Perspectives in Business Informatics Research
This book constitutes the proceedings of the 21st International Conference on Perspectives in Business Informatics Research, BIR 2022, which took place in Rostock, Germany, in September 2022. The central theme of BIR 2022 was "Business Informatics for Sustainable Innovation". Achieving sustainability requires a multi-perspective approach taking organizational, economic, and technical aspects into account. In a world of cloud computing, social networks and big data, additional challenges for business informatics and the design of information systems architectures are introduced. To deal with these challenges, a close cooperation of researchers from different disciplines such as information systems, business informatics, and computer science is required.The 14 papers presented in this volume were carefully reviewed and selected from 41 submissions. They were organized in topical sections as follows: Information system development; modeling methods and assistance; applications and technologies; and digital business.
Ocaml Scientific Computing
This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments.To this end, the book is divided into three parts, each focusing on a different area. Part I begins by introducing how basic numerical techniques are performed in OCaml, including classical mathematical topics (interpolation and quadrature), statistics, and linear algebra. It moves on from using only scalar values to multi-dimensional arrays, introducing the tensor and Ndarray, core data types in any numerical computing system. It concludes with two more classical numerical computing topics, the solution ofOrdinary Differential Equations (ODEs) and Signal Processing, as well as introducing the visualization module we use throughout this book. Part II is dedicated to advanced optimization techniques that are core to most current popular data science fields. We do not focus only on applications but also on the basic building blocks, starting with Algorithmic Differentiation, the most crucial building block that in turn enables Deep Neural Networks. We follow this with chapters on Optimization and Regression, also used in building Deep Neural Networks. We then introduce Deep Neural Networks as well as topic modelling in Natural Language Processing (NLP), two advanced and currently very active fields in both industry and academia. Part III collects a range of case studies demonstrating how you can build a complete numerical application quickly from scratch using Owl. The cases presented include computer vision and recommender systems. This book aims at anyone with a basic knowledge of functional programming and a desire to explore the world of scientific computing, whether to generally explore the field in the round, to build applications for particular topics, or to deep-dive into how numerical systems are constructed. It does not assume strict ordering in reading - readers can simply jump to the topic that interests them most.
Research Challenges in Information Science: Ethics and Trustworthiness in Information Science
This book constitutes the proceedings of the 16th International Conference on Research Challenges in Information Sciences, RCIS 2022, which took place in Barcelona, Spain, during May 17-20, 2022. It focused on the special theme "Ethics and Trustworthiness in Information Science". The scope of RCIS is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice. The 35 full papers presented in this volume were carefully reviewed and selected from a total 100 submissions. The 18 Forum papers are based on 11 Forum submissions, from which 5 were selected, and the remaining 13 were transferred from the regular submissions. The 6 Doctoral Consortium papers were selected from 10 submissions to the consortium. The contributions were organized in topical sections named: Data Science and Data Management; Information Search and Analysis; Business Process Management; Business Process Mining; Digital Transformation and Smart Life; Conceptual Modelling and Ontologies; Requirements Engineering; Model-Driven Engineering; Machine Learning Applications. In addition, two-page summaries of the tutorials can be found in the back matter.
