The internet has profoundly changed interpersonal communication, but most of us don’t really understand how it works. What enables information to travel across the internet? Can we really be anonymous and private online? Who controls the internet, and why is that important? And… what’s with all the cats? How the Internet Really Works answers these questions and more. Using clear language and whimsical illustrations, the authors translate highly technical topics into accessible, engaging prose that demystifies the world’s most intricately linked computer network. Alongside a feline guide named Catnip, you’ll learn about: •The “How-What-Why” of nodes, packets, and internet protocols •Cryptographic techniques to ensure the secrecy and integrity of your data •Censorship, ways to monitor it, and means for circumventing it •Cybernetics, algorithms, and how computers make decisions •Centralization of internet power, its impact on democracy, and how it hurts human rights •Internet governance, and ways to get involved This book is also a call to action, laying out a roadmap for using your newfound knowledge to influence the evolution of digitally inclusive, rights-respecting internet laws and policies. Whether you’re a citizen concerned about staying safe online, a civil servant seeking to address censorship, an advocate addressing worldwide freedom of expression issues, or simply someone with a cat-like curiosity about network infrastructure, you will be delighted — and enlightened — by Catnip’s felicitously fun guide to understanding how the internet really works!

Thoroughly revised and updated to address the many changes in this evolving field, the third edition of Legal and Privacy Issues in Information Security addresses the complex relationship between the law and the practice of information security. Information systems security and legal compliance are required to protect critical governmental and corporate infrastructure, intellectual property created by individuals and organizations alike, and information that individuals believe should be protected from unreasonable intrusion. Organizations must build numerous information security and privacy responses into their daily operations to protect the business itself, fully meet legal requirements, and to meet the expectations of employees and customers.

Instructor Materials for Legal Issues in Information Security include:

PowerPoint Lecture Slides
Instructor's Guide
Sample Course Syllabus
Quiz & Exam Questions
Case Scenarios/Handouts

New to the third Edition:

• Includes discussions of amendments in several relevant federal and state laws and regulations since 2011 • Reviews relevant court decisions that have come to light since the publication of the first edition • Includes numerous information security data breaches highlighting new vulnerabilities

The book will discuss the statistical methods involved, covers the development of academic writing skills for a higher impact, teaches learning theories, and uses a structured and holistic approach for educational research proposal development.

This IBM® Redpaper publication describes the architecture, installation procedure, and results for running a typical training application that works on an automotive data set in an orchestrated and secured environment that provides horizontal scalability of GPU resources across physical node boundaries for deep neural network (DNN) workloads. This paper is mostly relevant for systems engineers, system administrators, or system architects that are responsible for data center infrastructure management and typical day-to-day operations such as system monitoring, operational control, asset management, and security audits. This paper also describes IBM Spectrum® LSF® as a workload manager and IBM Spectrum Discover as a metadata search engine to find the right data for an inference job and automate the data science workflow. With the help of this solution, the data location, which may be on different storage systems, and time of availability for the AI job can be fully abstracted, which provides valuable information for data scientists.

Create industry-compliant graphs with this practical guide for professionals Analysis of clinical trial results is easier when the data is presented in a visual form. However, clinical graphs must conform to specific guidelines in order to satisfy regulatory agency requirements. If you are a programmer working in the health care and life sciences industry and you want to create straightforward, visually appealing graphs using SAS, then this book is designed specifically for you. Written by two experienced practitioners, the book explains why certain graphs are requested, gives the necessary code to create the graphs, and shows you how to create graphs from ADaM data sets modeled on real-world CDISC pilot study data. SAS Graphics for Clinical Trials by Example demonstrates step-by-step how to create both simple and complex graphs using Graph Template Language (GTL) and statistical graphics procedures, including the SGPLOT and SGPANEL procedures. You will learn how to generate commonly used plots such as Kaplan-Meier plots and multi-cell survival plots as well as special purpose graphs such as Venn diagrams and interactive graphs. Because your graph is only as good as the aesthetic appearance of the output, you will learn how to create a custom style, change attributes, and set output options. Whether you are just learning how to produce graphs or have been working with graphs for a while, this book is a must-have resource to solve even the most challenging clinical graph problems.

