Język R. Receptury. Analiza danych, statystyka i przetwarzanie grafiki. Wydanie II

JD Long, Paul Teetor

Język R jest potężnym narzędziem używanym w statystyce, przetwarzaniu grafiki i programowaniu statystycznym; stanowi konkurencję dla komercyjnych systemów do obliczeń tego rodzaju. Zawiera wszystkie narzędzia, których potrzebują statystycy. Równocześnie jest to specyficzny język, przez co jego użytkowanie może sprawiać problemy. Zarówno proste, jak i złożone zadania są łatwe do wykonania, jeśli tylko wiadomo, w jaki sposób je zrobić. Jeżeli jednak trzeba stopniowo dochodzić do właściwego rozwiązania, może to kosztować sporo cierpliwości i zniechęcać. Oto zbiór 275 receptur instruktażowych, z których każda pomaga w rozwiązaniu konkretnego problemu. Wszystkie zostały starannie przetestowane i wielokrotnie dowodziły swojej przydatności. Każda z omawianych receptur została poprzedzona krótkim wprowadzeniem i omówieniem zastosowanych mechanizmów działania. Nie jest to klasyczny podręcznik programowania, jednak z pewnością przyśpieszy naukę praktycznego wykorzystania możliwości R. Jeśli masz już pewne doświadczenie z tym językiem, odświeżysz swoją wiedzę i uzyskasz szerszą perspektywę. Wśród receptur znajdziesz obejmujące szeroki zakres zadania - od podstawowych operacji na danych wejściowych i wyjściowych, poprzez statystykę ogólną, aż po grafikę i regresję liniową. Dowiesz się również, jak wykorzystać język R do wizualizacji danych za pomocą ciekawych wykresów graficznych. W tej książce między innymi: przygotowywanie danych wejściowych i upraszczanie danych wyjściowych macierze, listy, wektory czynnikowe, ramki danych testy statystyczne, przedziały ufności, prawdopodobieństwa modele statystyczne z wykorzystaniem regresji liniowej i analizy wariancji stosowanie zaawansowanych technik statystycznych R: błyskawicznie osiągniesz znakomite wyniki!

Julia 1.0 Programming Cookbook. Over 100 numerical and distributed computing recipes for your daily data science work?ow

Bogumił Kamiński, Przemysław Szufel

Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia.Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia.By the end of the book, you will have acquired the skills to work more effectively with your data

Julia for Data Science. high-performance computing simplified

Anshul Joshi

Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century).This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game.This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations.You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning.This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia.

Jupyter Cookbook. Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Dan Toomey

Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications.The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it.

Jupyter for Data Science. Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

Dan Toomey

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations, and visualizations. This book is a comprehensive guide to getting started with data science using the popular Jupyter notebook. If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The book also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks.By the end of this book, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.

Kibana 7 Quick Start Guide. Visualize your Elasticsearch data with ease

Anurag Srivastava

The Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective. This book endeavors to explain all the important aspects of Kibana, which is essential for utilizing its full potential.This book covers the core concepts of Kibana, with chapters set out in a coherent manner so that readers can advance their learning in a step-by-step manner. The focus is on a practical approach, thereby enabling the reader to apply those examples in real time for a better understanding of the concepts and to provide them with the correct skills in relation to the tool. With its succinct explanations, it is quite easy for a reader to use this book as a reference guide for learning basic to advanced implementations of Kibana. The practical examples, such as the creation of Kibana dashboards from CSV data, application RDBMS data, system metrics data, log file data, APM agents, and search results, can provide readers with a number of different drop-off points from where they can fetch any type of data into Kibana for the purpose of analysis or dashboarding.

Kibana 8.x - A Quick Start Guide to Data Analysis. Learn about data exploration, visualization, and dashboard building with Kibana

Krishna Shah

Unleash the full potential of Kibana—an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets.Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You’ll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens.By the end of this book, you’ll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case.

