Mastering PostgreSQL 13 - Fourth Edition
Explore expert techniques such as advanced indexing and high availability to build scalable, reliable, and fault-tolerant database applications using PostgreSQL 13Key FeaturesMaster advanced PostgreSQL 13 concepts with the help of real-world datasets and examplesLeverage PostgreSQL's indexing features to fine-tune the performance of your queriesExtend PostgreSQL's functionalities to suit your organization's needs with minimal effortBook DescriptionThanks to its reliability, robustness, and high performance, PostgreSQL has become one of the most advanced open source databases on the market. This updated fourth edition will help you understand PostgreSQL administration and how to build dynamic database solutions for enterprise apps with the latest release of PostgreSQL, including designing both physical and technical aspects of the system architecture with ease.Starting with an introduction to the new features in PostgreSQL 13, this book will guide you in building efficient and fault-tolerant PostgreSQL apps. You'll explore advanced PostgreSQL features, such as logical replication, database clusters, performance tuning, advanced indexing, monitoring, and user management, to manage and maintain your database. You'll then work with the PostgreSQL optimizer, configure PostgreSQL for high speed, and move from Oracle to PostgreSQL. The book also covers transactions, locking, and indexes, and shows you how to improve performance with query optimization. You'll also focus on how to manage network security and work with backups and replication while exploring useful PostgreSQL extensions that optimize the performance of large databases.By the end of this PostgreSQL book, you'll be able to get the most out of your database by executing advanced administrative tasks.What You Will LearnGet well versed with advanced SQL functions in PostgreSQL 13Get to grips with administrative tasks such as log file management and monitoringWork with stored procedures and manage backup and recoveryEmploy replication and failover techniques to reduce data lossPerform database migration from Oracle to PostgreSQL with easeReplicate PostgreSQL database systems to create backups and scale your databaseManage and improve server security to protect your dataTroubleshoot your PostgreSQL instance to find solutions to common and not-so-common problemsWho this book is forThis database administration book is for PostgreSQL developers and database administrators and professionals who want to implement advanced functionalities and master complex administrative tasks with PostgreSQL 13. Prior experience in PostgreSQL and familiarity with the basics of database administration will assist with understanding key concepts covered in the book.
Chinese Computational Linguistics
This book constitutes the proceedings of the 19th China National Conference on Computational Linguistics, CCL 2020, held in Hainan, China, in October/November 2020.The 32 full and 2 short papers presented in this volume were carefully reviewed and selected from 99 submissions. They were organized in topical sections named: fundamental theory and methods of computational linguistics; information retrieval, dialogue and question answering; text generation and summarization; knowledge graph and information extraction; machine translation and multilingual information processing; minority language information processing; language resource and evaluation; social computing and sentiment analysis; and NLP applications.
Getting Structured Data from the Internet
Utilize web scraping at scale to quickly get unlimited amounts of free data available on the web into a structured format. This book teaches you to use Python scripts to crawl through websites at scale and scrape data from HTML and JavaScript-enabled pages and convert it into structured data formats such as CSV, Excel, JSON, or load it into a SQL database of your choice. This book goes beyond the basics of web scraping and covers advanced topics such as natural language processing (NLP) and text analytics to extract names of people, places, email addresses, contact details, etc., from a page at production scale using distributed big data techniques on an Amazon Web Services (AWS)-based cloud infrastructure. It book covers developing a robust data processing and ingestion pipeline on the Common Crawl corpus, containing petabytes of data publicly available and a web crawl data set available on AWS's registry of open data.Getting Structured Data from the Internet also includes a step-by-step tutorial on deploying your own crawlers using a production web scraping framework (such as Scrapy) and dealing with real-world issues (such as breaking Captcha, proxy IP rotation, and more). Code used in the book is provided to help you understand the concepts in practice and write your own web crawler to power your business ideas. What You Will LearnUnderstand web scraping, its applications/uses, and how to avoid web scraping by hitting publicly available rest API endpoints to directly get dataDevelop a web scraper and crawler from scratch using lxml and BeautifulSoup library, and learn about scraping from JavaScript-enabled pages using SeleniumUse AWS-based cloud computing with EC2, S3, Athena, SQS, and SNS to analyze, extract, and store useful insights from crawled pagesUse SQL language on PostgreSQL running on Amazon Relational Database Service (RDS) and SQLite using SQLalchemyReview sci-kit learn, Gensim, and spaCy to perform NLP tasks on scraped web pages such as name entity recognition, topic clustering (Kmeans, Agglomerative Clustering), topic modeling (LDA, NMF, LSI), topic classification (naive Bayes, Gradient Boosting Classifier) and text similarity (cosine distance-based nearest neighbors)Handle web archival file formats and explore Common Crawl open data on AWSIllustrate practical applications for web crawl data by building a similar website tool and a technology profiler similar to builtwith.comWrite scripts to create a backlinks database on a web scale similar to Ahrefs.com, Moz.com, Majestic.com, etc., for search engine optimization (SEO), competitor research, and determining website domain authority and rankingUse web crawl data to build a news sentiment analysis system or alternative financial analysis covering stock market trading signalsWrite a production-ready crawlerin Python using Scrapy framework and deal with practical workarounds for Captchas, IP rotation, and moreWho This Book Is ForPrimary audience: data analysts and scientists with little to no exposure to real-world data processing challenges, secondary: experienced software developers doing web-heavy data processing who need a primer, tertiary: business owners and startup founders who need to know more about implementation to better direct their technical team
