Handbuch Data Engineering
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Handbuch Data Engineering
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Author : Joe Reis
language : de
Publisher: O'Reilly
Release Date : 2023-08-01
Handbuch Data Engineering written by Joe Reis and has been published by O'Reilly this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-01 with Computers categories.
Der praxisnahe Überblick über die gesamte Data-Engineering-Landschaft Das Buch vermittelt grundlegende Konzepte des Data Engineering und beschreibt Best Practices für jede Phase des Datenlebenszyklus Mit dem Data-Engineering-Lifecycle bietet es einen konzeptionellen Rahmen, der langfristig Gültigkeit haben wird Es unterstützt Sie - jenseits des Hypes - bei der Auswahl der richtigen Datentechnologien, Architekturen und Prozesse und verfolgt den Cloud-First-Ansatz Data Engineering hat sich in den letzten zehn Jahren rasant weiterentwickelt, so dass viele Softwareentwickler, Data Scientists und Analysten nach einer zusammenfassenden Darstellung grundlegender Techniken suchen. Dieses praxisorientierte Buch bietet einen umfassenden Überblick über das Data Engineering und gibt Ihnen mit dem Data-Engineering-Lifecycle ein Framework an die Hand, das die Evaluierung und Auswahl der besten Technologien für reale Geschäftsprobleme erleichtert. Sie erfahren, wie Sie Systeme so planen und entwickeln, dass sie den Anforderungen Ihres Unternehmens und Ihrer Kunden optimal gerecht werden. Die Autoren Joe Reis und Matt Housley führen Sie durch den Data-Engineering-Lebenszyklus und zeigen Ihnen, wie Sie eine Vielzahl von Cloud-Technologien kombinieren können, um die Bedürfnisse von Datenkonsumenten zu erfüllen. Sie lernen, die Konzepte der Datengenerierung, -aufnahme, -orchestrierung, -transformation, -speicherung und -verwaltung anzuwenden, die in jeder Datenumgebung unabhängig von der verwendeten Technologie von entscheidender Bedeutung sind. Darüber hinaus erfahren Sie, wie Sie Data Governance und Sicherheit in den gesamten Datenlebenszyklus integrieren.
Master Python Data Engineering With Virtual Ai Tutoring
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2024-11-19
Master Python Data Engineering With Virtual Ai Tutoring written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-19 with Business & Economics categories.
Imagine acquiring a book and, as a bonus, gaining access to a 24/7 AI-assisted Virtual Tutoring to personalize your learning journey, reinforce knowledge, and receive mentorship for developing and implementing real projects... ...Welcome to the Revolution of Personalized Learning with AI-Assisted Virtual Tutoring! Discover " MASTER PYTHON DATA ENGINEERING: From Fundamentals to Advanced Applications with Virtual AI Tutoring," the essential guide for professionals and enthusiasts who want to master data engineering with Python. This innovative manual, written by Diego Rodrigues, an author with over 140 titles published in six languages, combines high-quality content with the advanced technology of IAGO, a virtual tutor developed and hosted on the OpenAI platform. Innovative Features: Personalized Learning: IAGO adapts the content to your knowledge level, offering detailed explanations and personalized exercises. Immediate Feedback: Receive corrections and suggestions in real time, speeding up your learning process. Interactivity and Engagement: Interact with the tutor via text or voice, making learning more dynamic and motivating. Project Development Mentorship: Get practical guidance to develop and implement real projects, applying the knowledge gained. Total Flexibility: Access the tutor anywhere, anytime, whether on a desktop, notebook, or smartphone with web access. Take advantage of the Limited-Time Launch Promotional Price! Don't miss the opportunity to transform your learning journey with an innovative and effective method. This book has been carefully structured to meet your needs and exceed your expectations, ensuring you are prepared to face challenges and seize opportunities in the field of data engineering. Open the book sample and discover how to access the select club of cutting-edge technology professionals. Take advantage of this unique opportunity and achieve your goals! TAGS: data engineering automation science big Pandas NumPy Dask SQLAlchemy web scraping BeautifulSoup Scrapy APIs ETL DataOps Data Lakes Data Warehouses AWS Google Cloud Microsoft Azure Hadoop Spark machine learning artificial intelligence data pipelines data visualization Matplotlib Seaborn data analysis relational databases NoSQL MongoDB Apache Airflow Kafka real-time data governance data security compliance mentorship Diego Rodrigues Tableau Power BI Snowflake Informatica Alation Talend Apache Flink Jupyter Notebooks DevOps Databricks Cloudera Hortonworks Teradata IBM Cloud Oracle Cloud Salesforce SAP HANA ElasticSearch Redis Kubernetes Docker Jenkins GitHub GitLab Continuous Integration Continuous Deployment CI/CD digital transformation predictive analysis business intelligence IoT Internet of Things smart cities connected health Industry 4.0 fintechs retail education marketing competitive intelligence data science automated testing custom reports operational efficiency Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global cybersecurity trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud security threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR
Ai Driven Data Engineering Transforming Big Data Into Actionable Insight
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Author : Eswar Prasad Galla
language : en
Publisher: JEC PUBLICATION
Release Date :
Ai Driven Data Engineering Transforming Big Data Into Actionable Insight written by Eswar Prasad Galla and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Architecture categories.