SAP S/4hana Systems in Hyperscaler Clouds
This book helps SAP architects and SAP Basis administrators deploy and operate SAP S/4HANA systems on the most common public cloud platforms. Market-leading cloud offerings are covered, including Amazon Web Services, Microsoft Azure, and Google Cloud. You will gain an end-to-end understanding of the initial implementation of SAP S/4HANA systems on those platforms. You will learn how to move away from the big monolithic SAP ERP systems and arrive at an environment with a central SAP S/4HANA system as the digital core surrounded by cloud-native services.The book begins by introducing the core concepts of Hyperscaler cloud platforms that are relevant to SAP. You will learn about the architecture of SAP S/4HANA systems on public cloud platforms, with specific content provided for each of the major platforms. The book simplifies the deployment of SAP S/4HANA systems in public clouds by providing step-by-step instructions and helping you deal with thecomplexity of such a deployment. Content in the book is based on best practices, industry lessons learned, and architectural blueprints, helping you develop deep insights into the operations of SAP S/4HANA systems on public cloud platforms. Reading this book enables you to build and operate your own SAP S/4HANA system in the public cloud with a minimum of effort.What You Will LearnChoose the right Hyperscaler platform for your future SAP S/4HANA workloadsStart deploying your first SAP S/4HANA system in the public cloudAvoid typical pitfalls during your implementationApply and leverage cloud-native services for your SAP S/4HANA systemSave costs by choosing the right architecture and build a robust architecture for your most critical SAP systemsMeet your business' criteria for availability and performance by having the right sizing in placeIdentify further use cases whenoperating SAP S/4HANA in the public cloudWho This Book Is ForSAP architects looking for an answer on how to move SAP S/4HANA systems from on-premises into the cloud; those planning to deploy to one of the three major platforms from Amazon Web Services, Microsoft Azure, and Google Cloud Platform; and SAP Basis administrators seeking a detailed and realistic description of how to get started on a migration to the cloud and how to drive that cloud implementation to completion
Linking Theory and Practice of Digital Libraries
This book constitutes the proceedings of the 26th International Conference on Theory and Practice of Digital Libraries, TPDL 2022, which took place in Padua, Italy, in September 2022. The 18 full papers, 27 short papers and 15 accelerating innovation papers included in these proceedings were carefully reviewed and selected from 107 submissions. They focus on digital libraries and associated technical, practical, and social issues.
Fundamentals of Enterprise Architecture Management
This textbook provides a comprehensive, holistic, scientifically precise, and practically relevant description of Enterprise Architecture Management (EAM). Based on state-of-the-art concepts, it also addresses current trends like disruptive digitization or agile methods. The book is structured in five chapters. The first chapter offers a comprehensive overview of EAM. It addresses questions like: what does EAM mean, what is the history of EAM, why do enterprises need EAM, what are its goals, and how is it related to digitalization? It also includes a short overview of essential EAM standards and literature. The second chapter provides an overview of Enterprise Architecture (EA). It starts with clarifying basic terminology and the difference between EA and EAM. It also gives a short summary of existing EA frameworks and methods for structuring the digital ecosystem into layers and views. The third chapter addresses the strategic and tactical context of the EAM capabilityin an enterprise. It defines essential terms and parameters in the context of enterprise strategy and tactics as well as the operative, organizational context of EAM. The fourth chapter specifies the detailed goals, processes, functions, artifacts, roles and tools of EAM, building the basis for an EAM process framework that provides a comprehensive overview of EAM processes and functions. Closing the circle, the last chapter describes how to evaluate EAM in an enterprise. It starts by laying out core terminology, like "metric" and "strategic performance measurement system" and ends with a framework that integrates the various measuring areas in the context of EA and EAM. This textbook focuses on two groups: First, EAM scholars, ie bachelor or master students of Business Information Systems, Business Administration or Computer Science. And second, EAM practitioners working in the field of IT strategy or EA who need a reliable, scientifically solid, and practically proven state-of-the-art description of essential EAM methods.
Emerging Technology Beyond 2035
This report presents the development and implementation of a technology assessment process to help the Army understand the implications of key emerging technologies that could be crucial to Army missions in the years 2035 to 2050. This work aims to assist the Army for shifting operational environments, such as operations in extreme weather conditions. Emerging technologies might help the Army succeed in key missions and promote U.S. interests.
Business Intelligence
This book constitutes the proceedings of the 7th International Conference on Business Intelligence, CBI 2022, which took place in Khouribga, Morocco, during May 26-28, 2022. The 23 full papers included in this book were carefully reviewed and selected from a total of 68 submissions. They were organized in topical sections as follows: decision support and artificial intelligence; business intelligence and database; and optimization and dynamic programming.
