This document is intended to facilitate the deployment of the Cyber Resiliency solution for IBM® Spectrum Scale. This solution is designed to protect the data on IBM Spectrum™ Scale from external cyberattacks or insider attacks using its integration with IBM Spectrum Protect™ and IBM Tape Storage. To complete the tasks that it describes, you must understand IBM Spectrum Scale™, IBM Spectrum Protect, and IBM Tape Storage architecture, concepts, and configuration. 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 Spectrum Scale or IBM Spectrum Protect are supported and entitled, and where the issues are specific to a blueprint implementation.

This IBM® Redbooks® publication helps strengthen the position of the IBM PowerHA® SystemMirror® for Linux solution with well-defined and documented deployment models within an IBM Power Systems™ environment, which provides customers a planned foundation for business resilience and disaster recovery (DR) for their IBM Power Systems infrastructure solutions. This book addresses topics to help answer customers' complex high availability (HA) and DR requirements for IBM AIX® and Linux on IBM Power Systems servers to help maximize system availability and resources and provide technical documentation to transfer the how-to-skills to users and support teams. This publication is targeted at technical professionals (consultants, technical support staff, IT architects, and IT specialists) who are responsible for providing HA and DR solutions and support for IBM PowerHA SystemMirror for AIX and Linux Standard and Enterprise Editions on IBM Power Systems servers.

Gain a better understanding of implementing SAP S/4HANA-based digital transformations. This book helps you understand the various components involved in the planning and execution of successful SAP S/4HANA projects. Learn how to ensure success by building a solid business case for SAP S/4HANA up front and track business value generated throughout the implementation. Implementing SAP S/4HANA provides a framework for planning and executing SAP S/4HANA projects by articulating the implementation approach used by different components in SAP S/4HANA implementations. Whether you are mid-way through the SAP S/4HANA program or about to embark on it, this book will help you throughout the journey. If you are looking for answers on why SAP S/4HANA requires special considerations as compared to a traditional SAP implementation, this book is for you. What You Will Learn Understand various components of your SAP S/4HANA project Forecast and track your success throughout the SAP S/4HANA implementation Build a solid business case for your SAP S/4HANA program Discover how the implementation approach varies across these components Who This Book Is For SAP S/4HANA clients (line managers and consultants).

Business Intelligence (BI) has emerged as a field which seeks to support managers in decision-making. It encompasses the techniques, methods and tools for conducting analytically-based IT solutions, which are referred to as OLAP (OnLine Analytical Processing). Within this field, SQL has a role as a leader and is continuously evolving to cover both transactional and analytical data management. This book discusses the functions provided by Microsoft® SQL Server 2014/2016 in terms of business intelligence. The analytic functions are considered as an enrichment of the SQL language. They combine a series of practical functions to answer complex analysis requests with all the simplicity, elegance and acquired performance of the SQL language. Drawing on the wide experience of the author in teaching and research, as well as insights from contacts in the industry, this book focuses on the issues and difficulties faced by academics (students and teachers) and professionals engaged in data analysis with the SQL Server 2014/2016 database management system.

This IBM® Redpaper publication provides an update to the original description of IBM Reference Architecture for Genomics. This paper expands the reference architecture to cover all of the major vertical areas of healthcare and life sciences industries, such as genomics, imaging, and clinical and translational research. The architecture was renamed IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences to reflect the fact that it incorporates key building blocks for high-performance computing (HPC) and software-defined storage, and that it supports an expanding infrastructure of leading industry partners, platforms, and frameworks. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data, which can be deployed on-premises, in the cloud, or as a hybrid of the two. IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks that are frequently encountered in personalized healthcare initiatives, and in compute-intensive and data-intensive biomedical workloads. This reference architecture also provides a framework and context for modern healthcare and life sciences institutions to adopt cutting-edge technologies, such as cognitive life sciences solutions, machine learning and deep learning, Spark for analytics, and cloud computing. To illustrate these points, this paper includes case studies describing how clients and IBM Business Partners alike used the reference architecture in the deployments of demanding infrastructures for precision medicine. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing life sciences solutions and support.