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Fundamentals Of Data Engineering
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Author : Joe Reis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-22
Fundamentals Of Data Engineering written by Joe Reis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Computers categories.
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology. This book will help you: Get a concise overview of the entire data engineering landscape Assess data engineering problems using an end-to-end framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle
Webkdd 2002 Mining Web Data For Discovering Usage Patterns And Profiles
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Author : Osmar R. Zaiane
language : en
Publisher: Springer
Release Date : 2003-10-02
Webkdd 2002 Mining Web Data For Discovering Usage Patterns And Profiles written by Osmar R. Zaiane and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-02 with Computers categories.
1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that - dress the unique challenges of discovering insights from Web usage data, aiming toevaluateWebusability,understandtheinterestsandexpectationsofusersand assess the e?ectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce and a new channel for content providers. Customized o?ers and content, made possible by discovered knowledge about the customer, are fundamental for the establi- ment of viable e-commerce solutions and sustained and e?ective content delivery in noncommercial domains. Rich Web logs provide companies with data about their online visitors and prospective customers, allowing microsegmentation and personalized interactions. While Web mining as a domain is several years old, the challenges that characterize data analysis in this area continue to be formidable. Though p- processing data routinely takes up a major part of the e?ort in data mining, Web usage data presents further challenges based on the di?culties of assigning data streams to unique users and tracking them over time. New innovations are required to reliably reconstruct sessions, to ascertain similarity and di?erences between sessions, and to be able to segment online users into relevant groups.
Handbook Of Nuclear Engineering
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Author : Dan Gabriel Cacuci
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-14
Handbook Of Nuclear Engineering written by Dan Gabriel Cacuci and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-14 with Science categories.
This is an authoritative compilation of information regarding methods and data used in all phases of nuclear engineering. Addressing nuclear engineers and scientists at all levels, this book provides a condensed reference on nuclear engineering since 1958.
Handbuch Der Internationalen Dokumentation Und Information
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Author : Peter Wennrich
language : en
Publisher:
Release Date : 1977
Handbuch Der Internationalen Dokumentation Und Information written by Peter Wennrich and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with categories.
Routledge German Dictionary Of Electrical Engineering And Electronics Worterbuch Elektrotechnik And Elektronik Englisch
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Author : Prof Dr Peter-Klaus Budig
language : en
Publisher: Routledge
Release Date : 2020-10-14
Routledge German Dictionary Of Electrical Engineering And Electronics Worterbuch Elektrotechnik And Elektronik Englisch written by Prof Dr Peter-Klaus Budig and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-14 with Computers categories.
This book presents the vocabulary of a continually evolving and fundamental technical field which is finding ever broad applications in industry. It provides special attention to the language of national and international standards and recommendations, as well as appropriate field indications.