Digital Transformation in Norwegian Enterprises
This open access book presents a number of case studies on digital transformation in Norway, one of the fore-runners in the digital progress index established by the European Commission in 2020. They explore the process of adoption, diffusion and value generation from digital technologies, and how the use of different digital solutions has enabled Norwegian enterprises to digitally transform their operations and business models.The book starts with an introductory chapter summarizing a vast body of literature in order to synthesize what is already known about digital transformation before exploring the Norwegian context in more detail. Then a series of case studies from the private and public sector in Norway is presented. They document a process perspective which describes the sequence of events during and after adoption of digital solutions, as well as the types of business value that were realized. Through these single studies, the process of digital transformation is illustrated, a number of key findings highlighted, and eventually theoretical and practical recommendations based on these cases emphasized. The book closes with a brief overview of some emerging technologies, and comments on how they are likely to change different sectors. Digital transformation has been one of the priority areas for the Norwegian government over the past years and puts Norwegian enterprises upfront in adopting novel technologies and utilizing them for achieving organizational goals. This experience accumulated over the years makes the Norwegian context a particularly interesting one in understanding how private and public organizations make use of new digital solutions, what lessons can be learnt during the process, and what are some of the key success and failure factors. This way the book is written for practitioners who are currently involved in digital transformation projects in their organizations, researchers of information systems and management, aswell as master students in degrees of informatics and technology management.
Emerging Technologies in Computer Engineering: Cognitive Computing and Intelligent Iot
This book constitutes the refereed proceedings of the 5th International Conference on Emerging Technologies in Computer Engineering, ICETCE 2021, held in Jaipur, India, in February 2022.The 40 revised full papers along with 20 short papers presented were carefully reviewed and selected from 235 submissions. The papers are organized according to the following topical headings: ​cognitive computing; Internet of Things (IoT); machine learning and applications; soft computing; data science and big data analytics; blockchain and cyber security.
Data Warehouse Systems
With this textbook, Vaisman and Zim獺nyi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details "Implementation and Deployment," including physical design, ETL and data warehouse design methodologies. Part III covers "Advanced Topics" and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQLdatabase systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. "I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition."From the foreword by Panos Vassiliadis, University of Ioannina, Greece.
Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs
This book constitutes the proceedings of the 8th International Conference on Decision Support Systems Technologies, ICDSST 2022, held during May 23-25, 2022.The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main aim of this year's conference is to investigate the role DSS and related technologies can play in mitigating the impact of pandemics and post-crisis recovery. The 15 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections as follows: decision support addressing modern industry; decision support addressing business and societal needs, and multiple criteria approaches.
Bioinformatics with Python Cookbook - Third Edition
Discover modern, next-generation sequencing libraries from the powerful Python ecosystem to perform cutting-edge research and analyze large amounts of biological dataKey Features: Perform complex bioinformatics analysis using the most essential Python libraries and applicationsImplement next-generation sequencing, metagenomics, automating analysis, population genetics, and much moreExplore various statistical and machine learning techniques for bioinformatics data analysisBook Description: Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python.This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you'll explore the application of machine learning algorithms in bioinformatics.By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.What You Will Learn: Become well-versed with data processing libraries such as NumPy, pandas, arrow, and zarr in the context of bioinformatic analysisInteract with genomic databasesSolve real-world problems in the fields of population genetics, phylogenetics, and proteomicsBuild bioinformatics pipelines using a Galaxy server and SnakemakeWork with functools and itertools for functional programmingPerform parallel processing with Dask on biological dataExplore principal component analysis (PCA) techniques with scikit-learnWho this book is for: This book is for bioinformatics analysts, data scientists, computational biologists, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems. Working knowledge of the Python programming language is expected. Basic knowledge of biology will also be helpful.
