Analiza danych
Google Analytics 4. The Practical Guide
Rheinwerk Publishing, Inc, Markus Vollmert
Master Google Analytics 4 (GA4) with this hands-on guide, starting with account setup, data streams, and Google Tag Manager implementation. The book teaches you to create custom events, track user behavior across websites and apps, and leverage advanced tools like BigQuery and Looker Studio for deeper insights. Throughout, you’ll find practical examples and real-life scenarios that help you apply your learning immediately. It also covers troubleshooting common issues, ensuring data accuracy, and complying with data privacy regulations.Designed for both beginners and experienced users, this book offers step-by-step instructions and expert tips to make the most of GA4’s features. By the end, readers will have the skills to effectively track and analyze data, optimize their digital marketing strategies, and enhance reporting quality for better decision-making. Whether you're a marketer, analyst, or developer, this guide provides the knowledge to harness GA4’s full potential and improve your business's digital presence.
Google Analytics dla marketingowców. Wydanie III
Martyna Zastrożna
Analiza. Podstawa działań online Czasy radosnego internetowego marketingu bazującego na wyszukanych hasłach reklamowych, perfekcyjnie przygotowanych grafikach i sprytnych programach lojalnościowych... cóż, nie minęły. W reklamie nadal liczą się pomysł, wykonanie, myślenie o kliencie. Od kiedy jednak udostępnione zostało narzędzie Google Analytics, na pierwszy plan wysunęło się coś zupełnie innego. Statystyki. Święty Graal działań promocyjnych w sieci. Dzięki narzędziom, jakie nieodpłatnie oferuje Google Analytics, można spojrzeć na witrynę, sklep online, produkty i usługi oferowane za pośrednictwem internetu z zupełnie innej, konkretnej strony. Z uwzględnieniem takich parametrów jak ruch internautów, wskaźniki konwersji i rentowności (ROI) itd., przedstawionych w formie przystępnych raportów. Brzmi niczym podstawa do prowadzenia skutecznych kampanii online? Jak najbardziej. Zatem nie czekaj, tylko zaprzyjaźnij się z Google Analytics. Analizuj i działaj.
Google Analytics. Integracja i analiza danych
Daniel Waisberg
Aby podjąć dobrą decyzję o rozwoju firmy, trzeba dysponować dobrymi danymi. Zachowania użytkowników, decyzje, które podejmują, ich sposób korzystania z zasobów sieci to nieprzebrana kopalnia danych marketingowych. Ich zebranie, porównanie z danymi pochodzącymi z innych źródeł, a następnie przeanalizowanie dostarcza cennych informacji. Tymczasem wielu specjalistów wciąż analizuje tylko część danych o zachowaniu użytkowników korzystających z zasobów cyfrowych, nie mogąc uwzględnić wszystkich istotnych czynników. Problem polega na rozproszeniu różnych danych w różnych miejscach i przechowywaniu ich na różne sposoby. Konsekwencją są złe decyzje. Rozwiązaniem tego problemu jest narzędzie Google Analytics, wyjątkowo dobrze nadające się do utworzenia platformy analizy danych. Podobnie książka, którą masz przed sobą, wyjątkowo dobrze przedstawia wszystkie istotne informacje o integrowaniu danych za pomocą tego narzędzia. Odwołując się do praktycznych przykładów, szczegółowo opisano tu metody integracji i analizy danych z takich źródeł, jak AdWords, AdSense, systemy CRM i wiele innych. Autor zawarł tu też liczne wskazówki i porady, bazując na swoim ogromnym doświadczeniu. Dzięki tej książce: zaczniesz udoskonalać integrację danych pochodzących z analizy zachowań klientów i z wielu innych źródeł, będziesz stosował sprawdzone techniki umożliwiające zbieranie czytelnych i dokładnych danych, nauczysz się integrować i importować do Google Analytics wszystkie dane o rynku i klientach, wykorzystasz możliwości analityczne tego narzędzia do uzyskania pełniejszego obrazu zachowań klientów, uzyskasz spójny zestaw informacji wysokiej jakości, dzięki czemu umożliwisz managerom podejmowanie właściwych, racjonalnych decyzji biznesowych. Kluczem do sukcesu jest informacja. Kluczem do informacji jest Google Analytics.