Handbuch Data Engineering
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Author : Joe Reis
language : de
Publisher: O'Reilly
Release Date : 2023-08-01
Handbuch Data Engineering written by Joe Reis and has been published by O'Reilly this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-01 with Computers categories.
Der praxisnahe Überblick über die gesamte Data-Engineering-Landschaft Das Buch vermittelt grundlegende Konzepte des Data Engineering und beschreibt Best Practices für jede Phase des Datenlebenszyklus Mit dem Data-Engineering-Lifecycle bietet es einen konzeptionellen Rahmen, der langfristig Gültigkeit haben wird Es unterstützt Sie - jenseits des Hypes - bei der Auswahl der richtigen Datentechnologien, Architekturen und Prozesse und verfolgt den Cloud-First-Ansatz Data Engineering hat sich in den letzten zehn Jahren rasant weiterentwickelt, so dass viele Softwareentwickler, Data Scientists und Analysten nach einer zusammenfassenden Darstellung grundlegender Techniken suchen. Dieses praxisorientierte Buch bietet einen umfassenden Überblick über das Data Engineering und gibt Ihnen mit dem Data-Engineering-Lifecycle ein Framework an die Hand, das die Evaluierung und Auswahl der besten Technologien für reale Geschäftsprobleme erleichtert. Sie erfahren, wie Sie Systeme so planen und entwickeln, dass sie den Anforderungen Ihres Unternehmens und Ihrer Kunden optimal gerecht werden. Die Autoren Joe Reis und Matt Housley führen Sie durch den Data-Engineering-Lebenszyklus und zeigen Ihnen, wie Sie eine Vielzahl von Cloud-Technologien kombinieren können, um die Bedürfnisse von Datenkonsumenten zu erfüllen. Sie lernen, die Konzepte der Datengenerierung, -aufnahme, -orchestrierung, -transformation, -speicherung und -verwaltung anzuwenden, die in jeder Datenumgebung unabhängig von der verwendeten Technologie von entscheidender Bedeutung sind. Darüber hinaus erfahren Sie, wie Sie Data Governance und Sicherheit in den gesamten Datenlebenszyklus integrieren.
Materials Handbook
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Author : François Cardarelli
language : en
Publisher: Springer
Release Date : 2018-07-09
Materials Handbook written by François Cardarelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-09 with Technology & Engineering categories.
The unique and practical Materials Handbook (third edition) provides quick and easy access to the physical and chemical properties of very many classes of materials. Its coverage has been expanded to include whole new families of materials such as minor metals, ferroalloys, nuclear materials, food, natural oils, fats, resins, and waxes. Many of the existing families—notably the metals, gases, liquids, minerals, rocks, soils, polymers, and fuels—are broadened and refined with new material and up-to-date information. Several of the larger tables of data are expanded and new ones added. Particular emphasis is placed on the properties of common industrial materials in each class. After a chapter introducing some general properties of materials, each of twenty-four classes of materials receives attention in its own chapter. The health and safety issues connected with the use and handling of industrial materials are included. Detailed appendices provide additional information on subjects as diverse as crystallography, spectroscopy, thermochemical data, analytical chemistry, corrosion resistance, and economic data for industrial and hazardous materials. Specific further reading sections and a general bibliography round out this comprehensive guide. The index and tabular format of the book makes light work of extracting what the reader needs to know from the wealth of factual information within these covers. Dr. François Cardarelli has spent many years compiling and editing materials data. His professional expertise and experience combine to make this handbook an indispensable reference tool for scientists and engineers working in numerous fields ranging from chemical to nuclear engineering. Particular emphasis is placed on the properties of common industrial materials in each class. After a chapter introducing some general properties of materials, materials are classified as follows. ferrous metals and their alloys; ferroalloys; common nonferrous metals; less common metals; minor metals; semiconductors and superconductors; magnetic materials; insulators and dielectrics; miscellaneous electrical materials; ceramics, refractories and glasses; polymers and elastomers; minerals, ores and gemstones; rocks and meteorites; soils and fertilizers; construction materials; timbers and woods; fuels, propellants and explosives; composite materials; gases; liquids; food, oils, resin and waxes; nuclear materials. food materials