Computing & Internet Databases Books

Knowledge Graphs and Big Data Processing (Lecture Notes in Computer Science Book 12072)

This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

Mastering Excel: Starter Set

Ramp up your Excel skills with the Mastering Excel Starter Set. This collection of three Excel lessons will get you on the path to be the Excel guru.The Starter Set includes:Mastering Excel Macros - Introduction: The first in the mastering Excel macros series. The series starts from the most basic levels (you need to know nothing about macros) and ends with you writing macro to control PowerPoint and other programs from Excel.Mastering Excel - Apps: Did you know that Excel has apps in it? Yes it does! They are hidden in plain sight. This lesson uncovers the power of apps in Excel. You'll learn to make charts that are dynamic and gorgeous.Mastering Excel - Data Types: There are new data types in Excel. You select cells and Excel will automatically connect the cells to  the Internet and retrieve data.These lessons all include several workbooks you will receive via email so you can work alongside the material.

Mastering Excel: Excel Apps

This lesson only applies to Excel 2013 or Office 365!This short lesson covers Excel applications (apps). Apps are almost like the apps you find on your smartphone. In the Excel world, an app is a small, programmed interface that interacts with Excel data to extend your spreadsheet's functionality.Excel come with two apps built by Microsoft. You will learn how to use these apps to add dynamic charts to your worksheets. There is no programming involved with these apps. They do all the work for you.As with all my other lessons, this one comes with two follow along workbooks. One you can use to work through the exercises and the other one has the completed exercises.Once again, if you do not have Excel 2013 or Office 365 for Windows, you will not be able to use this lesson!

Office 365: Migrating and Managing Your Business in the Cloud

Written for the IT professional and business owner, this book provides the business and technical insight necessary to migrate your business to the cloud using Microsoft Office 365. This is a practical look at cloud migration and the use of different technologies to support that migration. Numerous examples of cloud migration with technical migration details are included. Cloud technology is a tremendous opportunity for an organization to reduce IT costs, and to improve productivity with increased access, simpler administration and improved services. Those businesses that embrace the advantages of the cloud will receive huge rewards in productivity and lower total cost of ownership over those businesses that choose to ignore it. The challenge for those charged with implementing Microsoft Office 365 is to leverage these advantages with the minimal disruption of their organization. This book provides practical help in moving your business to the Cloud and covers the planning, migration and the follow on management of the Office 365 Cloud services.

Programming Persistent Memory: A Comprehensive Guide for Developers

Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times—a huge leap forward in byte-addressable capacity compared with current DRAM offerings.This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data.   Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included.What You’ll LearnUnderstand what persistent memory is, what it does, and the value it brings to the industryBecome familiar with the operating system and hardware requirements to use persistent memoryKnow the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistenceLook at persistent memory application development by example using the Persistent Memory Development Kit (PMDK)Design and optimize data structures for persistent memoryStudy how real-world applications are modified to leverage persistent memoryUtilize the tools available for persistent memory programming, application performance profiling, and debuggingWho This Book Is ForC, C++, Java, and Python developers, but will also be useful to software, cloud, and hardware architects across a broad spectrum of sectors, including cloud service providers, independent software vendors, high performance compute, artificial intelligence, data analytics, big data, etc.  

Linked Open Data -- Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project (Lecture Notes in Computer Science Book 8661)

Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.

The Economics of Big Science: Essays by Leading Scientists and Policymakers (Science Policy Reports)

The essays in this open access volume identify the key ingredients for success in capitalizing on public investments in scientific projects and the development of large-scale research infrastructures.Investment in science – whether in education and training or through public funding for developing new research tools and technologies – is a crucial priority. Authors from big research laboratories/organizations, funding agencies and academia discuss how investing in science can produce societal benefits as well as identifying future challenges for scientists and policy makers. The volume cites different ways to assess the socio-economic impact of Research Infrastructures and their role as hubs of global collaboration, creativity and innovation. It highlights the different benefits stemming from fundamental research at the local, national and global level, while also inviting us to rethink the notion of “benefit” in the 21st century.Public investment is required to maintain the pace of technological and scientific advancements over the next decades. Far from advocating a radical transformation and massive expansion in funding, the authors suggest ways for maintaining a strong foundation of science and research to ensure that we continue to benefit from the outputs. The volume draws inspiration from the first “Economics of Big Science” workshop, held in Brussels in 2019 with the aim of creating a new space for dialogue and interaction between representatives of Big Science organizations, policy makers and academia. It aspires to provide useful reading for policy makers, scientists and students of science, who are increasingly called upon to explain the value of fundamental research and adopt the language and logic of economics when engaging in policy discussions.