Pro Google Kubernetes Engine
Discover methodologies and best practices for getting started with Google Kubernetes Engine (GKE). This book helps you understand how GKE provides a fully managed environment to deploy and operate containerized applications on Google Cloud infrastructure.You will see how Kubernetes makes it easier for users to manage clusters and the container ecosystem. And you will get detailed guidance on deploying and managing applications, handling administration of container clusters, managing policies, and monitoring cluster resources. You will learn how to operate the GKE environment through the GUI-based Google Cloud console and the "gcloud" command line interface. The book starts with an introduction to GKE and associated services. The authors provide hands-on examples to set up Container Registry and GKE Cluster, and you will follow through an application deployment on GKE. Later chapters focus on securing your GCP GKE environment, GKE monitoring anddashboarding, and CI/CD automation. All of the code presented in the book is provided in the form of scripts, which allow you to try out the examples and extend them in interesting ways.What You Will LearnUnderstand the main container services in GCP (Google Container Registry, Google Kubernetes Engine, Kubernetes Engine, Management Services)Perform hands-on steps to deploy, secure, scale, monitor, and automate your containerized environmentDeploy a sample microservices application on GKEDeploy monitoring for your GKE environmentUse DevOps automation in the CI/CD pipeline and integrate it with GKEWho This Book Is ForArchitects, developers, and DevOps engineers who want to learn Google Kubernetes Engine
Business Information Systems Workshops
This book constitutes revised papers from the five workshops which were held during June 2020 at the 23rd International Conference on Business Information Systems, BIS 2020. The conference was planned to take place in Colorado Springs, CO, USA. Due to the COVID-19 pandemic it changed to a virtual format. There was a total of 54 submissions to all workshops of which 26 papers were accepted for publication. The workshops included in this volume are: BITA 2020: 11th Workshop on Business and IT Alignment BSCT 2020: 3rd Workshop on Blockchain and Smart Contract Technologies DigEX 2020: 2nd International Workshop on transforming the Digital Customer Experience iCRM 2020: 5th International Workshop on Intelligent Data Analysis in Integrated Social CRM QOD 2020: 3rd Workshop on Quality of Open Data
VB.Net And SQL Client
This book is a series of books whose topics include ODBC, OLEDB and SQL Client. Each working with a specific sub topic: Dataset, Datatable or Dataview.
VB.Net and SQL Client
VB.Net and SQL Client. Working with the DataReader. Lots of source code inside.
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 9th International Conference on Computational Data and Social Networks, CSoNet 2020, held in Dallas, TX, USA, in December 2020. The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks.
SQL Server 2019 Alwayson
Get a fast start to using AlwaysOn, the SQL Server solution to high-availability and disaster recovery. This third edition is newly-updated to cover the 2019 editions of both SQL Server and Windows Server and includes strong coverage of implementing AlwaysOn Availability Groups on both Windows and Linux operating systems. The book provides a solid and accurate understanding of how to implement systems requiring consistent and continuous uptime, as well as how to troubleshoot those systems in order to keep them running and reliable. This edition is updated to account for all new major functionality and also includes coverage of implementing atypical configurations, such as clusterless and domain-independent Availability Groups, distributed Availability Groups, and implementing Availability Groups on Azure.The book begins with an introduction to high-availability and disaster recovery concepts such as Recovery Point Objectives (RPOs), Recovery Time Objectives (RTOs), availability levels, and the cost of downtime. You'll then move into detailed coverage of implementing and configuring the AlwaysOn feature set in order to meet the business objectives set by your organization. Content includes coverage on implementing clusters, building AlwaysOn failover clustered instances, and configuring AlwaysOn Availability Groups.SQL Server 2019 AlwaysOn is chock full of real-world advice on how to build and configure the most appropriate topology to meet the high-availability and disaster recovery requirements you are faced with, as well as how to use AlwaysOn Availability Groups to scale-out read-only workloads. This is a practical and hands-on book to get you started quickly in using one of the most talked-about SQL Server feature sets. What You Will Learn Understand high availability and disaster recovery in SQL Server 2019Build and configure a Windows Cluster in Windows Server 2019Create and configure an AlwaysOn failover clustered instanceImplement AlwaysOn Availability Groups and appropriately configure themImplement AlwaysOn Availability Groups on Linux serversConfigure Availability Groups on Azure IaaSAdminister AlwaysOn technologies post implementationUnderstand typical configurations, such as clusterless and distributed Availability Groups Who This Book Is For For Microsoft SQL Server database administrators who interested in growing their knowledge and skills in SQL Server's high-availability and disaster recovery feature set.
VBScript Code Warrior
Basic overview of ADO. Complete coverage a many different ways you can use ADO for reports.