Google Analytics od podstaw. Analiza wpływu biznesowego i wyznaczanie trendów
Mark Edmondson
Google Analytics 4 wyznacza nowe zasady marketingu cyfrowego: obecnie chodzi nie tyle o raportowanie zdarzeń z przeszłości, ile o aktywację danych przez łączenie danych online i offline ze wszystkich strumieni, aby zapewnić kompleksowe informacje marketingowe. Taka analityka cyfrowa umożliwia szybsze podejmowanie decyzji. Umiejętność korzystania z GA4 staje się więc nieodzowna. Oto zwięzły i praktyczny przewodnik po usłudze GA4 i jej integracji z chmurą. Szczególnie skorzystają z niego analitycy danych, biznesu i marketingu. Opisano tu wszystkie istotne kwestie dotyczące tego nowego, potężnego modelu analitycznego. Szczególną uwagę poświęcono bardziej zaawansowanym funkcjonalnościom GA4. Zaprezentowano architekturę GA4, strategie danych, a także informacje dotyczące pozyskiwania, przechowywania i modelowania danych. W książce znalazło się również omówienie typowych przypadków użycia dla aktywacji danych i instrukcji przydatnych podczas implementacji tych przypadków. Co istotne, poszczególne zagadnienia zostały zilustrowane praktycznymi przykładami kodu. Ta książka pomaga nie tylko zrozumieć dane, ale także wygenerować przewagę konkurencyjną! Melinda Schiera, strateg do spraw analityki Najciekawsze zagadnienia: integracja Google Cloud z GA4 przeprowadzanie integracji GA4 przechwytywanie danych GA4 i realizacja przypadków użycia projektowanie przepływów danych dostosowywanie przypadków użycia do potrzeb biznesowych Przygotuj się na cyfrowy marketing przyszłości!
Google Analytics w biznesie. Poradnik dla zaawansowanych. Wydanie II
Martyna Zastrożna
Najważniejsze narzędzie analityczne Google? Wykorzystaj je maksymalnie. Na 120%! Google Analytics to internetowe narzędzie, które Google oferuje nieodpłatnie każdemu, kto prowadzi działalność online. Dzięki niemu możliwe jest zbieranie i analizowanie danych generowanych przez internautów poruszających się w sieci, wchodzących na stronę firmy i podejmujących za pośrednictwem jej serwisu internetowego rozmaite aktywności. Dla osoby sprawnie poruszającej się w panelu użytkownika Google Analytics stanowi przebogate źródło wiedzy o klientach firmy - ich zwyczajach, zainteresowaniach, oczekiwaniach, zachowaniach itd. Te informacje mogą być podstawą do usprawnienia obsługi klienta online, a co za tym idzie - przyczynić się do zwiększenia ruchu i sprzedaży w serwisie WWW przedsiębiorstwa. Umiejętnie zaprzęgnięty do pracy Google Analytics zapewnia przewagę rynkową. Jednak słowem kluczem jest tu „umiejętnie”. Nie wystarczy bowiem podpiąć firmowy serwis pod panel analityczny i od czasu do czasu logować się do „analityksów”. Trzeba się nauczyć czytać zbierane przez Google dane, eksportować je i zestawiać w sposób, który będzie najlepiej odpowiadał potrzebom i celom biznesowym firmy. Jak pisze autorka, z Google Analytics - zwłaszcza w jego nowej odsłonie - da się wyciągnąć 120% możliwości! Jak to zrobić? Tego się dowiesz z tej książki, w drugim wydaniu pogłębionej o wiedzę dotyczącą wizualizacji danych w Google Data Studio, a także pracy z danymi wyeksportowanymi do BigQuery.
Arvind Ravulavaru
Cognitive services are the new way of adding intelligence to applications and services. Now we can use Artificial Intelligence as a service that can be consumed by any application or other service, to add smartness and make the end result more practical and useful.Google Cloud AI enables you to consume Artificial Intelligence within your applications, from a REST API. Text, video and speech analysis are among the powerful machine learning features that can be used. This book is the easiest way to get started with the Google Cloud AI services suite and open up the world of smarter applications.This book will help you build a Smart Exchange, a forum application that will let you upload videos, images and perform text to speech conversions and translation services. You will use the power of Google Cloud AI Services to make our simple forum application smart by validating the images, videos, and text provided by users to Google Cloud AI Services and make sure the content which is uploaded follows the forum standards, without a human curator involvement.You will learn how to work with the Vision API, Video Intelligence API, Speech Recognition API, Cloud Language Process, and Cloud Translation API services to make your application smarter.By the end of this book, you will have a strong understanding of working with Google Cloud AI Services, and be well on the way to building smarter applications.