Kibana Essentials. Use the functionalities of Kibana to discover data and build attractive visualizations and dashboards for real-world scenarios

Surendra Mohan, Yuvraj Gupta, Tim Roes

KNIME Essentials. Perform accurate data analysis using the power of KNIME

Gábor Bakos

KNIME is an open source data analytics, reporting, and integration platform, which allows you to analyze a small or large amount of data without having to reach out to programming languages like R.KNIME Essentials teaches you all you need to know to start processing your first data sets using KNIME. It covers topics like installation, data processing, and data visualization including the KNIME reporting features. Data processing forms a fundamental part of KNIME, and KNIME Essentials ensures that you are fully comfortable with this aspect of KNIME before showing you how to visualize this data and generate reports.KNIME Essentials guides you through the process of the installation of KNIME through to the generation of reports based on data. The main parts between these two phases are the data processing and the visualization. The KNIME variants of data analysis concepts are introduced, and after the configuration and installation description comes the data processing which has many options to convert or extend it. Visualization makes it easier to get an overview for parts of the data, while reporting offers a way to summarize them in a nice way.

Kompletny przewodnik po DAX. Analiza biznesowa przy użyciu Microsoft Excel, SQL Server Analysis Services i Power BI

Alberto Ferrari, Marco Russo

Kompletny przewodnik po DAX to najbardziej wyczerpujący i autorytatywny podręcznik języka Microsoft DAX w zastosowaniach BI i analityce. Podczas gdy inne książki omawiają tylko podstawy, ten przewodnik zapewnia wiedzę na poziomie eksperckim potrzebnych średnio i wysoko zaawansowanym użytkownikom Excela i profesjonalistom BI, od podstaw po innowacyjne techniki wysokiej wydajności. Dwaj czołowi konsultanci i wykładowcy Microsoft BI przedstawiają język DAX poprzez realistyczne i przydatne przykłady, prezentujące typowe obliczenia pozwalające użytkownikom od razu uzyskiwać wyniki. Alberto Ferrari i Marco Russo rozjaśniają złożone zagadnienia pokazując czytelnikom, co się dzieje pod maską silnika DAX, gdy wykonywane są wyrażenia. Ferrari i Russo starannie przechodzą przez typowe scenariusze, w których działanie DAX może być trudne do zrozumienia; pokazują, jak optymalizować modele danych, aby wyrażenia DAX były szybko wykonywane; demonstrują, jak pisać szybki i odporny kod DAX; wyjaśniają, jak usuwać wąskie gardła z istniejącego kodu. Pokazują działanie DAX zarówno w środowisku SQL Server, jak i Microsoft Excel, ułatwiając pracę bez względu na to, którą platformę Microsoft BI preferuje czytelnik.

Kompletny przewodnik po DAX, wyd. 2 rozszerzone. Analiza biznesowa przy użyciu Microsoft Power BI, SQL Server Analysis Services i Excel

Alberto Ferrari, Marco Russo

WYDANIE DRUGIE uzupełnione i rozszerzone Najbardziej wyczerpujący przewodnik po języku DAX, obecnie rozszerzony i uzupełniony o najnowsze funkcje i nowoczesne zalecane praktyki, prezentujący opracowany w firmie Microsoft język na potrzeby analiz biznesowych i modelowania danych. Czołowi eksperci w dziedzinie Microsoft BI pomagają opanować wszystkie elementy systemu, od funkcji tablicowych po zaawansowany kod i optymalizację modelu. Dowiedz, co naprawdę dzieje się przy wykonywaniu poleceń DAX i jak użyć tej wiedzy do pisania szybkiego i niezawodnego kodu. Wydanie to skupia się na przykładach, które można budować i uruchamiać przy użyciu bezpłatnego narzędzia Power BI Desktop i pomaga wydobyć najwięcej korzyści ze składni zmiennych (VAR) w Power BI, Excelu lub Analysis Services. Pragniesz wykorzystać wszystkie możliwości języka ? To książka, której potrzebujesz. Wykonuj skuteczną analizę danych w programach Power BI, SQL Server i Excel Poznaj podstawowe koncepcje DAX, w tym kolumny obliczane, miary i obsługę błędów Wydajnie korzystaj z zaawansowanych funkcji tablicowych Opanuj istotę kontekstów wykonania oraz funkcje ­CALCULATE i CALCULATETABLE Wykonuj obliczenia czasowe i oparte na niestandardowych hierarchiach Korzystaj z grup obliczeń i elementów obliczanych Używaj składni zmiennych do tworzenia bardziej czytelnego, zrozumiałego kodu Wyrażaj różnorodne nietypowe relacje, w tym relacje wiele-do-wielu i filtry dwukierunkowe Opanuj zaawansowane techniki optymalizacyjne, aby zwiększyć wydajność agregacji Optymalizuj modele danych Mierz wydajność zapytań przy użyciu DAX Studio i dowiedz się, jak optymalizować kod DAX O tej książce Dla zaawansowanych użytkowników programu Excel oraz anlityków BI używających SQL Server Analysis Services lub Power BI O autorach Marco Russo i Alberto Ferrari są współzałożycielami strony sqlbi.com, w której regularnie publikują artykuły na temat Microsoft PowerPivot, DAX, Power BI oraz SQL Server Analysis Services. Występują też na głównych międzynarodowych konferencjach, takich jak TechEd, Ignite, PASS Summit czy SQLBits. Obydwaj wykładają teorię analizy biznesowej (BI) oraz technologie Microsoft BI począwszy od roku 1999. Książki ich autorstwa obejmują Excel 2013: Budowanie modeli danych przy użyciu PowerPivot, Analyzing Data with Power BI and Power Pivot for Excel oraz Introducing Microsoft Power BI.