VB.Net And SQL Client
This book is a series of books with topics on ODBC, OLEDB and SQL Client. The focus on working with a Dataset, Datatable or Dataview.
VB.Net IDE Code Using ADO
This VB.Net book is about using ADO, with IDE controls such as the DataGridView, Listview, MSFlexgrid and the OWC Spreadsheet.Hundreds of lines of code.
The Semantic Web - Iswc 2020
The two volume set LNCS 12506 and 12507 constitutes the proceedings of the 19th International Semantic Web Conference, ISWC 2020, which was planned to take place in Athens, Greece, during November 2-6, 2020. The conference changed to a virtual format due to the COVID-19 pandemic. The papers included in this volume deal with the latest advances in fundamental research, innovative technology, and applications of the Semantic Web, linked data, knowledge graphs, and knowledge processing on the Web. They were carefully reviewed and selected for inclusion in the proceedings as follows: Part I: Features 38 papers from the research track which were accepted from 170 submissions; Part II: Includes 22 papers from the resources track which were accepted from 71 submissions; and 21 papers in the in-use track, which had a total of 46 submissions.
SQL for Data Science
This textbook explains SQL within the context of data science and introduces the different parts of SQL as they are needed for the tasks usually carried out during data analysis. Using the framework of the data life cycle, it focuses on the steps that are very often given the short shift in traditional textbooks, like data loading, cleaning and pre-processing. The book is organized as follows. Chapter 1 describes the data life cycle, i.e. the sequence of stages from data acquisition to archiving, that data goes through as it is prepared and then actually analyzed, together with the different activities that take place at each stage. Chapter 2 gets into databases proper, explaining how relational databases organize data. Non-traditional data, like XML and text, are also covered. Chapter 3 introduces SQL queries, but unlike traditional textbooks, queries and their parts are described around typical data analysis tasks like data exploration, cleaning and transformation.Chapter 4 introduces some basic techniques for data analysis and shows how SQL can be used for some simple analyses without too much complication. Chapter 5 introduces additional SQL constructs that are important in a variety of situations and thus completes the coverage of SQL queries. Lastly, chapter 6 briefly explains how to use SQL from within R and from within Python programs. It focuses on how these languages can interact with a database, and how what has been learned about SQL can be leveraged to make life easier when using R or Python. All chapters contain a lot of examples and exercises on the way, and readers are encouraged to install the two open-source database systems (MySQL and Postgres) that are used throughout the book in order to practice and work on the exercises, because simply reading the book is much less useful than actually using it. This book is for anyone interested in data science and/or databases. It just demands a bit of computer fluency, butno specific background on databases or data analysis. All concepts are introduced intuitively and with a minimum of specialized jargon. After going through this book, readers should be able to profitably learn more about data mining, machine learning, and database management from more advanced textbooks and courses.
Multi-Cloud Architecture and Governance
A comprehensive guide to architecting, managing, implementing, and controlling multi-cloud environmentsKey FeaturesDeliver robust multi-cloud environments and improve your business productivityStay in control of the cost, governance, development, security, and continuous improvement of your multi-cloud solutionIntegrate different solutions, principles, and practices into one multi-cloud foundation and manage this architectureBook DescriptionMulti-cloud has emerged as one of the top cloud computing trends, with businesses wanting to reduce their reliance on only one vendor. But when organizations shift to multiple cloud services without a clear strategy, they may face certain difficulties, in terms of how to stay in control, how to keep all the different components secure, and how to execute the cross-cloud development of applications. This book combines best practices from different cloud adoption frameworks to help you find solutions to these problems.With step-by-step explanations of essential concepts and practical examples, you'll begin by planning the foundation, creating the architecture, designing the governance model, and implementing tools, processes, and technologies to manage multi-cloud environments. You'll then discover how to design workload environments using different cloud propositions, understand how to optimize the use of these cloud technologies, and automate and monitor the environments. As you advance, you'll delve into multi-cloud governance, defining clear demarcation models and management processes. Finally, you'll learn about managing identities in multi-cloud: who's doing what, why, when, and where.By the end of this book, you'll be able to create, implement, and manage multi-cloud architectures with confidenceWhat You Will LearnGet to grips with the core functions of multiple cloud platforms Deploy, automate, and secure different cloud solutions Design network strategy and get to grips with identity and access management for multi-cloud Design a landing zone spanning multiple cloud platforms Use automation, monitoring, and management tools for multi-cloud Understand multi-cloud management with the principles of BaseOps, FinOps, SecOps, and DevOps Define multi-cloud security policies and use cloud security tools Test, integrate, deploy, and release using multi-cloud CI/CD pipelinesWho this book is forThis book is for architects and lead engineers involved in architecting multi-cloud environments, with a focus on getting governance right to stay in control of developments in multi-cloud. Basic knowledge of different cloud platforms (Azure, AWS, GCP, VMWare, and OpenStack) and understanding of IT governance is necessary.
C++.Net and Odbc
This book is part of a series of books involving topics on SQL Client, OLEDB and ODBC with the focus on working with a Dataset or Datatable or Dataview.