Gary Hutson, Matt Jackson
Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you’ll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis.Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you’ll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you’ll also get to grips with adapting your network model to evolving data requirements.By the end of this book, you’ll be able to transform tabular data into powerful graph data models. In essence, you’ll build your knowledge from beginner to advanced-level practitioner in no time.
Ravindranatha Anthapu
While it is easy to learn and understand the Cypher declarative language for querying graph databases, it can be very difficult to master it. As graph databases are becoming more mainstream, there is a dearth of content and guidance for developers to leverage database capabilities fully. This book fills the information gap by describing graph traversal patterns in a simple and readable way.This book provides a guided tour of Cypher from understanding the syntax, building a graph data model, and loading the data into graphs to building queries and profiling the queries for best performance. It introduces APOC utilities that can augment Cypher queries to build complex queries. You’ll also be introduced to visualization tools such as Bloom to get the most out of the graph when presenting the results to the end users.After having worked through this book, you’ll have become a seasoned Cypher query developer with a good understanding of the query language and how to use it for the best performance.
Guerrilla Data Analysis Using Microsoft Excel. Overcoming Crap Data and Excel Skirmishes
MrExcel's Holy Macro! Books, Oz du Soleil,...
Unlock Microsoft Excel's hidden potential with this dynamic guide designed for data professionals and enthusiasts. You'll start by reviewing Excel basics before advancing to powerful tools like Excel Tables, Pivot Tables, and Power Query. Each chapter enhances your ability to analyze and visualize data efficiently, from complex lookups and dynamic arrays to essential data validation techniques that ensure accuracy and integrity in your spreadsheets.As you progress, you'll learn how to protect your work with advanced sheet protection methods and collaboration tools for seamless teamwork. The book also covers sophisticated functions like INDIRECT, OFFSET, and LET, preparing you to tackle complex data challenges. Additionally, you'll receive critical advice on avoiding the pitfalls of machine learning-driven features and maintaining clean, organized data.By the end of the guide, you'll have mastered Excel's advanced capabilities, empowering you to streamline workflows, optimize data processes, and make confident, data-driven decisions. This guide is your comprehensive resource for transforming your approach to data analysis with Excel.
Hadoop 2.x Administration Cookbook. Administer and maintain large Apache Hadoop clusters
Aman Singh
Hadoop enables the distributed storage and processing of large datasets across clusters of computers. Learning how to administer Hadoop is crucial to exploit its unique features. With this book, you will be able to overcome common problems encountered in Hadoop administration.The book begins with laying the foundation by showing you the steps needed to set up a Hadoop cluster and its various nodes. You will get a better understanding of how to maintain Hadoop cluster, especially on the HDFS layer and using YARN and MapReduce. Further on, you will explore durability and high availability of a Hadoop cluster. You’ll get a better understanding of the schedulers in Hadoop and how to configure and use them for your tasks. You will also get hands-on experience with the backup and recovery options and the performance tuning aspects of Hadoop. Finally, you will get a better understanding of troubleshooting, diagnostics, and best practices in Hadoop administration.By the end of this book, you will have a proper understanding of working with Hadoop clusters and will also be able to secure, encrypt it, and configure auditing for your Hadoop clusters.
Sudheesh Narayan, Tanmay Deshpande, Anurag Shrivastava
If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level.Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book.The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space.
Hadoop: Data Processing and Modelling. Data Processing and Modelling
Sandeep Karanth, Gerald Turkington, Tanmay Deshpande
As Marc Andreessen has said “Data is eating the world,” which can be witnessed today being the age of Big Data, businesses are producing data in huge volumes every day and this rise in tide of data need to be organized and analyzed in a more secured way. With proper and effective use of Hadoop, you can build new-improved models, and based on that you will be able to make the right decisions.The first module, Hadoop beginners Guide will walk you through on understanding Hadoop with very detailed instructions and how to go about using it. Commands are explained using sections called “What just happened” for more clarity and understanding. The second module, Hadoop Real World Solutions Cookbook, 2nd edition, is an essential tutorial to effectively implement a big data warehouse in your business, where you get detailed practices on the latest technologies such as YARN and Spark.Big data has become a key basis of competition and the new waves of productivity growth. Hence, once you get familiar with the basics and implement the end-to-end big data use cases, you will start exploring the third module, Mastering Hadoop. So, now the question is if you need to broaden your Hadoop skill set to the next level after you nail the basics and the advance concepts, then this course is indispensable. When you finish this course, you will be able to tackle the real-world scenarios and become a big data expert using the tools and the knowledge based on the various step-by-step tutorials and recipes.