A revolution is occurring in data management regarding how data is collected, stored, processed, governed, managed, and provided to decision makers. The data lake is a popular approach that harnesses the power of big data and marries it with the agility of self-service. With this report, IT executives and data architects will focus on the technical aspects of building a data lake for your organization. Alex Gorelik from Facebook explains the requirements for building a successful data lake that business users can easily access whenever they have a need. You'll learn the phases of data lake maturity, common mistakes that lead to data swamps, and the importance of aligning data with your company's business strategy and gaining executive sponsorship. You'll explore: The ingredients of modern data lakes, such as the use of different ingestion methods for different data formats, and the importance of the three Vs: volume, variety, and velocity Building blocks of successful data lakes, including data ingestion, integration, persistence, data governance, and business intelligence and self-service analytics State-of-the-art data lake architectures offered by Amazon Web Services, Microsoft Azure, and Google Cloud

Discover why privacy is a counterproductive, if not obsolete, concept in this startling new book It's only a matter of time-- the modern notion of privacy is quickly evaporating because of technological advancement and social engagement. Whether we like it or not, all our actions and communications are going to be revealed for everyone to see. Exposed: How Revealing Your Data and Eliminating Privacy Increases Trust and Liberates Humanity takes a controversial and insightful look at the concept of privacy and persuasively argues that preparing for a post-private future is better than exacerbating the painful transition by attempting to delay the inevitable. Security expert and author Ben Malisow systematically dismantles common notions of privacy and explains how: Most arguments in favor of increased privacy are wrong Privacy in our personal lives leaves us more susceptible to being bullied or blackmailed Governmental and military privacy leads to an imbalance of power between citizen and state Military supremacy based on privacy is an obsolete concept Perfect for anyone interested in the currently raging debates about governmental, institutional, corporate, and personal privacy, and the proper balance between the public and the private, Exposed also belongs on the shelves of security practitioners and policymakers everywhere.

Manage Power BI within organizations. This book helps you systematize administration as Microsoft shifts Power BI from a self-service tool to an enterprise tool. You will learn best practices for many Power BI administrator tasks. And you will know how to manage artifacts such as reports, users, work spaces, apps, and gateways. The book also provides experience-based guidance on governance, licensing, and managing capacities. Good management includes policies and procedures that can be applied consistently and even automatically across a broad user base. This book provides a strategic road map for the creation and implementation of policies and procedures that support Power BI best practices in enterprises. Effective governance depends not only on good policies, but also on the active and timely monitoring of adherence to those policies. This book helps you evaluate the tools to automate and simplify the most common administrativeand monitoring tasks, freeing up administrators to provide greater value to the organization through better user training and awareness initiatives. What You Will Learn Recognize the roles and responsibilities of the Power BI administrator Manage users and their work spaces Know when to consider using Power BI Premium Govern your Power BI implementation and manage Power BI tenants Create an effective security strategy for Power BI in the enterprise Collaborate and share consistent views of the data across all users Follow a life cycle management strategy for rollout of dashboards and reports Create internal training resources backed up by accurate documentation Monitor Power BI to better understand risks and compliance manage costs, and track implementation Who This Book Is For IT professionals tasked with maintaining their corporate Power BI environments, Power BI administrators and power users interested in rolling out Power BI more widely in their organizations, and IT governance professionals tasked with ensuring adherence to policies and regulations

For organizations charting their way forward in today's digital economy, the clear imperative is to find better ways of extracting more value from data. By gleaning insight from data regarding customer preferences and business operations, organizations can respond to demand more effectively and better deliver the experiences that today's customers want. To this end, many organizations running SAP solutions seek to make the move to the SAP HANA database. SAP HANA offers the speed of in-memory data processing and the ability to combine transactions and analytics on a single platform for insight in real time. However, considerations at the level of IT infrastructure can make or break the success of an SAP HANA implementation. What the database runs on, in other words, matters significantly. This IBM® Redguide publication explores the value of deploying SAP HANA on SUSE Linux Enterprise Server for SAP Applications and the IBM Power platform with IBM POWER9™ processors. Both offerings are optimized to help your organization reap the rewards of SAP HANA while also transforming IT service delivery more generally. Designed for enterprise-grade operations, SUSE Linux Enterprise Server for SAP Applications offers an open-source software-defined infrastructure (SDI) that is optimized for SAP workloads. Reliable, fast, and secure, it also supports the automation that is needed to substantially free up IT staff from service deployment and management duties. Power Systems servers support SAP HANA implementations according to the SAP Tailored Data Center Integration (TDI) 5.0 specification. Optimized for scale-up and scale-out scenarios and built to support virtual persistent memory, Power Systems serves help you provision faster, scale affordably, and maximize uptime by persisting memory across virtual machines (VMs) and multiple SAP HANA instances. Both SUSE and IBM have partnered with SAP for decades to fine-tune these offerings. Together, SUSE and IBM solutions offer a way forward for deploying, optimizing, and running SAP HANA implementations that is proven to be successful. This publication looks at various aspects of this combined offering in greater detail.