This IBM® Redbooks® publication provides a security and compliance solution that is optimized for virtualized environments on IBM Power Systems™ servers, running IBM PowerVM® and IBM AIX®. Security control and compliance are some of the key components that are needed to defend the virtualized data center and cloud infrastructure against ever evolving new threats. The IBM business-driven approach to enterprise security that is used with solutions, such as IBM PowerSC™, makes IBM the premier security vendor in the market today. The book explores, tests, and documents scenarios using IBM PowerSC that leverage IBM Power Systems servers architecture and software solutions from IBM to help defend the virtualized data center and cloud infrastructure against ever evolving new threats. This publication helps IT and Security managers, architects, and consultants to strengthen their security and compliance posture in a virtualized environment running IBM PowerVM.

Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to learn to use this language to perform exploratory data analysis and solve an array of business challenges. You'll start by reviewing PySpark fundamentals, such as Spark’s core architecture, and see how to use PySpark for big data processing like data ingestion, cleaning, and transformations techniques. This is followed by building workflows for analyzing streaming data using PySpark and a comparison of various streaming platforms. You'll then see how to schedule different spark jobs using Airflow with PySpark and book examine tuning machine and deep learning models for real-time predictions. This book concludes with a discussion on graph frames and performing network analysis using graph algorithms in PySpark. All the code presented in the book will be available in Python scripts on Github. What You'll Learn Develop pipelines for streaming data processing using PySpark Build Machine Learning & Deep Learning models using PySpark latest offerings Use graph analytics using PySpark Create Sequence Embeddings from Text data Who This Book is For Data Scientists, machine learning and deep learning engineers who want to learn and use PySpark for real time analysis on streaming data.

Use MySQL Shell, the first modern and advanced client for connecting to and interacting with MySQL. It supports SQL, Python, and JavaScript. That’s right! You can write Python scripts and execute them within the shell interactively, or in batch mode. The level of automation available from Python combined with batch mode is especially helpful to those practicing DevOps methods in their database environments. Introducing MySQL Shell covers everything you need to know about MySQL Shell. You will learn how to use the shell for SQL, as well as the new application programming interfaces for working with a document store and even automating your management of MySQL servers using Python. The book includes a look at the supporting technologies and concepts such as JSON, schema-less documents, NoSQL, MySQL Replication, Group Replication, InnoDB Cluster, and more. MySQL Shell is the client that developers and databaseadministrators have been waiting for. Far more powerful than the legacy client, MySQL Shell enables levels of automation that are useful not only for MySQL, but in the broader context of your career as well. Automate your work and build skills in one of the most in-demand languages. With MySQL Shell, you can do both! What You'll Learn Use MySQL Shell with the newest features in MySQL 8 Discover what a Document Store is and how to manage it with MySQL Shell Configure Group Replication and InnoDB Cluster from MySQL Shell Understand the new MySQL Python application programming interfaces Write Python scripts for managing your data and the MySQL high availability features Who This Book Is For Developers and database professionals who want to automate their work and remain on the cutting edge of what MySQLhas to offer. Anyone not happy with the limited automation capabilities of the legacy command-line client will find much to like in this book on the MySQL Shell that supports powerful automation through the Python scripting language.

A collection of popular essays from security guru Bruce Schneier In his latest collection of essays, security expert Bruce Schneier tackles a range of cybersecurity, privacy, and real-world security issues ripped from the headlines. Essays cover the ever-expanding role of technology in national security, war, transportation, the Internet of Things, elections, and more. Throughout, he challenges the status quo with a call for leaders, voters, and consumers to make better security and privacy decisions and investments. Bruce’s writing has previously appeared in some of the world's best-known and most-respected publications, including The Atlantic, the Wall Street Journal, CNN, the New York Times, the Washington Post, Wired, and many others. And now you can enjoy his essays in one place—at your own speed and convenience. • Timely security and privacy topics • The impact of security and privacy on our world • Perfect for fans of Bruce’s blog and newsletter • Lower price than his previous essay collections The essays are written for anyone who cares about the future and implications of security and privacy for society.