Hadoop. Komplety przewodnik. Analiza i przechowywanie danych
Tom White
Analiza danych z Hadoopem — i wszystko staje się prostsze! Podstawy Hadoopa i model MapReduce Praca z Hadoopem, budowa klastra i zarządzanie platformą Dodatki zwiększające funkcjonalność Hadoopa Platforma Apache Hadoop to jedno z zaawansowanych narzędzi informatycznych. Dzięki niej można przeprowadzać różne operacje na dużych ilościach danych i znacznie skrócić czas wykonywania tych działań. Wszędzie tam, gdzie potrzebne jest szybkie sortowanie, obliczanie i archiwizowanie danych — np. w dużych międzynarodowych sklepach internetowych, serwisach społecznościowych lub wyszukiwarkach, takich jak Amazon, Facebook, Yahoo!, Apache Hadoop sprawdza się znakomicie. Jeśli potrzebne Ci narzędzie do poważnej analizy dużych zbiorów danych, nie znajdziesz lepszego rozwiązania! Tę książkę napisał wytrawny znawca i współtwórca Hadoopa. Przedstawia w niej wszystkie istotne mechanizmy działania platformy i pokazuje, jak efektywnie jej używać. Dowiesz się stąd, do czego służą model MapReduce oraz systemy HDFS i YARN. Nauczysz się budować aplikacje oraz klastry. Poznasz dwa formaty danych, a także wykorzystasz narzędzia do ich pobierania i transferu. Sprawdzisz, jak wysokopoziomowe narzędzia do przetwarzania danych współdziałają z Hadoopem. Zorientujesz się, jak działa rozproszona baza danych i jak zarządzać konfiguracją w środowisku rozproszonym. Przeczytasz również o nowinkach w Hadoopie 2 i prześledzisz studia przypadków ilustrujące rolę Hadoopa w systemach służby zdrowia i przy przetwarzaniu danych o genomie. Hadoop i model MapReduce Systemy HDFS i YARN Operacje wejścia – wyjścia w platformie Hadoop Typy, formaty, funkcje i budowa aplikacji w modelu MapReduce Zarządzanie platformą Hadoop Avro, Parquet, Flume i Sqoop — metody pracy z danymi Pig, Hive, Crunch i Spark — wysokopoziomowe narzędzia do przetwarzania danych HBase i ZooKeeper — praca w środowisku rozproszonym Integrowanie danych w firmie Cerner Nauka o danych biologicznych Cascading Hadoop — rozwiązanie na miarę wyzwań globalnych! Tom White — jeden z czołowych ekspertów w zakresie obsługi platformy Hadoop. Członek organizacji Apache Software Foundation, inżynier oprogramowania w firmie Cloudera.
Tanmay Deshpande
Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business.
Quan Nguyen
JetBrain’s PyCharm is the most popular Integrated Development Environment (IDE) used by the Python community thanks to its numerous features that facilitate faster, more accurate, and more productive programming practices. However, the abundance of options and customizations can make PyCharm seem quite intimidating.Hands-on Application Development with PyCharm starts with PyCharm’s installation and configuration process, and systematically takes you through a number of its powerful features that can greatly improve your productivity. You’ll explore code automation, version control, graphical debugging/testing, management of virtual environments, and much more. Finally, you’ll delve into specific PyCharm features that support web development and data science, two of the fastest growing applications in Python programming. These include the integration of the Django framework as well as the extensive support for IPython and Jupyter Notebook.By the end of this PyCharm book, you will have gained extensive knowledge of the tool and be able to implement its features and make the most of its support for your projects.
Amita Kapoor, Hector Duran Lopez-Velarde
There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter.This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models.By the end of this book, you will be able to build smart AI-powered IoT apps with confidence.
Subhashini Tripuraneni, Charles Song
From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS.With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS.The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning.By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle.
