IBM Storage for Red Hat OpenShift is a comprehensive container-ready solution that includes all the hardware & software components necessary to setup and/or expand your Red Hat OpenShift environment. This blueprint includes Red Hat OpenShift Container Platform and uses Container Storage Interface (CSI) standards. IBM Storage brings enterprise data services to containers. In this blueprint, learn how to: · Combine the benefits of IBM Systems with the performance of IBM Storage solutions so that you can deliver the right services to your clients today! · Build a 24 by 7 by 365 enterprise class private cloud with Red Hat OpenShift Container Platform utilizing new open source Container Storage interface (CSI) drivers · Leverage enterprise class services such as NVMe based flash performance, high data availability, and advanced container security IBM Storage for Red Hat OpenShift Container Platform is designed for your DevOps environment for on-premises deployment with easy-to-consume components built to perform and scale for your enterprise. Simplify your journey to cloud with pre-tested and validated blueprints engineered to enable rapid deployment and peace of mind as you move to a hybrid multicloud environment. You now have the capabilities.

This IBM® Redpaper Redbooks publication provides information and concepts about how to take advantage of SAP HANA and IBM Power Systems features to manage data and performance efficiently. The target audience of this book includes architects, IT specialists, and systems administrators who deploy SAP HANA and manage data and SAP system performance.

Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.

O’Reilly usage analysis shows continued growth in AI/ML and early signs that organizations are experimenting with advanced tools and methods.

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. About the Technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the Book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's Inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the Reader For readers who want to begin or advance a data science career. About the Authors Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Quotes Full of useful advice, real-case scenarios, and contributions from professionals in the industry. - Sebastián Palma Mardones, ArchDaily The perfect companion for someone who wants to be a successful data scientist! - Gustavo Gomes, Brightcove Insightful overview of all aspects of a data science career. - Krzysztof Jędrzejewski, Pearson Highly recommended. - Hagai Luger, Clarizen

Graph data closes the gap between the way humans and computers view the world. While computers rely on static rows and columns of data, people navigate and reason about life through relationships. This practical guide demonstrates how graph data brings these two approaches together. By working with concepts from graph theory, database schema, distributed systems, and data analysis, you’ll arrive at a unique intersection known as graph thinking. Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases. You’ll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application. Build an example application architecture with relational and graph technologies Use graph technology to build a Customer 360 application, the most popular graph data pattern today Dive into hierarchical data and troubleshoot a new paradigm that comes from working with graph data Find paths in graph data and learn why your trust in different paths motivates and informs your preferences Use collaborative filtering to design a Netflix-inspired recommendation system

For decades, businesses have used information about their customers to make critical decisions on what to stock in inventory, which items to recommend to customers, and when to run promotions. But the advent of big data early in this century changed the game considerably. The key to achieving a competitive advantage today is the ability to process and store ever-increasing amounts of information that affect those decisions. In this report, solutions specialists from Red Hat provide an architectural guide to help you navigate the modern data analytics ecosystem. You’ll learn how the industry has evolved and examine current approaches to storage. That includes a deep dive into the anatomy of a portable data platform architecture, along with several aspects of running data pipelines and intelligent applications with Kubernetes. Explore the history of open source data processing and the evolution of container scheduling Get a concise overview of intelligent applications Learn how to use storage with Kubernetes to produce effective intelligent applications Understand how to structure applications on Kubernetes in your platform architecture Delve into example pipeline architectures for deploying intelligent applications on Kubernetes

This IBM® Redpaper publication provides SAP HANA platform migration information and details for successful planning for migration to IBM Power Systems servers. This publication addresses topics for sellers, IT architects, IT specialists, and anyone who wants to migrate and manage SAP 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.

Real-life examples of how to apply intelligence in the healthcare industry through innovative analytics Healthcare analytics offers intelligence for making better healthcare decisions. Identifying patterns and correlations contained in complex health data, analytics has applications in hospital management, patient records, diagnosis, operating and treatment costs, and more. Helping healthcare managers operate more efficiently and effectively. Transforming Healthcare Analytics: The Quest for Healthy Intelligence shares real-world use cases of a healthcare company that leverages people, process, and advanced analytics technology to deliver exemplary results. This book illustrates how healthcare professionals can transform the healthcare industry through analytics. Practical examples of modern techniques and technology show how unified analytics with data management can deliver insight-driven decisions. The authors—a data management and analytics specialist and a healthcare finance executive—share their unique perspectives on modernizing data and analytics platforms to alleviate the complexity of the healthcare, distributing capabilities and analytics to key stakeholders, equipping healthcare organizations with intelligence to prepare for the future, and more. This book: Explores innovative technologies to overcome data complexity in healthcare Highlights how analytics can help with healthcare market analysis to gain competitive advantage Provides strategies for building a strong foundation for healthcare intelligence Examines managing data and analytics from end-to-end, from diagnosis, to treatment, to provider payment Discusses the future of technology and focus areas in the healthcare industry Transforming Healthcare Analytics: The Quest for Healthy Intelligence is an important source of information for CFO’s, CIO, CTO, healthcare managers, data scientists, statisticians, and financial analysts at healthcare institutions.

