In this paper, we outline some IBM® Spectrum Virtualize HyperSwap® SAN implementation and design best practices for optimum resiliency of the SAN Volume Controller cluster. It provides IBM Spectrum® Virtualize HyperSwap and Stretched Cluster configuration details. Note: In this book, for brevity, we use HyperSwap to refer to both HyperSwap and Stretched Cluster. The documentation there details the minimum requirements. However, it does not describe the design of the storage area network (SAN) in detail, nor does it describe the recommended way to implement those requirements on a SAN. In this IBM Redpaper publication, we outline some of the best practices for SAN design and implementation that leads to optimum resiliency of the SAN Volume Controller (SVC) cluster, and we explain why each recommendation is made. This paper is SAN vendor-neutral wherever possible. Any mention of a specific SAN switch vendor, or terms used by a specific switch vendor, is made only where relevant to a specific context, and does not imply an endorsement of a specific switch vendor. Note: Some of the figures in this document might not depict redundant fabrics or storage configurations. This was done for simplicity, and it should be assumed that any recommendations made for fabric design assume that there are two redundant fabrics.

Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.

This IBM® Redpaper publication describes IBM Spectrum® LSF® Suite best practices installation topics, application checks for workload management, and high availability configurations by using theoretical knowledge and hands-on exercises. These findings are documented by way of sample scenarios. This publication addresses topics for sellers, IT architects, IT specialists, and anyone who wants to implement and manage a high-performing workload management solution with LSF. Moreover, this guide provides documentation to transfer how-to-skills to the technical teams, and solution guidance to the sales team. This publication compliments documentation that is available at IBM Knowledge Center, and aligns with educational materials that are provided by IBM Systems.

Is your company ready for the next wave of analytics? Data analytics offer the opportunity to predict the future, use advanced technologies, and gain valuable insights about your business. But unless you're staying on top of the latest developments, your company is wasting that potential--and your competitors will be gaining speed while you fall behind. Strategic Analytics: The Insights You Need from Harvard Business Review will provide you with today's essential thinking about what data analytics are capable of, what critical talents your company needs to reap their benefits, and how to adopt analytics throughout your organization--before it's too late. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues--blockchain, cybersecurity, AI, and more--each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.

IBM® experts recognize the need for data protection, both from hardware or software failures, and from physical relocation of hardware, theft, and retasking of existing hardware. The IBM DS8000® supports encryption-capable hard disk drives (HDDs) and flash drives. These Full Disk Encryption (FDE) drive sets are used with key management services that are provided by IBM Security Key Lifecycle Manager software or Gemalto SafeNet KeySecure to allow encryption for data at rest. Use of encryption technology involves several considerations that are critical for you to understand to maintain the security and accessibility of encrypted data. Failure to follow the requirements that are described in the IBM Redpaper can result in an encryption deadlock. Starting with Release 8.5 code, the DS8000 also supports Transparent Cloud Tiering (TCT) data object encryption. With TCT encryption, data is encrypted before it is transmitted to the cloud. The data remains encrypted in cloud storage and is decrypted after it is transmitted back to the IBM DS8000. Starting with DS8000 Release 9.0, the DS8900F provides Fibre Channel Endpoint Security when communicating with an IBM z15™, which supports link authentication and the encryption of data that is in-flight. For more information, see IBM Fibre Channel Endpoint Security for IBM DS8900F and IBM Z, SG24-8455. This edition focuses on IBM Security Key Lifecycle Manager Version 3.0.1.3 or later, which enables support Key Management Interoperability Protocol (KMIP) with the DS8000 Release 9.0 code or later and updated DS GUI for encryption functions.

This IBM® Redpaper publication delivers SAP HANA architectural concepts for successful implementation on IBM Power Systems servers. This publication addresses topics for sellers, IT architects, IT specialists, and anyone who wants to understand how to take advantage of running SAP HANA workloads on Power Systems servers. Moreover, this guide provides documentation to transfer how-to skills to the technical teams, and it provides solution guidance to the sales team. This publication complements documentation that is available at IBM Knowledge Center, and it aligns with educational materials that are provided by IBM Systems.

This IBM Redpaper™ publication introduces the IBM Spectrum Scale immutability function. It shows how to set it up and presents different ways for managing immutable and append-only files. This publication also provides guidance for implementing IT security aspects in an IBM Spectrum Scale cluster by addressing regulatory requirements. It also describes two typical use cases for managing immutable files. One use case involves applications that manage file immutability; the other use case presents a solution to automatically set files to immutable within a IBM Spectrum Scale immutable fileset.