Sibanjan Das, Umit Mert Cakmak
AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.
James Cross, Rudy Lai, Bartłomiej Potaczek
Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs.You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark.By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively.
Arjuna Sky Kok
Blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions. This book serves as a practical guide to developing a full-fledged decentralized application with Python to interact with the various building blocks of blockchain applications.Hands-On Blockchain for Python Developers starts by demonstrating how blockchain technology and cryptocurrency hashing works. You will understand the fundamentals and benefits of smart contracts such as censorship resistance and transaction accuracy. As you steadily progress, you'll go on to build smart contracts using Vyper, which has a similar syntax to Python. This experience will further help you unravel the other benefits of smart contracts, including reliable storage and backup, and efficiency. You'll also use web3.py to interact with smart contracts and leverage the power of both the web3.py and Populus framework to build decentralized applications that offer security and seamless integration with cryptocurrencies. As you explore later chapters, you'll learn how to create your own token on top of Ethereum and build a cryptocurrency wallet graphical user interface (GUI) that can handle Ethereum and Ethereum Request for Comments (ERC-20) tokens using the PySide2 library. This will enable users to seamlessly store, send, and receive digital money. Toward the end, you'll implement InterPlanetary File System (IPFS) technology in your decentralized application to provide a peer-to-peer filesystem that can store and expose media.By the end of this book, you'll be well-versed in blockchain programming and be able to build end-to-end decentralized applications on a range of domains using Python.
Pablo Labbe, Clever Anjos , Kaushik Solanki,...
Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions.Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense’s features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You’ll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you’ll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you’ll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you’ll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices.
Rajneesh Gupta
Blockchain technology is being welcomed as one of the most revolutionary and impactful innovations of today. Blockchain technology was first identified in the world’s most popular digital currency, Bitcoin, but has now changed the outlook of several organizations and empowered them to use it even for storage and transfer of value.This book will start by introducing you to the common cyberthreat landscape and common attacks such as malware, phishing, insider threats, and DDoS. The next set of chapters will help you to understand the workings of Blockchain technology, Ethereum and Hyperledger architecture and how they fit into the cybersecurity ecosystem. These chapters will also help you to write your first distributed application on Ethereum Blockchain and the Hyperledger Fabric framework. Later, you will learn about the security triad and its adaptation with Blockchain. The last set of chapters will take you through the core concepts of cybersecurity, such as DDoS protection, PKI-based identity, 2FA, and DNS security. You will learn how Blockchain plays a crucial role in transforming cybersecurity solutions.Toward the end of the book, you will also encounter some real-world deployment examples of Blockchain in security cases, and also understand the short-term challenges and future of cybersecurity with Blockchain.
Abhishek Agarwal
QlikView is one of the market leaders when it comes to building effective Business Intelligence solutions. This book will show how you can leverage its power to build your own dashboards to tell your own data story.The book starts with showing you how to connect your data to QlikView and create your own QlikView application. You will learn how to add data from multiple sources, create a data model by joining data, and then review it on the front end. You will work with QlikView components such as charts, list boxes, input boxes, and text objects to create stunning visualizations that help give actionable business insights. You will also learn how to perform analysis on your data in QlikView and master the various types of security measures to be taken in QlikView.By the end of this book, you will have all the essential knowledge required for insightful data storytelling and creating useful BI dashboards using QlikView.
Chris Beeley
Although vanilla Shiny applications look attractive with some layout flexibility, you may still want to have more control over how the interface is laid out to produce a dashboard. Hands-On Dashboard Development with Shiny helps you incorporate this in your applications.The book starts by guiding you in producing an application based on the diamonds dataset included in the ggplot2 package. You’ll create a single application, but the interface will be reskinned and rebuilt throughout using different methods to illustrate their uses and functions using HTML, CSS, and JavaScript. You will also learn to develop an application that creates documents and reports using R Markdown. Furthermore, the book demonstrates the use of HTML templates and the Bootstrap framework. Moving along, you will learn how to produce dashboards using the Shiny command and dashboard package. Finally, you will learn how to lay out applications using a wide range of built-in functions.By the end of the book, you will have an understanding of the principles that underpin layout in Shiny applications, including sections of HTML added to a vanilla Shiny application, HTML interfaces written from scratch, dashboards, navigation bars, and interfaces.