Business Process Management Forum
This book constitutes the proceedings of the BPM Forum held at the 20th International Conference on Business Process Management, BPM 2022, which took place in M羹nster, Germany, in September 2022. The BPM Forum hosts innovative research which has a high potential of stimulating discussions. The papers selected for the forum are expected to showcase fresh ideas from exciting and emerging topics in BPM, even if they are not yet as mature as the regular papers at the conference. The 13 full papers included in this volume were carefully reviewed and selected from 98 submissions. The papers were organized in topical sections named: modeling and design; process mining; and predictive process monitoring.
Business Process Management: Blockchain, Robotic Process Automation, and Central and Eastern Europe Forum
This book constitutes the proceedings of the Blockchain, Robotic Process Management (RPA), and Central and Eastern Europe (CEE) Forum which were held as part of the 20th International Conference on Business Process Management, BPM 2022, which took place in M羹nster, Germany, during September 11-15, 2022. The Blockchain Forum is dealing with techniques for and applications of blockchains, distributed ledger technologies, and related topics. "The RPA Forum brings together researchers from various communities to discuss challenges, opportunities, and new ideas related to robotic process automation and its application to business processes in private and public sectors." The CEE Forum provides a discussion platform for BPM academics from Central and Eastern Europe to disseminate their research, compare results and share experiences. The 20 papers presented in this volume were carefully reviewed and selected from a total of 40 submissions.
Model-Driven Development of Akoma Ntoso Application Profiles
This book presents a model-driven approach for creating a national application profile of the international legislative document standard Akoma Ntoso (AKN). AKN is an XML-based document standard that serves as the basis for modern machine-readable and fully digital legislative and judicial processes. The described model-driven development approach ensures consistent and error-proof application of AKN concepts and types, even when using different software tools. It allows for easy maintenance, is self-documenting, and facilitates stakeholder validation with nontechnical legal experts. The resulting application profile remains fully compliant to and compatible with AKN. For the sake of illustration, the approach is paradigmatically applied to the German federal legislative process, as a corresponding approach was used in the creation of the German AKN application profile, LegalDocML.de. We discuss how the methodology yields a model, schema definition and specification that correspond to the artefacts created by LegalDocML.de, using examples from Germany. The book is of interest to both legal and technical project teams on the cusp of introducing AKN in a legislative domain and intended as a practical guideline for teams preparing to create a custom application profile for their own domain. Furthermore, it can serve as both a resource and an inspiration for similar and yet to be developed methodologies in the public sector, the health sector or in defense, where international standardization and interoperability efforts are to be applied to a local level.
Azure Data Engineering Cookbook - Second Edition
Nearly 80 recipes to help you collect and transform data from multiple sources into a single data source, making it way easier to perform analytics on the dataKey Features: Build data pipelines from scratch and find solutions to common data engineering problemsLearn how to work with Azure Data Factory, Data Lake, Databricks, and Synapse AnalyticsMonitor and maintain your data engineering pipelines using Log Analytics, Azure Monitor, and Azure PurviewBook Description: The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure.You'll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You'll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you'll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview.By the end of this book, you'll be able to build superior data engineering pipelines along with having an invaluable go-to guide.What You Will Learn: Process data using Azure Databricks and Azure Synapse AnalyticsPerform data transformation using Azure Synapse data flowsPerform common administrative tasks in Azure SQL DatabaseBuild effective Synapse SQL pools which can be consumed by Power BIMonitor Synapse SQL and Spark pools using Log AnalyticsTrack data lineage using Microsoft Purview integration with pipelinesWho this book is for: This book is for data engineers, data architects, database administrators, and data professionals who want to get well versed with the Azure data services for building data pipelines. Basic understanding of cloud and data engineering concepts will help in getting the most out of this book.
Chinese Computational Linguistics
This book constitutes the proceedings of the 21st China National Conference on Computational Linguistics, CCL 2022, held in Nanchang, China, in October 2022.The 22 full English-language papers in this volume were carefully reviewed and selected from 293 Chinese and English submissions.The conference papers are categorized into the following topical sub-headings: Linguistics and Cognitive Science; 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; NLP Applications.