Korporacyjne jezioro danych. Wykorzystaj potencjał big data w swojej organizacji

Alex Gorelik

Koncepcja big data, nauka o danych i analityka danych wspomagają dziś procesy decyzyjne w przedsiębiorstwach w niespotykanym wcześniej zakresie. Zwiększają poziom efektywności pracy w wielu różnych branżach. Korporacje zaczęły więc eksperymenty z wykorzystaniem big data i technologii chmury, aby budować jeziora danych oraz tworzyć oparte na nich systemy podejmowania decyzji. Niejeden z tych projektów się nie powiódł, gdyż nie został dostosowany do kultury i potrzeb przedsiębiorstwa. Najwyraźniej zabrakło wiedzy, w jaki sposób skutecznie przeprowadzać tak radykalną transformację. Ta książka jest praktycznym przewodnikiem, który ułatwia wdrażanie architektury jeziora danych (ang. data lake) w przedsiębiorstwie. Omówiono tu różne podejścia do jej uruchamiania i rozwijania, w tym kałuże danych (analityczne piaskownice) i stawy danych (hurtownie danych), a także budowanie jezior danych od podstaw. Opisano konfigurowanie różnych stref, co pozwala na odpowiednie rozmieszczenie zarówno surowych, jak i starannie zarządzanych i przetworzonych danych. Wyjaśniono znaczenie zarządzania dostępem do stref. Zawarto tu również wskazówki umożliwiające zachowanie zgodności z regułami zarządzania danymi przedsiębiorstwa. W tej książce: wprowadzenie do hurtowni danych, big data i nauki o danych praktyczne techniki budowania jezior danych najlepsze praktyki dostarczania analitykom dostępu do danych projektowanie architektury jeziora danych oraz różne techniki implementacji zalety i wady różnych podejść do budowania magazynów danych i zarządzania nimi Jeziora danych i big data - ocean możliwości!

LaTeX Beginner's Guide. Create visually appealing texts, articles, and books for business and science using LaTeX - Second Edition

Stefan Kottwitz

LaTeX is high-quality open source typesetting software that produces professional prints and PDF files. It's a powerful and complex tool with a multitude of features, so getting started can be intimidating. However, once you become comfortable with LaTeX, its capabilities far outweigh any initial challenges, and this book will help you with just that!The LaTeX Beginner's Guide will make getting started with LaTeX easy. If you are writing mathematical, scientific, or business papers, or have a thesis to write, this is the perfect book for you. With the help of fully explained examples, this book offers a practical introduction to LaTeX with plenty of step-by-step examples that will help you achieve professional-level results in no time. You'll learn to typeset documents containing tables, figures, formulas, and common book elements such as bibliographies, glossaries, and indexes, and go on to manage complex documents and use modern PDF features. You'll also get to grips with using macros and styles to maintain a consistent document structure while saving typing work.By the end of this LaTeX book, you'll have learned how to fine-tune text and page layout, create professional-looking tables, include figures, present complex mathematical formulas, manage complex documents, and benefit from modern PDF features.