This book presents fundamentals in MATLAB programming, including data and statement structures, control structures, function writing and bugging in MATLAB programming, followed by the presentations of algebraic computation, transcendental function evaluations and data processing. Advanced topics such as MATLAB interfacing, object-oriented programming and graphical user interface design are also addressed.

"DAX Cookbook: Over 120 recipes to enhance your business with analytics, reporting, and business intelligence" is the ultimate guidebook for mastering DAX (Data Analysis Expressions) in business intelligence, Power BI, and SQL Server Analysis Services. With hands-on examples and extensive recipes, it enables professionals to solve real-world data challenges effectively. What this Book will help me do Understand how to create tailored calculations for dates, time, and duration to enhance data insights. Develop key performance indicators (KPIs) and advanced business metrics for strategic decision-making. Master text and numerical data transformations to construct dynamic dashboards and reports. Optimize data models and DAX queries for improved performance and analytics accuracy. Learn to handle and debug calculations, and implement complex statistical and mathematical measures. Author(s) Greg Deckler is a seasoned business intelligence professional with extensive experience in using DAX and Power BI to provide actionable insights. As a recognized expert in the field, Greg brings practical knowledge of developing scalable BI solutions. His teaching approach is rooted in clarity and real-world application, making complex topics accessible to learners of all levels. Who is it for? This book is perfect for business professionals, BI developers, and data analysts with basic knowledge of the DAX language and associated tools. If you are looking to enhance your DAX skills and solve tough analytical challenges, this book is tailored for you. It's highly relevant for those aiming to optimize business intelligence workflows and improve data-driven decisions.

This IBM® Redbooks® publication gives a broad understanding of storage clouds and the initial functionality that was introduced for mainframes to have Transparent Cloud Tiering. IBM DFSMS and the IBM DS8000 added functionality to provide elements of serverless data movement, and for IBM z/OS® to communicate with a storage cloud. The function is known as Transparent Cloud Tiering and is composed of the following key elements: A gateway in the DS8000, which allows the movement of data to and from Object Storage by using a network connection, with the option to encrypt data in the Cloud. DFSMShsm enhancements to support Migrate and Recall functions to and from the Object Storage. Other commands were enhanced to monitor and report on the new functionality. DFSMShsm uses the Web Enablement toolkit for z/OS to create and access the metadata for specific clouds, containers, and objects. DFSMSdss enhancements to provide some basic backup and restore functions to and from the cloud. The IBM TS7700 can also be set up to act as if it were cloud storage from the DS8000 perspective. This IBM Redbooks publication is divided into the following parts: Part 1 provides you with an introduction to clouds. Part 2 shows you how we set up the Transparent Cloud Tiering in a controlled laboratory and how the new functions work. We provide points to consider to help you set up your storage cloud and integrate it into your operational environment. Part 3 shows you how we used the new functionality to communicate with the cloud and to send data and retrieve data from it..

Building on over 20 years of virtual tape experience, the TS7700 (TS7760, TS7770) now supports the ability to store virtual tape volumes in an object store. This IBM® Redpaper publication helps you set up and configure the cloud object storage support for IBM Cloud™ Object Storage (COS) or Amazon Simple Storage Service (Amazon S3). The TS7700 supported off loading to physical tape for over two decades. Off loading to physical tape behind a TS7700 is used by hundreds of organizations around the world. By using the same hierarchical storage techniques, the TS7700 can also off load to object storage. Because object storage is cloud-based and accessible from different regions, the TS7700 Cloud Storage Tier support essentially allows the cloud to be an extension of the grid. In this IBM Redpaper publication, we provide a brief overview of cloud technology with an emphasis on Object Storage. Object Storage is used by a broad set of technologies, including those technologies that are exclusive to IBM Z®. The aim of this publication is to provide a basic understanding of cloud, Object Storage, and different ways it can be integrated into your environment. This Redpaper is intended for system architects and storage administrators with TS7700 experience who want to add the support of a Cloud Storage Tier to their TS7700 solution. Note: As of this writing, the TS7700C supports the ability to offload to on-premise cloud with IBM Cloud Object Storage and public cloud with Amazon S3.

Grasp the essentials of JMP to generate rapid results. JMP Essentials: An Illustrated Guide for New Users, Third Edition, is designed for new or novice JMP users who need to generate meaningful analysis quickly. The book focuses on the most commonly used platforms and typical workflow of the user, from data importing, exploring, and visualizing to modeling and sharing results with others. Throughout the book, the authors emphasize results over theory, providing just the essential steps with corresponding screenshots. In most cases, each section completes a JMP task, which maximizes the book’s utility as a reference. This edition has new instructions and screenshots reflecting the features added to the latest release of JMP software, including updated sections on JMP Dashboard Builder, Query Builder, the Fit Model platform, JMP Public and JMP Live, and a more detailed look at the JMP website. Each chapter contains a family of features that are carefully crafted to first introduce you to basic features and then move on to more advanced topics. JMP Essentials: An Illustrated Guide for New Users, Third Edition, is the quickest and most accessible reference book available.