Time has become a precious commodity, so business leaders who can save their customers' time more effectively than competitors do will win their loyalty. This book shows how it's done. Business survival requires valuing what customers value—and in our overworked and distraction-rich era, customers value their time above all else. Real-time companies beat their rivals by being faster and more responsive in meeting customer needs. To become a real-time company, as top scholars Jerry Power and Tom Ferratt explain, you need a real-time monitoring and response system. They offer detailed advice on how to put procedures in place that will collect data on how well products or services are saving customer time; identify strengths, weaknesses, threats, and opportunities; and specify innovations needed to save even more customer time. Where should leaders look to innovate? Powers and Ferratt say to search every step in the life of a product or service, from development to production to usage. And for each step, they identify four possible levers for innovation: the design of the products or services themselves, the process used to produce them, the data that can be gathered on their use, and the people who make or provide the product or service. The book features dozens of examples of companies that are getting it right and the innovations they used to help their customers save time, all while helping themselves to a hefty slice of market share. This is a comprehensive, authoritative guide to thriving in a revolution that is sweeping every industry and sector.

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more. Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

Private Security and the Investigative Process, Fourth Edition targets those students in the early phases of their study of private sector justice and the principles of investigative practice most relevant to the private security industry. The book lays out not only the basic steps taken by entry level as well advanced security professionals conducting investigations, but also provides an overview of the professional security industry and landscape as a whole.

Dive deep into the advanced capabilities of Elasticsearch 7.0 with this expert-level guide. In this book, you will explore the most effective techniques and tools for building, indexing, and querying advanced distributed search engines. Whether optimizing performance, scaling applications, or integrating with big data analytics, this guide empowers you with practical skills and insights. What this Book will help me do Master ingestion pipelines and preprocess documents for faster and more efficient indexing. Model search data optimally for complex and varied real-world applications. Perform exploratory data analyses using Elasticsearch's robust features. Integrate Elasticsearch with modern analytics platforms like Kibana and Logstash. Leverage Elasticsearch with Apache Spark and machine learning libraries for real-time advanced analytics. Author(s) None Wong is a seasoned Elasticsearch expert with years of real-world experience developing enterprise-grade search and analytics systems. With a passion for innovation and teaching, Wong enjoys breaking down complex technical concepts into digestible learning experiences. His work reflects a pragmatic and results-driven approach to teaching Elasticsearch. Who is it for? This book is ideal for Elasticsearch developers and data engineers with some prior experience who are looking to elevate their skills to an advanced level. It suits professionals seeking to enhance their expertise in building scalable search and analytics solutions. If you aim to master sophisticated Elasticsearch operations and real-time integrations, this book is tailored for you.

Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with ease Key Features Work with temporal tables to access information stored in a table at any time Get familiar with the latest features in SQL Server 2017 Integration Services Program and extend your packages to enhance their functionality Book Description Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You'll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you'll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Milos Radivojevic, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al What you will learn Use columnstore indexes to make storage and performance improvements Extend database design solutions using temporal tables Exchange JSON data between applications and SQL Server Migrate historical data to Microsoft Azure by using Stretch Database Design the architecture of a modern Extract, Transform, and Load (ETL) solution Implement ETL solutions using Integration Services for both on-premise and Azure data Who this book is for This Learning Path is for database developers and solution architects looking to develop ETL solutions with SSIS, and explore the new features in SSIS 2017. Advanced analysis practitioners, business intelligence developers, and database consultants dealing with performance tuning will also find this book useful. Basic understanding of database concepts and T-SQL is required to get the best out of this Learning Path.

Start developing with Oracle SQL. This book is a one-stop introduction to everything you need to know about getting started developing an Oracle Database. You'll learn about foundational concepts, setting up a simple schema, adding data, reading data from the database, and making changes. No experience with databases is required to get started. Examples in the book are built around Oracle Live SQL, a freely available, online sandbox for practicing and experimenting with SQL statements, and Oracle Express Edition, a free version of Oracle Database that is available for download. A marquee feature of Beginning Oracle SQL for Oracle Database 18c is the small chapter size. Content is divided into easily digestible chunks that can be read and practiced in very short intervals of time, making this the ideal book for a busy professional to learn from. Even just a 15-20 minute block of free time can be put to good use. AuthorBen Brumm begins by helping you understand what a database is, and getting you set up with a sandbox in which to practice the SQL that you are learning. From there, easily digestible chapters cover, point-by-point, the different aspects of writing queries to get data out of a database. You’ll also learn about creating tables and getting data into the database. Crucial topics such as working with nulls and writing analytic queries are given the attention they deserve, helping you to avoid pitfalls when writing queries for production use. What You'll Learn Create, update, and delete tables in an Oracle database Add, update, delete data from those database tables Query and view data stored in your database Manipulate and transform data using in-built database functions and features Correctly choose when to use Oracle-specific syntax and features Who This Book Is For Those new to Oracle who are planning to develop software using Oracle as the back-end data store. The book is also for those who are getting started in software development and realize they need to learn some kind of database language. Those who are learning software development on the side of their normal job, or learning it as a college student, who are ready to learn what a database is and how to use it also will find this book useful.