Industrial Digital Transformation
Delve into industrial digital transformation and learn how to implement modern business strategies powered by digital technologies as well as organization and cultural optimizationKey FeaturesIdentify potential industry disruptors from various business domains and emerging technologiesLeverage existing resources to identify new avenues for generating digital revenueBoost digital transformation with cloud computing, big data, artificial intelligence (AI), and the Internet of Things (IoT)Book DescriptionDigital transformation requires the ability to identify opportunities across industries and apply the right technologies and tools to achieve results. This book is divided into two parts with the first covering what digital transformation is and why it is important. The second part focuses on how digital transformation works.After an introduction to digital transformation, you will explore the transformation journey in logical steps and understand how to build business cases and create productivity benefit statements. Next, you'll delve into advanced topics relating to overcoming various challenges. Later, the book will take you through case studies in both private and public sector organizations. You'll explore private sector organizations such as industrial and hi-tech manufacturing in detail and get to grips with public sector organizations by learning how transformation can be achieved on a global scale and how the resident experience can be improved. In addition to this, you will understand the role of artificial intelligence, machine learning and deep learning in digital transformation. Finally, you'll discover how to create a playbook that can ensure success in digital transformation.By the end of this book, you'll be well-versed with industrial digital transformation and be able to apply your skills in the real world.What you will learnGet up to speed with digital transformation and its important aspectsExplore the skills that are needed to execute the transformationFocus on the concepts of Digital Thread and Digital TwinUnderstand how to leverage the ecosystem for successful transformationGet to grips with various case studies spanning industries in both private and public sectorsDiscover how to execute transformation at a global scaleFind out how AI delivers value in the transformation journeyWho this book is forThis book is for IT leaders, digital strategy leaders, line-of-business leaders, solution architects, and IT business partners looking for digital transformation opportunities within their organizations. Professionals from service and management consulting firms will also find this book useful. Basic knowledge of enterprise IT and some intermediate knowledge of identifying digital revenue streams or internal transformation opportunities are required to get started with this book.
Improving the Quality of ABAP Code
Gain an in-depth understanding of the large number of common problems found in ABAP programs and have a robust methodology for fixing problems when you find them. This book also shows you how to prevent them from occurring in new programs.A large chunk of the world's biggest organizations use SAP software and virtually all of them have very large amounts of custom code. However, a lot of that custom code is not as good as it could be. In this book we look at why object-oriented programming is the basic building block for improved program quality and at the test-driven development that this enables. We cover the three pillars of clarity, stability, and high performance on which a high-quality ABAP program stands. You will then move on to the user interface, which needs its own set of standards for high quality. In the final chapters, you will learn about specialist topics such as user exits, making sure code will run on the latest releases of SAP, and how to add your own automated custom code quality checks. What You Will Learn Know why object-oriented programming and test-driven development are the cornerstones of high-quality custom code Ensure that the three pillars of clarity, stability, and high performance are fulfilled Make sure your applications are user friendlyEnsure that your custom code works on newer SAP releasesCreate your own custom code quality checks Who This Book Is ForABAP developers who started yesterday or have been programming for 20 years
Software Foundations for Data Interoperability and Large Scale Graph Data Analytics
This book constitutes refereed proceedings of the 4th International Workshop on Software Foundations for Data Interoperability, SFDI 2020, and 2nd International Workshop on Large Scale Graph Data Analytics, LSGDA 2020, held in Conjunction with VLDB 2020, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 full papers and 4 short papers were thoroughly reviewed and selected from 38 submissions. The volme presents original research and application papers on the development of novel graph analytics models, scalable graph analytics techniques and systems, data integration, and data exchange.
The Voice in the Machine
An examination of more than sixty years of successes and failures in developing technologies that allow computers to understand human spoken language.Stanley Kubrick's 1968 film 2001: A Space Odyssey famously featured HAL, a computer with the ability to hold lengthy conversations with his fellow space travelers. More than forty years later, we have advanced computer technology that Kubrick never imagined, but we do not have computers that talk and understand speech as HAL did. Is it a failure of our technology that we have not gotten much further than an automated voice that tells us to "say or press 1"? Or is there something fundamental in human language and speech that we do not yet understand deeply enough to be able to replicate in a computer? In The Voice in the Machine, Roberto Pieraccini examines six decades of work in science and technology to develop computers that can interact with humans using speech and the industry that has arisen around the quest for these technologies. He shows that although the computers today that understand speech may not have HAL's capacity for conversation, they have capabilities that make them usable in many applications today and are on a fast track of improvement and innovation.Pieraccini describes the evolution of speech recognition and speech understanding processes from waveform methods to artificial intelligence approaches to statistical learning and modeling of human speech based on a rigorous mathematical model--specifically, Hidden Markov Models (HMM). He details the development of dialog systems, the ability to produce speech, and the process of bringing talking machines to the market. Finally, he asks a question that only the future can answer: will we end up with HAL-like computers or something completely unexpected?