Lead your organization to become evidence-driven Data. It’s the benchmark that informs corporate projections, decision-making, and analysis. But, why do many organizations that see themselves as data-driven fail to thrive? In Leading with AI and Analytics, two renowned experts from the Kellogg School of Management show business leaders how to transform their organization to become evidence-driven, which leads to real, measurable changes that can help propel their companies to the top of their industries. The availability of unprecedented technology-enabled tools has made AI (Artificial Intelligence) an essential component of business analytics. But what’s often lacking are the leadership skills to integrate these technologies to achieve maximum value. Here, the authors provide a comprehensive game plan for developing that all-important human factor to get at the heart of data science: the ability to apply analytical thinking to real-world problems. Each of these tools and techniques comes to powerful life through a wealth of powerful case studies and real-world success stories. Inside, you’ll find the essential tools to help you: Written for anyone in a leadership or management role—from C-level/unit team managers to rising talent—this powerful, hands-on guide meets today’s growing need for real-world tools to lead and succeed with data. Develop a strong data science intuition quotient Lead and scale AI and analytics throughout your organization Move from “best-guess” decision making to evidence-based decisions Craft strategies and tactics to create real impact

Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering. Identifies key problems and offers solution approaches as well as tools which have been developed or are necessary for modeling paradigms across cyber physical systems Explores basic theory and current research topics, related challenges, and research directions for multi-paradigm modeling Provides a complete, conceptual overview and framework of the research done by the MPM4CPS working groups and the different types of modeling paradigms developed

Manipulating and processing masses of digital data is never a purely technical activity. It requires an interpretative and exploratory outlook – already well known in the social sciences and the humanities – to convey intelligible results from data analysis algorithms and create new knowledge. Big Data is based on an inquiry of several years within Proxem, a software publisher specializing in big data processing. The book examines how data scientists explore, interpret and visualize our digital traces to make sense of them, and to produce new knowledge. Grounded in epistemology and science and technology studies, Big Data offers a reflection on data in general, and on how they help us to better understand reality and decide on our daily actions.

Relationships in data often look far more like a web than an orderly set of rows and columns. Graph databases shine when it comes to revealing valuable insights within complex, interconnected data such as demographics, financial records, or computer networks. In Graph Databases in Action, experts Dave Bechberger and Josh Perryman illuminate the design and implementation of graph databases in real-world applications. You'll learn how to choose the right database solutions for your tasks, and how to use your new knowledge to build agile, flexible, and high-performing graph-powered applications! About the Technology Isolated data is a thing of the past! Now, data is connected, and graph databases—like Amazon Neptune, Microsoft Cosmos DB, and Neo4j—are the essential tools of this new reality. Graph databases represent relationships naturally, speeding the discovery of insights and driving business value. About the Book Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization. What's Inside Graph databases vs. relational databases Systematic graph data modeling Querying and navigating a graph Graph patterns Pitfalls and antipatterns About the Reader For software developers. No experience with graph databases required. About the Authors Dave Bechberger and Josh Perryman have decades of experience building complex data-driven systems and have worked with graph databases since 2014. Quotes A comprehensive overview of graph databases and how to build them using Apache tools. - Richard Vaughan, Purple Monkey Collective A well-written and thorough introduction to the topic of graph databases. - Luis Moux, EMO A great guide in your journey towards graph databases and exploiting the new possibilities for data processing. - Mladen Knežić, CROZ A great introduction to graph databases and how you should approach designing systems that leverage graph databases. - Ron Sher, Intuit

Dive into PostgreSQL 13 with this comprehensive guide that equips you to build, manage, and optimize database applications using state-of-the-art features. With a strong focus on hands-on insights, this book covers everything from SQL functions to advanced replication, helping you to enhance your database management expertise. What this Book will help me do Understand and utilize advanced SQL features to increase database efficiency. Optimize your PostgreSQL queries for improved performance in applications. Implement robust backup, recovery, and replication strategies for data integrity. Migrate seamlessly from Oracle to PostgreSQL using proven strategies. Strengthen server security to safeguard sensitive data in your PostgreSQL system. Author(s) Hans-Jürgen Schönig is a renowned PostgreSQL expert with decades of experience in database administration and consulting. He has guided companies across the globe to leverage the power of PostgreSQL, achieving high performance and reliability in their applications. His clear, methodical, and practical approach makes complex topics accessible to database professionals. Who is it for? This book is crafted for PostgreSQL database administrators and developers with some prior experience. If you are looking to refine your skills and adopt advanced features in PostgreSQL 13 to enhance performance and manageability, this book is ideal for you. It is best suited for individuals who aim to make their database applications more secure and robust.