Learn Algorithmic Trading. Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis

Sebastien Donadio, Sourav Ghosh

It’s now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate.You’ll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You’ll explore the key components of an algorithmic trading business and aspects you’ll need to take into account before starting an automated trading project. Next, you’ll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you’ll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you’ll create a trading bot from scratch using the algorithms built in the previous sections.By the end of this book, you’ll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets.

Learn Azure Synapse Data Explorer. A guide to building real-time analytics solutions to unlock log and telemetry data

Pericles (Peri) Rocha

Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data.This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you’ll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you’ll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users.By the end of this book, you’ll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.

Learn Bitcoin and Blockchain. Understanding blockchain and Bitcoin architecture to build decentralized applications

Kirankalyan Kulkarni

Blockchain is a distributed database that enables permanent, transparent, and secure storage of data. Blockchain technology uses cryptography to keep data secure. Learn Bitcoin and Blockchain is the perfect entry point to the world of decentralized databases.This book will take you on a journey through the blockchain database, followed by advanced implementations of the blockchain concept. You will learn about Bitcoin basics and their technical operations. As you make your way through the book, you will gain insight into this leading technology and its implementation in the real world. You will also cover the technical foundation of blockchain and understand the fundamentals of cryptography and how they keep data secure. In the concluding chapters, you’ll get to grips with the mechanisms behind cryptocurrencies.By the end of this book, you will have learned about decentralized digital money, advanced blockchain concepts, and Bitcoin and blockchain security.

Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2

Helder da Rocha

Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice.This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript.By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js.

Learn Grafana 10.x. A beginner's guide to practical data analytics, interactive dashboards, and observability - Second Edition

Eric Salituro

Get 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.

Learn Microsoft Fabric. A practical guide to performing data analytics in the era of artificial intelligence

Arshad Ali, Bradley Schacht

Discover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model. This book provides an overview of Microsoft Fabric, its components, and the wider analytics landscape.In this book, you'll explore workloads such as Data Factory, Synapse Data Engineering, data science, data warehouse, real-time analytics, and Power BI. You’ll learn how to build end-to-end lakehouse and data warehouse solutions using the medallion architecture, unlock the real-time analytics, and implement machine learning and AI models. As you progress, you’ll build expertise in monitoring workloads and administering Fabric across tenants, capacities, and workspaces. The book also guides you step by step through enhancing security and governance practices in Microsoft Fabric and implementing CI/CD workflows with Azure DevOps or GitHub. Finally, you’ll discover the power of Copilot, an AI-driven assistant that accelerates your analytics journey.By the end of this book, you’ll have unlocked the full potential of AI-driven data analytics, gaining a comprehensive understanding of the analytics landscape and mastery over the essential concepts and principles of Microsoft Fabric.

Learn Odoo. A beginner's guide to designing, configuring, and customizing business applications with Odoo

Greg Moss

Odoo is management software that contains a set of open source enterprise management applications that help you modernize your business.Completely revised and updated, this comprehensive Odoo guide is a fourth edition of Working with Odoo. This book begins with an introduction to Odoo and helps you set up Odoo Online in your system. You'll learn how to start a new company database in Odoo and the basics of Odoo sales management. You will explore customer relationship management in Odoo and its importance in a modern business environment. Moving on, you'll learn how to install the purchasing application, set up suppliers, and begin purchasing and receiving products in Odoo. Next, you'll learn how to use the MRP module to create, process, and schedule the manufacturing and production order. Once you get to grips with the basic applications, you'll uncover how to customize Odoo to meet the specific needs of your business. You'll learn some advanced techniques for searching and finding information, and you'll be taken through business intelligence in Odoo. Towards the end of the book, you'll go in-depth into Odoo's architecture and learn to use Odoo's API to integrate with other applications. By the end of the book, you'll be ready to use Odoo to build enterprise applications and set up the functional requirements for your business.