Interactive Storytelling
This book constitutes the refereed proceedings of the 13th International Conference on Interactive Digital Storytelling, ICIDS 2020, held in Bournemouth, UK, in November 2020. The 15 full papers and 8 short papers presented together with 5 posters, were carefully reviewed and selected from 70 submissions. The conference offers topics in game narrative and interactive storytelling, including the theoretical, technological, and applied design practices, narrative systems, storytelling technology, and humanities-inspired theoretical inquiry, empirical research and artistic expression.
Die 444 besten Easter Eggs von Alexa
Die 444 besten Easter Eggs von AlexaDiese Alexa-Sprachbefehle kennen Sie noch nicht! Jetzt mit weihnachtlichen Kommandos!Was haben eigentlich Easter Eggs (Ostereier) mit Alexa zu tun? ?hnlich wie bei Ostereiern, sind auch digitale Easter Eggs (lustige Gags, lustige Bemerkungen, witzige Zitate) im Inneren eines Systems versteckt. Man muss Sie suchen und entdecken. Jeder Anwender kennt sie von Google oder aus den unterschiedlichsten Computerprogrammen. Bei Software l瓣sst sich 羹ber sie meist ein Bonus oder ein geheimes Spiellevel freischalten. Bei Alexa gibt es nur eine witzige Antwort zu entdecken. Meist stecken hinter den versteckten Gimmicks die Entwickler der jeweiligen Software, die sich so ein ewiges Denkmal in der digitalen Welt setzen. Bei Alexa scheint es jedoch eher Absicht der Entwickler zu sein, da humorvolle Antworten dem System etwas Menschliches entlocken.Lustigste und tiefsinnige Antworten des SprachassistentenDabei ist es 瓣u?erst erstaunlich, mit wie viel Humor und Tiefgr羹ndigkeit der intelligente Sprachassistent daherkommt. Immer wieder stolpert der Anwender 羹ber durchaus witzige Antworten. Es ist es wirklich bemerkenswert, wie die Macher dem virtuellen Sprachassistenten so viel Menschliches einhauchen konnten. Oft sind die Antworten und die Qualit瓣t des Gesprochenen wirklich erstaunlich.Humor aus der CloudWas zun瓣chst nur mit einem kurzzeitigen Spa? begann, endete nun in dieser umfangreichen Auflistung der besten Easter Eggs. Auch wenn der Titel keinen tieferen Sinn versp羹rt, so macht es doch sehr viel Spa?, die F瓣higkeiten und die damit verbundene Schlagf瓣higkeit des Sprachsystems zu ergr羹nden. Sehen Sie somit keinen tiefgr羹ndigen Sinn in den folgenden Zeilen, vielmehr geht es um Spa? und Vergn羹gen. Zudem m羹ssen Sie als Nutzer von Alexa nicht ewig im Netz surfen, um die wirklich besten Easter Eggs zu finden. Updates: Immer auf dem neuesten StandNat羹rlich sind wie weiterhin auf der Suche nach lustigen und au?ergew繹hnliche Easter Eggs. Sofern Sie weitere Easter Eggs entdecken, freuen wir uns 羹ber eine kurze Nachricht per Mail. Entsprechend wird dieses Buch in regelm瓣?igen Abst瓣nden aktualisiert, um immer auf dem neuesten Stand zu sein. Nutzen Sie dazu auch unseren Update-Service: (Version 1.27).NEU: Die passende Seite zum Thema Sprachassistenten: Streamingz.deZugreifen: So genie?t man Medien heute!Auch unter Kindle Unlimited verf羹gbar!
Intelligent Data Engineering and Automated Learning - Ideal 2020
This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.
Ict Innovations 2020. Machine Learning and Applications
This book constitutes the refereed proceedings of the 12th International ICT Innovations Conference, ICT Innovations 2020, held in Skopje, North Macedonia, in September 2020.The 12 full papers and 6 short papers presented were carefully reviewed and selected from 60 submissions. The focal point of the volume is machine learning and applications in spheres of business, science and technology.
Intelligent Data Engineering and Automated Learning - Ideal 2020
This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.
Business Intelligence and Big Data
The twenty-first century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The questions facing us today are: What does success mean? Is success a matter of chance and luck or perhaps is success a category that can be planned and properly supported?Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers, and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization.The book discusses business intelligence (BI) and Big Data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as: Analysis and interpretation of the essence of BI and BD Decision support Potential areas of BI and BD utilization in organizations Factors determining success with using BI and BD The role of BI and BD in value creation for organizations Identifying barriers and constraints related to BI and BD design and implementation The book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes and business performance, and creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success.
Beyond Planar Graphs
Chapter 1: Introduction.- Chapter 2: Quantitative Restrictions on Crossing Patterns.- Chapter 3: Quasi-planar Graphs.- Chapter 4: 1-Planar Graphs.- Chapter 5: Algorithms for 1-planar Graphs.- Chapter 6: ^= 2.- Chapter 8: Fan-Planarity.- Chapter 9: Right Angle Crossing Drawings of Graphs.- Chapter 10: Angular Resolutions.- Chapter 11: Crossing Layout in Non-Planar Graph Drawings.- Chapter 12: Beyond Clustered Planarity.- Chapter: Simultaneous Embedding.