Data Science Concepts and Techniques with Applications
This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.
Recent Trends in Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers of the 10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021, held in Tbilisi, Georgia, in December 2021. Due to the COVID-19 pandemic the conference was held in hybrid mode. The 17 full papers were carefully reviewed and selected from 118 submissions, out of which 92 were sent to peer review. The papers are organized in topical sections on ​natural language processing; computer vision; data analysis and machine learning; social network analysis; theoretical machine learning and optimisation.
Enterprise Systems Architecture
Enhance your technical and business skills to better manage your organization's technology ecosystem. This book aims to explain how to align the technology landscape to service your company's business operating model. The book begins by exploring different architectural approaches before taking a deep dive into multiple layers of the architectural stack and the methodology of each component. You'll also learn about the many products delivered by enterprise architecture. To complete the book, author Daljit Banger delves into the various roles and responsibilities of an enterprise architect. After completing Enterprise Systems Architecture, you will understand how to develop an ICT (Information Communication Technology) strategy to meet the needs of your organization. What Will You Learn Gain a complete understanding of enterprise architectureConceptualize the enterprise ecosystem using the EsA canvasMaster the products and services of an enterprise architecture function Who This Book Is For Architects (Enterprise, Solution, or Technical), CTOs, Business Analysts, or any stakeholder in delivering technology services to their organization.
Data Science and Analytics for Smes
Master the tricks and techniques of business analytics consulting, specifically applicable to small-to-medium businesses (SMEs). Written to help you hone your business analytics skills, this book applies data science techniques to help solve problems and improve upon many aspects of a business' operations. SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing with the ongoing digital revolution. The topics covered in the books will help to provide the knowledge leverage needed for implementing data science in small business. The demand of small business for data analytics are in conjunction with the growing number of freelance data science consulting opportunities; hence this book will provide insight on how to navigate this new terrain.This book uses a do-it-yourself approach to analytics and introduces tools that are easily available online and are non-programming based. Data science will allow SMEs to understand their customer loyalty, market segmentation, sales and revenue increase etc. more clearly. Data Science and Analytics for SMEs is particularly focused on small businesses and explores the analytics and data that can help them succeed further in their business. What You'll LearnCreate and measure the success of their analytics projectStart your business analytics consulting careerUse solutions taught in the book in practical uses cases and problems Who This Book Is ForBusiness analytics enthusiasts who are not particularly programming inclined, small business owners and data science consultants, data science and business students, and SME (small-to-medium enterprise) analysts
Pro SQL Server 2022 Wait Statistics
Use this practical guide to analyze and troubleshoot SQL Server performance using wait statistics. You'll learn to identify precisely why your queries are running slowly. And you'll know how to measure the amount of time consumed by each bottleneck so you can focus attention on making the largest improvements first. This edition is updated to cover analysis of wait statistics current with SQL Server 2022. Whether you are new to wait statistics, or already familiar with them, this book provides a deeper understanding on how wait statistics are generated and what they mean for your SQL Server instance's performance. The book goes beyond the most common wait types into the more complex and performance-threatening wait types. You'll learn about per-query wait statistics and session-based wait statistics, and the types of problems they can help you solve. The different wait types are categorized by their area of impact, including CPU, IO, Latching, Locking, and many more.Clear examples are included to help you gain practical knowledge of why and how specific wait times increase or decrease, how they impact your SQL Server's performance, and what you can do to improve performance. After reading this book, you won't want to be without the valuable information that wait statistics provide regarding where you should be spending your limited tuning time to maximize performance and value to your business. What You'll LearnUnderstand how the SQL Server engine processes requestsIdentify resource bottlenecks in a running SQL Server instanceLocate wait statistics information inside DMVs and Query StoreAnalyze the root cause of sub-optimal performanceDiagnose I/O contention and locking contentionBenchmark SQL Server performanceImprove database performance by lowering overall wait time Who This Book Is ForDatabase administrators who want to identify and resolve performance bottlenecks, those who want to learn more about how the SQL Server engine accesses and uses resources inside SQL Server, and administrators concerned with achieving--and knowing they have achieved--optimal performance
R 4 Data Science Quick Reference
In this handy, quick reference book you'll be introduced to several R data science packages, with examples of how to use each of them. All concepts will be covered concisely, with many illustrative examples using the following APIs: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more.With R 4 Data Science Quick Reference, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. All source code used in the book is freely available on GitHub.. What You'll LearnImplement applicable R 4 programming language specification featuresImport data with readrWork with categories using forcats, time and dates with lubridate, and strings with stringrFormat data using tidyr and then transform that data using magrittr and dplyrWrite functions with R for data science, data mining, and analytics-based applicationsVisualize data with ggplot2 and fit data to models using modelrWho This Book Is ForProgrammers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.