SQL Queries: 200+ Queries to Challenge you.

This is a SQL Queries Workbook in Which I have listed a collection of 200+ Queries so you can review it before your interview.

Ethics and Data Science

As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day.To help you consider all of possible ramifications of your work on data projects, this report includes:A sample checklist that you can adapt for your own proceduresFive framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequencesSuggestions for building ethics into your data-driven cultureNow is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

TouchDevelop: Programming on the Go (Expert's Voice in Web Development)

"The book is great! It's clear and easy to read, with loads of examples that showed my students what to do."        -- Larry Snyder, Emeritus Professor, University of Washington, Department of Computer Science and Engineering “Having the TouchDevelop book available made our events so much easier. Students could figure things out for themselves with help from the book.” -- Jennifer Marsman, Microsoft Principal Developer Evangelist Mobile devices such as smartphones and tablets are set to become the main computers that virtually all people will own and carry with them at all times. And yet,mobile devices are not yet used for all computing tasks. A project at Microsoft Research was created to answer a simple question: “It is possible to create interesting apps directly on a smartphone or tablet, without using a separate PC or a keyboard?” The result is TouchDevelop, a programming environment that runs on all modern mobile devices such as Windows Phone, iPhone, iPad, Android phones and tablets, and also on PCs and Macs.This book walks you through all of the screens of the TouchDevelop app, and it points out similarities and differences of the TouchDevelop language compared to other programming languages. For users, the book can serve as a handyreference next to the phone. The book systematically addresses all programming language constructs, starting from the very basic constructs such as variables and loops. The book also explores many of the phone sensors and data sources which make creating apps for mobile devices so rewarding.If you are new to programming with TouchDevelop, or if you have not yet worked on touchscreen devices, we suggest that you read the book starting from Chapter 1. If you are already familiar with the basic paradigm of the TouchDevelop programming environment, then feel free to jump ahead to the later chapters that address particular topic areas.This book is written from the perspective of a person developing their code using a web browser. The TouchDevelop Web App runs in many modern browsers on many different devices including smartphones and tablets, Macs, PC. All screenshots and navigation instructions refer to the TouchDevelop Web App running in a browser. For Windows Phone, there is a dedicated TouchDevelop app in the Windows Phone Store which gives access to many more sensors and data sources. Starting with the TouchDevelop app v3.0 for Windows Phone 8, the phone app will share the same look and navigation structure and all features of the Web App.

Big Data in Context: Legal, Social and Technological Insights (SpringerBriefs in Law)

This book is open access under a CC BY 4.0 license.This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.All contributions are based on papers submitted in connection with ABIDA (Assessing Big Data), an interdisciplinary research project exploring the societal aspects of big data and funded by the German Federal Ministry of Education and Research.This volume was produced as a part of the ABIDA project (Assessing Big Data, 01IS15016A-F). ABIDA is a four-year collaborative project funded by the Federal Ministry of Education and Research. However the views and opinions expressed in this book reflect only the authors’ point of view and not necessarily those of all members of the ABIDA project or the Federal Ministry of Education and Research.

Clinical Text Mining: Secondary Use of Electronic Patient Records

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Disruptive Possibilities: How Big Data Changes Everything

Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds. This relentlessly innovative form of computing will soon become standard practice for organizations of any size attempting to derive insight from the tsunami of data engulfing them.Replacing legacy silos—whether they’re infrastructure, organizational, or vendor silos—with a platform-centric perspective is just one of the big stories of big data. To reap maximum value from the myriad forms of data, organizations and vendors will have to adopt highly collaborative habits and methodologies.

Unauthorized Access: The Crisis in Online Privacy and Security

Going beyond current books on privacy and security, this book proposes specific solutions to public policy issues pertaining to online privacy and security. Requiring no technical or legal expertise, it provides a practical framework to address ethical and legal issues. The authors explore the well-established connection between social norms, privacy, security, and technological structure. They also discuss how rapid technological developments have created novel situations that lack relevant norms and present ways to develop these norms for protecting informational privacy and ensuring sufficient information security.