Database and Expert Systems Applications
The double volumes LNCS 12391-12392 constitutes the papers of the 31st International Conference on Database and Expert Systems Applications, DEXA 2020, which will be held online in September 2020. The 38 full papers presented together with 20 short papers plus 1 keynote papers in these volumes were carefully reviewed and selected from a total of 190 submissions.
Data Science6th International Conference of Pioneering Computer Scientists, Engineers and Educators, Icpcsee 2020, Taiyuan, China, September 18-21, 2020, Proceedings, Part I
This two volume set (CCIS 1257 and 1258) constitutes the refereed proceedings of the 6th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2020 held in Taiyuan, China, in September 2020. The 98 papers presented in these two volumes were carefully reviewed and selected from 392 submissions. The papers are organized in topical sections: database, machine learning, network, graphic images, system, natural language processing, security, algorithm, application, and education.The chapter "Highly Parallel SPARQL Engine for RDF" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Transactions on Large-Scale Data- And Knowledge-Centered Systems XLIII
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.This, the 43rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include classification tasks, machine learning algorithms, top-k queries, business process redesign and a knowledge capitalization framework.
Transactions on Large-Scale Data- And Knowledge-Centered Systems XLIV
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 44th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised and extended papers selected from the 35th conference on Data Management - Principles, Technologies and Applications, BDA 2019. The topics covered include big data, graph data streams, workflow execution in the cloud, privacy in crowdsourcing, secure distributed computing, machine learning, and data mining for recommendation systems.
Business Process Management: Blockchain and Robotic Process Automation Forum
This book constitutes the proceedings of the Blockchain and Robotic Process Automation (RPA) Forum which was held as part of the 18th International Conference on Business Process Management, BPM 2020. The conference was planned to take place in Seville, Spain, in September 2020. Due to the COVID-19 pandemic the conference took place virtually.The Blockchain Forum and the RPA Forum have in common that they are centered around an emerging and exciting technology. The blockchain is a sophisticated distributed ledger technology, while RPA software allows for mimicking human, repetitive actions. Each of these have the potential to fundamentally change how business processes are being orchestrated and executed in practice. The BPM community has embraced these technologies as objects of analysis, design, development, and evaluation.The 14 full plus one short paper presented in this volume were carefully reviewed and selected from a total of 28 submissions.
Privacy in Statistical Databases
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2020, held in Tarragona, Spain, in September 2020 under the sponsorship of the UNESCO Chair in Data Privacy.The 25 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized into the following topics: privacy models; microdata protection; protection of statistical tables; protection of interactive and mobility databases; record linkage and alternative methods; synthetic data; data quality; and case studies.The Chapter "Explaining recurrent machine learning models: integral privacy revisited" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Mathematical Optimization Theory and Operations Research
This book constitutes refereed proceedings of the 19th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2020, held in Novosibirsk, Russia, in July 2020. Due to the COVID-19 pandemic the conference was held online. The 25 full papers and 8 short papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. The papers in the volume are organised according to the following topical headings: ​combinatorial optimization; mathematical programming; global optimization; game theory and mathematical economics; heuristics and metaheuristics; machine learning and data analysis.
Understanding Oracle Apex 20 Application Development
This book shows developers and Oracle professionals how to build practical, non-trivial web applications using Oracle's rapid application development environment - Application Express (APEX). This third edition Is revised to cover the new features and user interface experience found in APEX 20. Interactive grids and form regions are two of the newer aspects of APEX covered in this edition. The book is targeted at those who are new to APEX and just beginning to develop real projects for deployment, as well as those who are familiar with APEX and want a deeper understanding. The book takes you through the development of a demo web application that illustrates the concepts all APEX programmers should know. This book introduces the world of APEX properties, explaining the functionality supported by each page component as well as the techniques developers use to achieve that functionality. Topics include conditional formatting, user-customized reports, data entry forms, concurrency and lost updates, and security control. Specific attention is given in the book to the thought process involved in choosing and assembling APEX components and features to deliver a specific result. Understanding Oracle APEX 20 Application Development, 3rd Edition is the ideal book to take you from an understanding of the individual pieces of APEX to an understanding of how those pieces are assembled into polished applications.What You Will LearnBuild attractive, highly functional web apps from the ground upEnhance and customize pages created by the APEX wizardsUnderstand the security implications of page designWrite PL/SQL code for process activity and verificationBuild complex components such as forms and interactive gridsWho This Book Is ForDevelopers new to APEXwho desire a strong fundamental understanding of how APEX applications work. For existing developers and database administrators desiring to mine the most value from APEX by improving their development techniques.