SQL Server 2022 Query Performance Tuning
Covers cutting-edge features like Query Store, adaptive execution plans, automated tuning in Azure.Current with SQL Server 2017, while also covering older editions back to 2012.Alerts you to changes in the cardinality estimation and query optimization engines that can lead to poor performance.Describes new tooling introduced in SQL Server 2017 SQL Server Management Studio.
Business Intelligence with Databricks SQL
Master critical skills needed to deploy and use Databricks SQL and elevate your BI from the warehouse to the lakehouse with confidenceKey Features: Learn about business intelligence on the lakehouse with features and functions of Databricks SQLMake the most of Databricks SQL by getting to grips with the enablers of its data warehousing capabilitiesA unique approach to teaching concepts and techniques with follow-along scenarios on real datasetsBook Description: In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse - a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark(TM), Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics.This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You'll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse - data security, governance, and management of the computational power of the lakehouse. You'll also delve into the core technology enablers of Databricks SQL - Delta Lake and Photon. Finally, you'll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.By the end of this book, you'll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.What You Will Learn: Understand how Databricks SQL fits into the Databricks Lakehouse PlatformPerform everyday analytics with Databricks SQL Workbench and business intelligence toolsOrganize and catalog your data assetsProgram the data security model to protect and govern your dataTune SQL warehouses (computing clusters) for optimal query experienceTune the Delta Lake storage format for maximum query performanceDeliver extreme performance with the Photon query execution engineImplement advanced data ingestion patterns with Databricks SQLWho this book is for: This book is for business intelligence practitioners, data warehouse administrators, and data engineers who are new to Databrick SQL and want to learn how to deliver high-quality insights unhindered by the scale of data or infrastructure. This book is also for anyone looking to study the advanced technologies that power Databricks SQL. Basic knowledge of data warehouses, SQL-based analytics, and ETL processes is recommended to effectively learn the concepts introduced in this book and appreciate the innovation behind the platform.
Cooperative Information Systems
This volume LNCS 13591 constitutes the proceedings of the International Conference on Cooperative Information Systems, CoopIS 2022, collocated with the Enterprise Design, Operations and Computing conference, EDOC 2022, in October 2022 in Bozen-Bolzano, Italy. The 15 regular papers presented together with 5 research in progress papers were carefully reviewed and selected from 68 submissions. The conference focuses on technical, economical, and societal aspects of distributed information systems at scale. As said, this 28th edition was collocated with the 26th edition of the Enterprise Design, Operations and Computing conference, EDOC 2022, and its guiding theme was "Information Systems in a Digital World".
Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers from the thoroughly refereed proceedings of the 10th International Conference on Analysis of Images, Social Networks and Texts, AIST 2021, held in Tbilisi, Georgia, during December 16-18, 2021. The 20 full papers and 5 short papers included in this book were carefully reviewed and selected from 118 submissions. They were organized in topical sections as follows: Invited papers; natural language processing; computer vision; data analysis and machine learning; social network analysis; and theoretical machine learning and optimization.