Companies need to migrate data not only when technology needs to be replaced, but also for consolidation, load balancing, and disaster recovery (DR). Data migration is a critical operation, and this book explains the phases and steps to ensure a smooth migration. Topics range from planning and preparation to execution and validation. The book explains, from a generic standpoint, the appliance-based, storage-based, and host-based techniques that can be used to accomplish the migration. Each method is explained through practical migration scenarios and for various operating systems. This publication addresses the aspects of data migration efforts while focusing on fixed block storage systems in open environment with the IBM® FlashSystem 9100 as the target system. Therefore, the book also emphasizes various migration techniques using the Spectrum Virtualize built-in functions. This document targets storage administrators, storage network administrators, system designers, architects, and IT professionals who design, administer or plan data migrations in large data Centers. The aim is to ensure that you are aware of the current thinking, methods, and products that IBM can make available to you. These items are provided to ensure a data migration process that is as efficient and problem-free as possible. The material presented in this book was developed with versions of the referenced products as of February, 2020.

IBM® Spectrum Protect Plus is a data protection solution that provides near-instant recovery, replication, retention, and reuse for virtual machines, databases, and applications in hybrid multicloud environments. IBM Knowledge Center for IBM Spectrum® Protect Plus provides extensive documentation for installation, deployment, and usage. In addition, IBM Spectrum Protect Plus Blueprint (https://ibm.biz/IBMSpectrumProtectPlusBlueprints) provides guidance about how to build and size an IBM Spectrum Protect Plus solution. The goal of this IBM Redpaper publication is to summarize and complement the available information by providing useful hints and tips based on the authors' practical experience in installing and supporting IBM Spectrum Protect Plus in actual customer environments. Over time, our aim is to compile a set of best practices that cover all aspects of the product, from planning and installation to tuning, maintenance, and troubleshooting.

How can you use data in a way that protects individual privacy but still provides useful and meaningful analytics? With this practical book, data architects and engineers will learn how to establish and integrate secure, repeatable anonymization processes into their data flows and analytics in a sustainable manner. Luk Arbuckle and Khaled El Emam from Privacy Analytics explore end-to-end solutions for anonymizing device and IoT data, based on collection models and use cases that address real business needs. These examples come from some of the most demanding data environments, such as healthcare, using approaches that have withstood the test of time. Create anonymization solutions diverse enough to cover a spectrum of use cases Match your solutions to the data you use, the people you share it with, and your analysis goals Build anonymization pipelines around various data collection models to cover different business needs Generate an anonymized version of original data or use an analytics platform to generate anonymized outputs Examine the ethical issues around the use of anonymized data

This IBM® Redbooks® publication introduces the latest member of the IBM Z® platform, the IBM z15™. It includes information about the Z environment and how it helps integrate data and transactions more securely. It also provides insight for faster and more accurate business decisions. The z15 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z15 is designed for enhanced modularity, and occupies an industry-standard footprint. It is offered as a single air-cooled 19-inch frame called the z15 T02, or as a multi-frame (1 to 4 19-inch frames) called the z15 T01. Both z15 models excel at the following tasks: Using hybrid multicloud integration services Securing and protecting data with encryption everywhere Providing resilience with key to zero downtime Transforming a transactional platform into a data powerhouse Getting more out of the platform with IT Operational Analytics Accelerating digital transformation with agile service delivery Revolutionizing business processes Blending open source and IBM Z technologies This book explains how this system uses innovations and traditional Z strengths to satisfy growing demand for cloud, analytics, and open source technologies. With the z15 as the base, applications can run in a trusted, reliable, and secure environment that improves operations and lessens business risk.

With Interactive Data Visualization with Python, you will learn to turn raw data into compelling, interactive visual stories. This book guides you through the practical uses of Python libraries such as Bokeh and Plotly, teaching you skills to create visualizations that captivate and inform. What this Book will help me do Understand and apply different principles and techniques of interactive data visualization to bring your data to life. Master the use of libraries like Matplotlib, Seaborn, Altair, and Bokeh for creating a variety of data visualizations. Learn how to customize data visualizations effectively to meet the needs of different audiences and use cases. Gain proficiency in using advanced tools like Plotly for creating dynamic and engaging visual presentations. Acquire the ability to identify common pitfalls in visualization and learn strategies to avoid them, ensuring clarity and impact. Author(s) Abha Belorkar, Sharath Chandra Guntuku, Shubhangi Hora, and Anshu Kumar are experts in Python programming and data visualization with years of experience in data science and software development. They have collaborated to blend their knowledge into this book-a clear and practical guide to mastering interactive visualization with Python. Who is it for? This book is perfect for Python developers, data analysts, and data scientists who want to enhance their skills in data presentation. If you are ready to transform complex data into digestible and interactive visuals, this book is for you. A basic familiarity with Python programming and libraries like pandas is recommended. By the end of the book, you'll feel confident in creating professional-grade data visualizations.