Monitoring Microservices and Containerized Applications
Discover the methodologies and best practices for getting started with container services monitoring using Prometheus, AppDynamics, and Dynatrace. The book begins with the basics of working with the containerization and microservices architecture while establishing the need for monitoring and management technologies. You'll go through hands-on deployment, configuration, and best practices for Prometheus. Next, you'll delve deeper into monitoring of container ecosystems for availability, performance, and logs, and then cover the reporting capabilities of Prometheus. Further, you'll move on to advanced topics of extending Prometheus including how to develop new use cases and scenarios. You'll then use enterprise tools such as AppDynamics and Wavefront to discover deeper application monitoring best practices. You'll conclude with fully automated deployment of the monitoring and management platforms integrated with the container ecosystem using infrastructure-as -codetools such as Jenkins, Ansible and Terraform. The book provides sample code and best practices for you to look at container monitoring from a holistic viewpoint. This book is a good starting point for developers, architects, and administrators who want to learn about monitoring and management of cloud native and microservices containerized applications. What You Will LearnExamine the fundamentals of container monitoringGet an overview of the architecture for Prometheus and Alert Manager Enable Prometheus monitoring for containers Monitor containers using Wavefront Use the guidelines on container monitoring with enterprise solutions AppDynamics and Wavefront Who This Book Is For Software developers, system administrators, and DevOps engineers working for enterprise customers who want to use monitoring solutions for their container ecosystems.
Executing Data Quality Projects
Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work - with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations - for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before.
Data Stewardship
Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data--moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered.Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort. It includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards.
Advanced Platform Development with Kubernetes
Leverage Kubernetes for the rapid adoption of emerging technologies. Kubernetes is the future of enterprise platform development and has become the most popular, and often considered the most robust, container orchestration system available today. This book focuses on platforming technologies that power the Internet of Things, Blockchain, Machine Learning, and the many layers of data and application management supporting them. Advanced Platform Development with Kubernetes takes you through the process of building platforms with these in-demand capabilities. You'll progress through the development of Serverless, CICD integration, data processing pipelines, event queues, distributed query engines, modern data warehouses, data lakes, distributed object storage, indexing and analytics, data routing and transformation, query engines, and data science/machine learning environments. You'll also see how to implement and tie together numerous essential and trending technologies including: Kafka, NiFi, Airflow, Hive, Keycloak, Cassandra, MySQL, Zookeeper, Mosquitto, Elasticsearch, Logstash, Kibana, Presto, Mino, OpenFaaS, and Ethereum. The book uses Golang and Python to demonstrate the development integration of custom container and Serverless functions, including interaction with the Kubernetes API. The exercises throughout teach Kubernetes through the lens of platform development, expressing the power and flexibility of Kubernetes with clear and pragmatic examples. Discover why Kubernetes is an excellent choice for any individual or organization looking to embark on developing a successful data and application platform. What You'll Learn Configure and install Kubernetes and k3s on vendor-neutral platforms, including generic virtual machines and bare metalImplement an integrated development toolchain for continuous integration and deploymentUse data pipelines with MQTT, NiFi, Logstash, Kafka and ElasticsearchInstall a serverless platform with OpenFaaSExplore blockchain network capabilities with Ethereum Support a multi-tenant data science platform and web IDE with JupyterHub, MLflow and Seldon CoreBuild a hybrid cluster, securely bridging on-premise and cloud-based Kubernetes nodes Who This Book Is ForSystem and software architects, full-stack developers, programmers, and DevOps engineers with some experience building and using containers. This book also targets readers who have started with Kubernetes and need to progress from a basic understanding of the technology and "Hello World" example to more productive, career-building projects.
Empower Decision Makers with SAP Analytics Cloud
Discover the capabilities and features of SAP Analytics Cloud to draw actionable insights from a variety of data, as well as the functionality that enables you to meet typical business challenges. With this book, you will work with SAC and enable key decision makers within your enterprise to deliver crucial business decisions driven by data and key performance indicators. Along the way you'll see how SAP has built a strong repertoire of analytics products and how SAC helps you analyze data to derive better business solutions. This book begins by covering the current trends in analytics and how SAP is re-shaping its solutions. Next, you will learn to analyze a typical business scenario and map expectations to the analytics solution including delivery via a single platform. Further, you will see how SAC as a solution meets each of the user expectations, starting with creation of a platform for sourcing data from multiple sources, enabling self-service for a spectrum of business roles, across time zones and devices. There's a chapter on advanced capabilities of predictive analytics and custom analytical applications. Later there are chapters explaining the security aspects and their technical features before concluding with a chapter on SAP's roadmap for SAC.Empower Decision Makers with SAP Analytics Cloud takes a unique approach of facilitating learning SAP Analytics Cloud by resolving the typical business challenges of an enterprise. These business expectations are mapped to specific features and capabilities of SAC, while covering its technical architecture block by block.What You Will Learn Work with the features and capabilities of SAP Analytics Cloud Analyze the requirements of a modern decision-support system Use the features of SAC that make it a single platform for decision support in a modern enterprise. See how SAC provides a secure and scalable platform hosted on the cloud Who This Book Is For Enterprise architects, SAP BI analytic solution architects, and developers.