Databases Theory and Applications
This book constitutes the refereed proceedings of the 33rd International Conference on Databases Theory and Applications, ADC 2022, held in Sydney, Australia, in September 2022. The conference is co-located with the 48th International Conference on Very Large Data Bases, VLDB 2022. The 9 full papers presented together with 8 short papers were carefully reviewed and selected from 36 submissions. ADC focuses on database systems, data-driven applications, and data analytics.
Database Systems
This book provides a concise but comprehensive guide to the disciplines of database design, construction, implementation, and management. Based on the authors' professional experience in the software engineering and IT industries before making a career switch to academia, the text stresses sound database design as a necessary precursor to successful development and administration of database systems. The discipline of database systems design and management is discussed within the context of the bigger picture of software engineering. Students are led to understand from the outset of the text that a database is a critical component of a software infrastructure, and that proper database design and management is integral to the success of a software system. Additionally, students are led to appreciate the huge value of a properly designed database to the success of a business enterprise. The text was written for three target audiences. It is suited for undergraduate students of computer science and related disciplines who are pursuing a course in database systems, graduate students who are pursuing an introductory course to database, and practicing software engineers and information technology (IT) professionals who need a quick reference on database design. Database Systems: A Pragmatic Approach, 3rd Edition discusses concepts, principles, design, implementation, and management issues related to database systems. Each chapter is organized into brief, reader-friendly, conversational sections with itemization of salient points to be remembered. This pragmatic approach includes adequate treatment of database theory and practice based on strategies that have been tested, proven, and refined over several years. Features of the third edition include: Short paragraphs that express the salient aspects of each subject Bullet points itemizing important points for easy memorization Fully revised and updated diagrams and figures to illustrate concepts to enhance the student's understanding Real-world examples Original methodologies applicable to database design Step-by-step, student-friendly guidelines for solving generic database systems problems Opening chapter overviews and concluding chapter summaries Discussion of DBMS alternatives such as the Entity-Attributes-Value model, NoSQL databases, database-supporting frameworks, and other burgeoning database technologies A chapter with sample assignment questions and case studies This textbook may be used as a one-semester or two-semester course in database systems, augmented by a DBMS (preferably Oracle). After its usage, students will come away with a firm grasp of the design, development, implementation, and management of a database system.
Psychology, Learning, Technology
This open access book constitutes the refereed proceedings of 1st International Workshop on Psychology, Learning, Technology, PLT 2022, Foggia, Italy, during January 2022. The 8 full papers presented here were carefully reviewed and selected from 23 submissions. In addition, one invited paper is also included. Psychology, Learning, ad Technology Conference (PLT2022) aims to explore learning paths that incorporate digital technologies in innovative and transformative ways and the improvement of the psychological and relational life. The conference includes topics about the methodology of application of the ICT tools in psychology and education: from blended learning to the application of artificial intelligence in education; from the teaching, learning, and assessment strategies and practices to the new frontiers on Human-Computer Interaction.
How To Gather And Use Data For Business Analysis
These days the business world is full of talk about data science, big data, and how data analysis can transform your business.And it's absolutely true that collecting the right information, in the right way, analyzing that information, and then using it effectively to manage your business can give your business a competitive edge.But most businesses don't need to go so far as big data and data science. They just need to understand and implement some basic steps for gathering the right information about their business and using it effectively.Leveraging over twenty years of experience using data for business, M.L. Humphrey will walk you through what you need to know to help improve your bottom line today.So don't wait. Get started now.This title was previously published as Data Principles for Beginners.
Graph-Theoretic Concepts in Computer Science
This LNCS 13453 constitutes the thoroughly refereed proceedings of the 48th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2022.The 32 full papers presented in this volume were carefully reviewed and selected from a total of 96 submissions. The WG 2022 workshop aims to merge theory and practice by demonstrating how concepts from Graph Theory can be applied to various areas in Computer Science, or by extracting new graph theoretic problems from applications.
Applied Meta-Analysis with R and Stata
Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. -Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What's New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.