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.

Organizations of all sizes face the challenge of managing massive volumes of increasingly valuable data. But storing this data can be costly, and extracting value from the data is becoming more difficult. IT organizations have limited resources but must stay responsive to dynamic environments and act quickly to consolidate, simplify, and optimize their IT infrastructures. The IBM® Storwize® V5000 Gen2 system provides a smarter solution that is affordable, easy to use, and self-optimizing, which enables organizations to overcome these storage challenges. The Storwize V5000 Gen2 delivers efficient, entry-level configurations that are designed to meet the needs of small and midsize businesses. Designed to provide organizations with the ability to consolidate and share data at an affordable price, the Storwize V5000 Gen2 offers advanced software capabilities that are found in more expensive systems. This IBM Redbooks® publication is intended for pre-sales and post-sales technical support professionals and storage administrators. It applies to the Storwize V5030, V5020, and V5010, and to IBM Spectrum Virtualize™ V8.2.1.

As workloads are being offloaded to IBM® LinuxONE based cloud environments, it is important to ensure that these workloads and environments are secure. This IBM Redbooks® publication describes the necessary steps to secure your environment from the hardware level through all of the components that are involved in a LinuxONE cloud infrastructure that use Linux and IBM z/VM®. The audience for this book is IT architects, IT Specialists, and those users who plan to use LinuxONE for their cloud environments.

This IBM® Redpaper™ publication shows you how to deploy a database instance within a container using an IBM Cloud™ Private cluster on IBM Z®. A preinstalled IBM Spectrum™ Scale 5.0.3 cluster file system provides back-end storage for the persistent volumes bound to the database. A container is a standard unit of software that packages code and all its dependencies, so the application runs quickly and reliably from one computing environment to another. By default, containers are ephemeral. However, stateful applications, such as databases, require some type of persistent storage that can survive service restarts or container crashes. IBM provides several products helping organizations build an environment on an IBM Z infrastructure to develop and manage containerized applications, including dynamic provisioning of persistent volumes. As an example for a stateful application, this paper describes how to deploy the relational database MariaDB using a Helm chart. The IBM Spectrum Scale V5.0.3 cluster file system is providing back-end storage for the persistent volumes. This document provides step-by-step guidance regarding how to install and configure the following components: IBM Cloud Private 3.1.2 (including Kubernetes) Docker 18.03.1-ce IBM Storage Enabler for Containers 2.0.0 and 2.1.0 This Redpaper demonstrates how we set up the example for a stateful application in our lab. The paper gives you insights about planning for your implementation. IBM Z server hardware, the IBM Z hypervisor z/VM®, and the IBM Spectrum Scale cluster file system are prerequisites to set up the example environment. The Redpaper is written with the assumption that you have familiarity with and basic knowledge of the software products used in setting up the environment. The intended audience includes the following roles: Storage administrators IT/Cloud administrators Technologists IT specialists

Data professionals are confronting the most disruptive change since relational databases appeared in the 1980s. SQL is still a major tool for data analytics, but conventional relational database management systems can’t handle the increasing size and complexity of today’s datasets. This updated edition teaches you best practices for Greenplum Database, the open source massively parallel processing (MPP) database that accommodates large sets of nonrelational and relational data. Marshall Presser, field CTO at Pivotal, introduces Greenplum’s approach to data analytics and data-driven decisions, beginning with its shared-nothing architecture. IT managers, developers, data analysts, system architects, and data scientists will all gain from exploring data organization and storage, data loading, running queries, and learning to perform analytics in the database. Discover how MPP and Greenplum will help you go beyond the traditional data warehouse. This ebook covers: Greenplum features, use case examples, and techniques for optimizing use Four Greenplum deployment options to help you balance security, cost, and time to usability Why each networked node in Greenplum’s architecture includes an independent operating system, memory, and storage Additional tools for monitoring, managing, securing, and optimizing query responses in the Pivotal Greenplum commercial database