In today's data driven world, the information and data of an organization is considered as the most important asset to its business. It can serve as key asset for growth of an organization. As more data are collected by organizations, it is growing at a staggering pace. With this exponential data growth, there is an increase need to protect the data from the various cyberattacks in the form of malware and ransomware that is trying to steal precious data and information. These cyberattacks can have catastrophic impact on the organization and result in devastating financial losses and affect the organization's reputation for years. This document is intended to facilitate the deployment of the Hybrid Cloud Cyber Resilience solution for storage system data that it backed up in IBM Spectrum Protect Plus from external cyberattacks or insider attacks by using its integration with IBM Cloud Object Storage. You must understand IBM FlashSystem, IBM Spectrum Protect Plus, and IBM Cloud Object Storage architecture concepts and its configuration across hybrid cloud. The information in this document is distributed on an as-is basis without any warranty that is either expressed or implied. Support assistance for the use of this material is limited to situations where IBM FlashSystem, IBM Spectrum Protect Plus or IBM Cloud Object Storage are supported and entitled, and where the issues are specific to a solution technical paper implementation.

Essential Statistics for Non-STEM Data Analysts is your comprehensive guide to mastering the statistical concepts needed for data science. By working through real-world datasets and Python-based examples, you'll learn how to interpret data and build insightful analyses. This book demystifies statistics, making it accessible to anyone aiming to become proficient in data analysis. What this Book will help me do Learn how to preprocess, clean, and prepare data for analysis using Python. Master the foundations of statistical methods such as hypothesis testing and probability theory. Develop skills to interpret and explain statistical results in the context of data science. Understand how statistical concepts apply to machine learning tasks like classification and regression. Build confidence in statistical principles to tackle interviews and enhance your career prospects. Author(s) None Li is an experienced data scientist and educator with a strong focus on making abstract statistical concepts intuitive and applicable. With a background in designing data science curriculums, None has a passion for teaching statistics to individuals from diverse and often non-mathematical backgrounds. Through clear explanations and practical examples, None aims to empower everyone to excel in data analysis and machine learning. Who is it for? This book caters specifically to data analysts, data science enthusiasts, and developers eager to enhance their statistical knowledge. It's crafted for readers transitioning into data science who may lack a strong mathematical or statistics background. If you have a basic grasp of Python programming and a keen interest in understanding how to work effectively with data, this book is a perfect fit. Beginners and students aiming to familiarize themselves with statistical foundations for data-oriented careers will greatly benefit from this resource.

This IBM® Redpaper publication introduces System Recovery Boost, which is a new function of the IBM z15™ system. System Recovery Boost delivers substantially faster system shutdown and restart, short duration recovery process boosts for sysplex events, and fast catch-up of an accumulated backlog of work after specific events (such as system restart).

Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms

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 2019 Build and configure a Windows Cluster in Windows Server 2019 Create and configure an AlwaysOn failover clustered instance Implement AlwaysOn Availability Groups and appropriately configure them Implement AlwaysOn Availability Groups on Linux servers Configure Availability Groups on Azure IaaS Administer AlwaysOn technologies post implementation Understand 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.

Learn to build an analytics community in your organization from scratch How to Build a Data Community shows readers how to create analytics and data communities within their organizations. Celebrated author Eva Murray relies on intuitive and practical advice structured as step-by-step guidance to demonstrate the creation of new data communities. How to Build a Data Community uses concrete insights gleaned from real-world case studies to describe, in full detail, all the critical components of a data community. Readers will discover: What analytics communities are and what they look like Why data-driven organizations need analytics communities How selected businesses and nonprofits have applied these concepts successfully and what their journey to a data-driven culture looked like. How they can establish their own communities and what they can do to ensure their community grows and flourishes Perfect for analytics professionals who are responsible for making policy-level decisions about data in their firms, the book is also a must-have for data practitioners and consultants who wish to make positive changes in the organizations with which they work.