosity guide you as you embark on an enlightening adventure through the art and science of data analysis. Are you ready to revolutionize your understanding of data? Your journey starts here.

Find all the information, exercises, and tools to ace the Splunk Enterprise Certified Admin exam in one place Key Features:Explore various administration topics including installation, configuration, and user managementGain a deep understanding of data inputs, parsing, and field extractionExcel in the Splunk Enterprise Admin exam with the help of self-assessment questions and mock examsPurchase of the print or Kindle book includes a free PDF eBookBook Description:The IT sector's appetite for Splunk and skilled Splunk developers continues to surge, offering more opportunities for developers with each passing decade. If you want to enhance your career as a Splunk Enterprise administrator, then Splunk 9.x Enterprise Certified Admin Guide will not only aid you in excelling on your exam but also pave the way for a successful career.You'll begin with an overview of Splunk Enterprise, including installation, license management, user management, and forwarder management. Additionally, you'll delve into indexes management, including the creation and management of indexes used to store data in Splunk. You'll also uncover config files, which are used to configure various settings and components in Splunk.As you advance, you'll explore data administration, including data inputs, which are used to collect data from various sources, such as log files, network protocols (TCP/UDP), APIs, and agentless inputs (HEC).You'll also discover search-time and index-time field extraction, used to create reports and visualizations, and help make the data in Splunk more searchable and accessible. The self-assessment questions and answers at the end of each chapter will help you gauge your understanding.By the end of this book, you'll be well versed in all the topics required to pass the Splunk Enterprise Admin exam and use Splunk features effectively.What You Will Learn:Explore Splunk Enterprise 9.x features and usageInstall, configure, and manage licenses and users for SplunkCreate and manage indexes for data storageExplore Splunk configuration files, their precedence, and troubleshootingManage forwarders and source data into Splunk from various resourcesParse and transform data to make it easy to useExtract fields from data at search and index time for data analysisEngage with mock exam questions to simulate the Splunk admin examWho this book is for:This book is for data professionals looking to gain certified Splunk administrator credentials. It will also help data analysts, Splunk users, IT experts, security analysts, and system administrators seeking to explore the Splunk admin realm, understand its functionalities, and become proficient in effectively administering Splunk Enterprise. This guide serves as both a valuable resource for learning and a practical manual for administering Splunk Enterprise, encompassing features beyond the scope of certification preparation.

Build, design, and improve advanced business intelligence solutions using Tableau's newest updates, including new Tableau Desktop, Tableau Prep, and Tableau Server featuresPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesMaster new Tableau 2023 features to solve real-world analytics challengesLearn how to use both pre-defined and your own Machine Learning models in TableauHow to manage Data Governance and secure high data qualityBook DescriptionThis edition of the bestselling Tableau guide will teach you how to leverage Tableau's newest features and offerings in various paradigms of the BI domain. Updated with fresh topics, including the newest features in Tableau Server,Prep, and Desktop, as well as up-to-date examples, this book will take you from mastering essential Tableau concepts to advance functionalities. A chapter on data governance has also been added.Throughout this book, you'll learn how to use Tableau Hyper files and Prep Builder to easily perform data preparation and handling, as well as complex joins, spatial joins, unions, and data blending tasks using practical examples. You'll also get to grips with executing data densification and explore other expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions.Later chapters will teach you all about improving dashboard performance, connecting to Tableau Server, and understanding data visualization with examples. Finally, you'll cover advanced use cases, such as self-service analysis, time series analysis, geo-spatial analysis, and how to connect Tableau to Python and R to implement programming functionalities within Tableau.By the end of this book, you'll have mastered Tableau 2023 and be able to tackle common and advanced challenges in the BI domain.What you will learnLearn about various Tableau components, such as calculated fields, table calculations, and LOD expressionsMaster ETL (Extract, Transform, Load) techniques using Tableau Prep BuilderExplore and implement data storytelling with Python and RUnderstand Tableau Exchange by using accelerators, extensions, and connectorsInteract with Tableau Server to understand its functionalitiesStudy advanced visualizations and dashboard creation techniquesBrush up on powerful self-service analytics, time series analytics, and geo-spatial analyticsFind out why data governance matters and how to implement itWho this book is forThis book is designed for business analysts, business intelligence professionals, and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. Prior exposure to Tableau will help you get to grips with the features more quickly, but it's not a prerequisite.Table of ContentsReviewing the BasicsGetting Your Data ReadyUsing Tableau Prep BuilderLearning about Joins, Blends, and Data StructuresIntroducing Table CalculationsUtilizing OData, Data Densification, Big Data, and Google BigQueryPracticing Level of Detail CalculationsGoing Beyond the BasicsWorking with MapsPresenting with TableauDesigning Dashboards and Best Practices for VisualizationsLeveraging Advanced AnalyticsImproving PerformanceExploring Tableau Server and Tableau CloudIntegrating Programming LanguagesDeveloping Data Governance Practices

Learn how to use R for everything from workload automation and creating online reports, to interpreting data, map making, and more.Written by the founder of a very popular online training platform for the R programming language!The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate repetitive tasks or visualize your data, without the need for complex math, R for the Rest of Us is for you.Inside you’ll find a crash course in R, a quick tour of the RStudio programming environment, and a collection of real-word applications that you can put to use right away. You’ll learn how to create informative visualizations, streamline report generation, and develop interactive websites—whether you’re a seasoned R user or have never written a line of R code.You’ll also learn how to:• Manipulate, clean, and parse your data with tidyverse packages like dplyr and tidyr to make data science operations more user-friendly• Create stunning and customized plots, graphs, and charts with ggplot2 to effectively communicate your data insights• Import geospatial data and write code to produce visually appealing maps automatically• Generate dynamic reports, presentations, and interactive websites with R Markdown and Quarto that seamlessly integrate code, text, and graphics• Develop custom functions and packages tailored to your specific needs, allowing you to extend R’s functionality and automate complex tasksUnlock a treasure trove of techniques to transform the way you work. With R for the Rest of Us, you’ll discover the power of R to get stuff done. No advanced statistics degree required.

Learn to use ArcGIS Pro confidently, quickly, and effectively with the newest edition in this best-selling series. Getting to Know ArcGIS Pro 3.2 introduces readers to ArcGIS Pro, the world's most powerful desktop GIS. Getting to Know ArcGIS Pro 3.2 walks readers through how to build a geodatabase, discover 3D GIS, create maps for web and physical presentations, and more. With more than 300 full-color images, Getting to Know ArcGIS Pro 3.2 clarifies complicated processes such as developing a geoprocessing model, using Python to write a script tool, and creating space-time cubes for analysis in easy-to-follow workflows. This edition has been completely updated for use with ArcGIS Pro 3.2.Michael Law is a cartographer and GIS professional with more than 16 years of experience. He lives in Toronto, Canada. Amy Collins is a writer and editor who lives in Northern California.

No matter what electronic tools you take into the field, everyone takes a notebook or a guidebook. Along with all your equipment, be sure to include this fieldwork guide.   Fieldwork Handbook gives you tips, best practices, and activities that make your work in the field more productive and successful. No matter how you use location intelligence in the field, you can up your game with this book and improve your experience. Covering preparation, equipment, workflows, and data, this book will show you how to Organize and reconcile field dataEffectively coordinate and dispatch field resourcesRefine fieldwork workflowsSync the office with the fieldThis handbook is your friend in the field.

"This book explores the work of activists in the Americas who are documenting feminicide, arguing that feminist activists at the margins have much to teach mainstream data scientists about data ethics: how to work with data ethically amidst extreme and durable structural inequalities"--