Creating Good Data
Create good data from the start, rather than fixing it after it is collected. By following the guidelines in this book, you will be able to conduct more effective analyses and produce timely presentations of research data.Data analysts are often presented with datasets for exploration and study that are poorly designed, leading to difficulties in interpretation and to delays in producing meaningful results. Much data analytics training focuses on how to clean and transform datasets before serious analyses can even be started. Inappropriate or confusing representations, unit of measurement choices, coding errors, missing values, outliers, etc., can be avoided by using good dataset design and by understanding how data types determine the kinds of analyses which can be performed. This book discusses the principles and best practices of dataset creation, and covers basic data types and their related appropriate statistics and visualizations. A key focus of the book is why certain data types are chosen for representing concepts and measurements, in contrast to the typical discussions of how to analyze a specific data type once it has been selected. What You Will Learn Be aware of the principles of creating and collecting dataKnow the basic data types and representationsSelect data types, anticipating analysis goalsUnderstand dataset structures and practices for analyzing and sharingBe guided by examples and use cases (good and bad)Use cleaning tools and methods to create good data Who This Book Is For Researchers who design studies and collect data and subsequently conduct and report the results of their analyses can use the best practices in this book to produce better descriptions and interpretations of their work. In addition, data analysts who explore and explain data of other researchers will be able to create better datasets.
Database Systems for Advanced Applications. Dasfaa 2020 International Workshops
The LNCS 12115 constitutes the workshop papers which were held also online in conjunction with the 25th International Conference on Database Systems for Advanced Applications in September 2020.The complete conference includes 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions.DASFAA 2020 presents this year following five workshops: The 7th International Workshop on Big Data Management and Service (BDMS 2020) The 6th International Symposium on Semantic Computing and Personalization (SeCoP 2020) The 5th Big Data Quality Management (BDQM 2020) The 4th International Workshop on Graph Data Management and Analysis (GDMA 2020) The 1st International Workshop on Artificial Intelligence for Data Engineering (AIDE 2020)
Algorithmic Aspects in Information and Management
This volume constitutes the proceedings of the 14th International Conference on Algorithmic Aspects in Information and Management, AAIM 2020, held in Jinhua, China in August 2020. The 39 full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers deal with emerging important algorithmic problems with a focus on the fundamental background, theoretical technology development, and real-world applications associated with information and management analysis, modeling and data mining. Special considerations are given to algorithmic research that was motivated by real-world applications.
Big Data Analytics and Knowledge Discovery
The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.
Brain Informatics
This book constitutes the refereed proceedings of the 13th International Conference on Brain Informatics, BI 2020, held in Padua, Italy, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 33 full papers were carefully reviewed and selected from 57 submissions. The papers are organized in the following topical sections: cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain-inspired computing.
Bigquery for Data Warehousing
Create a data warehouse, complete with reporting and dashboards using Google's BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization.BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks.What You Will LearnDesign a data warehouse for your project or organizationLoad data from a variety of external and internal sourcesIntegrate other Google Cloud Platform services for more complex workflowsMaintain and scale your data warehouse as your organization growsAnalyze, report, and create dashboards on the information in the warehouseBecome familiar with machine learning techniques using BigQuery MLWho This Book Is ForDevelopers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers.
Artificial Intelligence with Python Cookbook
Work through practical recipes to learn how to solve complex machine learning and deep learning problems using PythonKey featuresGet up and running with artificial intelligence in no time using hands-on problem-solving recipesExplore popular Python libraries and tools to build AI solutions for images, text, sounds, and imagesImplement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree search, and much moreBook DescriptionArtificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you'll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you'll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production.What you will learnImplement data preprocessing steps and optimize model hyperparametersDelve into representational learning with adversarial autoencodersUse active learning, recommenders, knowledge embedding, and SAT solversGet to grips with probabilistic modeling with TensorFlow probabilityRun object detection, text-to-speech conversion, and text and music generationApply swarm algorithms, multi-agent systems, and graph networksGo from proof of concept to production by deploying models as microservicesUnderstand how to use modern AI in practiceWho this book is forThis AI machine learning book is for Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. You'll also find this book useful if you're looking for state-of-the-art solutions to perform different machine learning tasks in various use cases. Basic working knowledge of the Python programming language and machine learning concepts will help you to work with code effectively in this book.
Visual Privacy Management
​Privacy is a burden for most organizations, the more complex and wider an organization is, the harder to manage and enforce privacy is.GDPR and other regulations on privacy impose strict constraints that must be coherently enforced, considering also privacy needs of organization and their users. Furthermore, organizations should allow their users to express their privacy needs easily, even when the process that manages users' data is complex and involves multiple organizations.Many research work consider the problem using simplistic examples, with solutions proposed that never actually touch pragmatic problems of real, large organizations, with thousands of users and terabytes of personal and sensitive data.This book faces the privacy management problem targeting actual large organizations, such as public administrations, including stakeholders in the process of definition of the solution and evaluating the results with its actual integration in four large organizations. The contribution of this book is twofold: a privacy platform that can be customized and used to manage privacy in large organizations; and the process for the design of such a platform, from a state-of-the-art survey on privacy regulations, through the definition of its requirements, its design and its architecture, until the evaluation of the platform.