To help you safeguard your sensitive data and provide ease of auditability and control, IBM introduced a new capability for IBM Z® called IBM Data Privacy Passports. It can help minimize the risk and impact of data loss and privacy breaches when collecting and storing sensitive data. Data Privacy Passports can manage how data is shared securely through a central control of user access. Data Privacy Passports can protect data wherever it goes. Security policies are kept and honored whenever the data is accessed. Future data access may be revoked remotely via Data Privacy Passports, long after data leaves the system of record, and sensitive data may even be made unusable simply by destroying its encryption key. Data Privacy Passports is designed to help reduce the time that is spent by staff to protect data and ensure privacy throughout its lifecycle via a central point of control. This IBM Redguide presents a business view of Data Privacy Passports, including how data privacy and protection concerns are addressed. We also explore how value is gained through various business model examples.

IBM® Spectrum Scale is a proven, scalable, high-performance data and file management solution. It provides world-class storage management with extreme scalability, flash accelerated performance, automatic policy-based storage that has tiers of flash through disk to tape. It also provides support for various protocols, such as NFS, SMB, Object, HDFS, and iSCSI. Containers can leverage the performance, information lifecycle management (ILM), scalability, and multisite data management to give the full flexibility on storage as they experience on the runtime. Container adoption is increasing in all industries, and they sprawl across multiple nodes on a cluster. The effective management of containers is necessary because their number will probably reach a far greater number than virtual machines today. Kubernetes is the standard container management platform currently being used. Data management is of ultimate importance, and often is forgotten because the first workloads containerized are ephemeral. For data management, many drivers with different specifications were available. A specification named Container Storage Interface (CSI) was created and is now adopted by all major Container Orchestrator Systems available. Although other container orchestration systems exist, Kubernetes became the standard framework for container management. It is a very flexible open source platform used as the base for most cloud providers and software companies' container orchestration systems. Red Hat OpenShift is one of the most reliable enterprise-grade container orchestration systems based on Kubernetes, designed and optimized to easily deploy web applications and services. OpenShift enables developers to focus on the code, while the platform takes care of all of the complex IT operations and processes. This IBM Redbooks® publication describes how the CSI Driver for IBM file storage enables IBM Spectrum® Scale to be used as persistent storage for stateful applications running in Kubernetes clusters. Through the Container Storage Interface Driver for IBM file storage, Kubernetes persistent volumes (PVs) can be provisioned from IBM Spectrum Scale. Therefore, the containers can be used with stateful microservices, such as database applications (MongoDB, PostgreSQL, and so on).

Employ the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs. You’ll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling. After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering. What You Will Learn Model complex problems using MATLAB and Simulink Gain the programming and modeling essentials of MATLAB using ODEs and PDEs Use numerical methods to solve 1st and 2nd order ODEs Solve stiff, higher order, coupled, and implicit ODEs Employ numerical methods to solve 1st and 2nd order linear PDEs Solve stiff, higher order, coupled, and implicit PDEs Who This Book Is For Engineers, programmers, data scientists, and students majoring in engineering, applied/industrial math, data science, and scientific computing. This book continues where Apress' Beginning MATLAB and Simulink leaves off.

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data

This book focuses the solutions of differential equations with MATLAB. Analytical solutions of differential equations are explored first, followed by the numerical solutions of different types of ordinary differential equations (ODEs), as well as the universal block diagram based schemes for ODEs. Boundary value ODEs, fractional-order ODEs and partial differential equations are also discussed.

An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors – noted experts in the field – explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: • Presents a guide to innovation feasibility and formulation and process development • Contains the statistical tools used to solve challenges faced during product innovation and feasibility • Offers information on stability studies which are common especially in chemical or pharmaceutical fields • Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.

This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed integer, multiobjective and dynamic programming problems. Comparative studies and conclusions on intelligent global solvers are also provided.

Utilize organizational data and analytics to make better decisions about managing the learning and development of your workforce.