Algorithmic Aspects in Information and Management
This book constitutes the proceedings of the 16th International Conference on Algorithmic Aspects in Information and Management, AAIM 2022, which was held online during August 13-14, 2022. The conference was originally planned to take place in Guangzhou, China, but changed to a virtual event due to the COVID-19 pandemic.The 41 regular papers included in this book were carefully reviewed and selected from 59 submissions.
Python for Data Analysis
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the Jupyter notebook and IPython shell for exploratory computing Learn basic and advanced features in NumPy Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Snowflake: The Definitive Guide
Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace
Knowledge and Systems Sciences
This book constitutes the refereed proceedings of the 21st International Symposium on Knowledge and Systems Sciences, KSS 2022, held in Beijing, China, in June 2022.The 14 revised full papers and 3 short paper presented were carefully reviewed and selected from 51 submissions. The papers are organized in topical secions on ​data mining and machine learning; model-based systems engineering; complex systems modeling and knowledge technologies.
Quantum and Blockchain for Modern Computing Systems: Vision and Advancements
Data Analytics and Management in Data Intensive Domains
This book constitutes the post-conference proceedings of the 23rd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2021, held in Moscow, Russia, in October 2021*.The 16 revised full papers were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: problem solving infrastructures, experiment organization, and machine learning applications; data analysis in astronomy; data analysis in material and earth sciences; information extraction from text* The conference was held virtually due to the COVID-19 pandemic.
Simplifying Data Engineering and Analytics with Delta
Explore how Delta brings reliability, performance, and governance to your data lake and all the AI and BI use cases built on top of itKey Features: Learn Delta's core concepts and features as well as what makes it a perfect match for data engineering and analysisSolve business challenges of different industry verticals using a scenario-based approachMake optimal choices by understanding the various tradeoffs provided by DeltaBook Description: Delta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases.In this book, you'll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You'll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you'll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products.By the end of this Delta book, you'll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases.What You Will Learn: Explore the key challenges of traditional data lakesAppreciate the unique features of Delta that come out of the boxAddress reliability, performance, and governance concerns using DeltaAnalyze the open data format for an extensible and pluggable architectureHandle multiple use cases to support BI, AI, streaming, and data discoveryDiscover how common data and machine learning design patterns are executed on DeltaBuild and deploy data and machine learning pipelines at scale using DeltaWho this book is for: Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.
Data Mesh
We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, author Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale. Dehghani guides practitioners, architects, technical leaders, and decision makers on their journey from traditional big data architecture to a distributed and multidimensional approach to analytical data management. Data mesh treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure, and introduces a federated computational model of data governance. Get a complete introduction to data mesh principles and its constituents Design a data mesh architecture Guide a data mesh strategy and execution Navigate organizational design to a decentralized data ownership model Move beyond traditional data warehouses and lakes to a distributed data mesh
Business Modeling and Software Design
This book constitutes the refereed proceedings of the 12h International Symposium on Business Modeling and Software Design, BMSD 2022, which took place in Fribourg, Switzerland, in June 2022.The 12 full and 9 short papers included in this book were carefully reviewed and selected from a total of 56 submissions. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. Each year, a special theme is chosen, for making presentations and discussions more focused.The BMSD 2022 theme is: Information Systems Engineering and Trust.
Operations Research and Enterprise Systems
This book includes extended and revised versions of selected papers from the 9th and 10th edition of the International Conference on Operations Research and Enterprise Systems (ICORES 2020 and ICORES 2021). ICORES 2020 was held in Valletta, Malta from 22 - 24 of February 2020, and ICORES 2021 was held as an online event due to the Covid-19 pandemic, from 4 - 6 of February 2021.The 11 full papers included in this book were carefully reviewed and selected from 132 submissions. The ICORES 2020 and 2021 book contains extended and revised version of proceedings papers dealing with operations research and enterprise systems.
Data Science
This two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Management and Applications; Data Security and Privacy; Applications of Data Science; Infrastructure for Data Science; Education Track; Regulatory Technology in Finance.