Learn PostgreSQL. Use, manage, and build secure and scalable databases with PostgreSQL 16 - Second Edition

Luca Ferrari, Enrico Pirozzi

The latest edition of this PostgreSQL book will help you to start using PostgreSQL from absolute scratch, helping you to quickly understand the internal workings of the database. With a structured approach and practical examples, go on a journey that covers the basics, from SQL statements and how to run server-side programs, to configuring, managing, securing, and optimizing database performance.This new edition will not only help you get to grips with all the recent changes within the PostgreSQL ecosystem but will also dig deeper into concepts like partitioning and replication with a fresh set of examples. The book is also equipped with Docker images for each chapter which makes the learning experience faster and easier. Starting with the absolute basics of databases, the book sails through to advanced concepts like window functions, logging, auditing, extending the database, configuration, partitioning, and replication. It will also help you seamlessly migrate your existing database system to PostgreSQL and contains a dedicated chapter on disaster recovery. Each chapter ends with practice questions to test your learning at regular intervals.By the end of this book, you will be able to install, configure, manage, and develop applications against a PostgreSQL database.

Learn Power BI. A beginner's guide to developing interactive business intelligence solutions using Microsoft Power BI

Greg Deckler

To succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This Power BI book is an entry-level guide that will get you up and running with data modeling, visualization, and analytical techniques from scratch.You'll find this book handy if you want to get well-versed with the extensive Power BI ecosystem. You'll start by covering the basics of business intelligence and installing Power BI. You'll then learn the wide range of Power BI features to unlock business insights. As you progress, the book will take you through how to use Power Query to ingest, cleanse, and shape your data, and use Power BI DAX to create simple to complex calculations. You'll also be able to add a variety of interactive visualizations to your reports to bring your data to life. Finally, you'll gain hands-on experience in creating visually stunning reports that speak to business decision makers, and see how you can securely share these reports and collaborate with others.By the end of this book, you'll be ready to create simple, yet effective, BI reports and dashboards using the latest features of Power BI.

Learn TensorFlow Enterprise. Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise

KC Tung

TensorFlow as a machine learning (ML) library has matured into a production-ready ecosystem. This beginner’s book uses practical examples to enable you to build and deploy TensorFlow models using optimal settings that ensure long-term support without having to worry about library deprecation or being left behind when it comes to bug fixes or workarounds.The book begins by showing you how to refine your TensorFlow project and set it up for enterprise-level deployment. You’ll then learn how to choose a future-proof version of TensorFlow. As you advance, you’ll find out how to build and deploy models in a robust and stable environment by following recommended practices made available in TensorFlow Enterprise. This book also teaches you how to manage your services better and enhance the performance and reliability of your artificial intelligence (AI) applications. You’ll discover how to use various enterprise-ready services to accelerate your ML and AI workflows on Google Cloud Platform (GCP). Finally, you’ll scale your ML models and handle heavy workloads across CPUs, GPUs, and Cloud TPUs.By the end of this TensorFlow book, you’ll have learned the patterns needed for TensorFlow Enterprise model development, data pipelines, training, and deployment.

Learning Alteryx. A beginner's guide to using Alteryx for self-service analytics and business intelligence

Renato Baruti

Alteryx, as a leading data blending and advanced data analytics platform, has taken self-service data analytics to the next level. Companies worldwide often find themselves struggling to prepare and blend massive datasets that are time-consuming for analysts. Alteryx solves these problems with a repeatable workflow designed to quickly clean, prepare, blend, and join your data in a seamless manner. This book will set you on a self-service data analytics journey that will help you create efficient workflows using Alteryx, without any coding involved. It will empower you and your organization to take well-informed decisions with the help of deeper business insights from the data.Starting with the fundamentals of using Alteryx such as data preparation and blending, you will delve into the more advanced concepts such as performing predictive analytics. You will also learn how to use Alteryx’s features to share the insights gained with the relevant decision makers. To ensure consistency, we will be using data from the Healthcare domain throughout this book. The knowledge you gain from this book will guide you to solve real-life problems related to Business Intelligence confidently. Whether you are a novice with Alteryx or an experienced data analyst keen to explore Alteryx’s self-service analytics features, this book will be the perfect companion for you.