Identify, analyze, and improve poorly performing queries that damage user experience and lead to lost revenue for your business. This book will help you make query tuning an integral part of your daily routine through a multi-step process that includes monitoring of execution times, identifying candidate queries for optimization, analyzing their current performance, and improving them to deliver results faster and with less overhead. Author Jesper Krogh systematically discusses each of these steps along with the data sources and the tools used to perform them. MySQL 8 Query Performance Tuning aims to help you improve query performance using a wide range of strategies. You will know how to analyze queries using both the traditional EXPLAIN command as well as the new EXPLAIN ANALYZE tool. You also will see how to use the Visual Explain feature to provide a visually-oriented view of an execution plan. Coverage of indexes includes indexing strategies and index statistics, and you will learn how histograms can be used to provide input on skewed data distributions that the optimizer can use to improve query performance. You will learn about locks, and how to investigate locking issues. And you will come away with an understanding of how the MySQL optimizer works, including the new hash join algorithm, and how to change the optimizer’s behavior when needed to deliver faster execution times. You will gain the tools and skills needed to delight application users and to squeeze the most value from corporate computing resources. What You Will Learn Monitor query performance to identify poor performers Choose queries to optimize that will provide the greatest gain Analyze queries using tools such as EXPLAIN ANALYZE and Visual Explain Improve slow queries through a wide range of strategies Properly deploy indexes and histograms to aid in creating fast execution plans Understand and analyze locks to resolve contention and increase throughput Who This Book Is For Database administrators and SQL developers who are familiar with MySQL and need to participate in query tuning. While some experience with MySQL is required, no prior knowledge of query performance tuning is needed.

Obtain all the skills you need to configure and manage a PostgreSQL database. In this book you will begin by installing and configuring PostgreSQL on a server by focusing on system-level parameter settings before installation. You will also look at key post-installation steps to avoid issues in the future. The basic configuration of PostgreSQL is tuned for compatibility rather than performance. Keeping this in mind, you will fine-tune your PostgreSQL parameters based on your environment and application behavior. You will then get tips to improve database monitoring and maintenance followed by database security for handling sensitive data in PostgreSQL. Every system containing valuable data needs to be backed-up regularly. PostgreSQL follows a simple back-up procedure and provides fundamental approaches to back up your data. You will go through these approaches and choose the right one based on your environment. Running your application with limited resources can be tricky. To achieve this you will implement a pooling mechanism for your PostgreSQL instances to connect to other databases. Finally, you will take a look at some basic errors faced while working with PostgreSQL and learn to resolve them in the quickest manner. What You Will Learn Configure PostgreSQL for performance Monitor and maintain PostgreSQL instances Implement a backup strategy for your data Resolve errors faced while using PostgreSQL Who This Book Is For Readers with basic knowledge of PostgreSQL who wish to implement key solutions based on their environment.

Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.

Built on over 50 years of Enterprise storage expertise, the IBM® DS8000® series is the flagship of disk storage systems within the IBM System Storage™ portfolio. As of September 2019, the DS8900F is the latest addition and offers two new classes: DS8910F: Flexibility Class all-flash DS8950F: Agility Class all-flash The agility class is efficiently designed to consolidate all your mission-critical workloads for IBM Z®, IBM LinuxONE, IBM Power Systems, and distributed environments under a single all-flash storage solution. This IBM Redbooks® Product Guide gives an overview of the features and functions that are available with the IBM DS8900F models running microcode Release 9.0 (Bundle 89.0 / Licensed Machine Code 7.9.0.xxx).

This IBM® Redbooks® publication provides both introductory information and technical details about the IBM System z® Personal Development Tool (IBM zPDT®), which produces a small System z environment suitable for application development. zPDT is a PC Linux application. When zPDT is installed (on Linux), normal System z operating systems (such as IBM z/OS®) can be run on it. zPDT provides the basic System z architecture and emulated IBM 3390 disk drives, 3270 interfaces, OSA interfaces, and so on. The systems that are discussed in this document are complex. They have elements of Linux (for the underlying PC machine), IBM z/Architecture® (for the core zPDT elements), System z I/O functions (for emulated I/O devices), z/OS (the most common System z operating system), and various applications and subsystems under z/OS. The reader is assumed to be familiar with general concepts and terminology of System z hardware and software elements, and with basic PC Linux characteristics. This book provides the primary documentation for zPDT.

Conquer SQL Server 2019 administration–from the inside out Dive into SQL Server 2019 administration–and really put your SQL Server DBA expertise to work. This supremely organized reference packs hundreds of timesaving solutions, tips, and workarounds–all you need to plan, implement, manage, and secure SQL Server 2019 in any production environment: on-premises, cloud, or hybrid. Six experts thoroughly tour DBA capabilities available in SQL Server 2019 Database Engine, SQL Server Data Tools, SQL Server Management Studio, PowerShell, and Azure Portal. You’ll find extensive new coverage of Azure SQL, big data clusters, PolyBase, data protection, automation, and more. Discover how experts tackle today’s essential tasks–and challenge yourself to new levels of mastery. Explore SQL Server 2019’s toolset, including the improved SQL Server Management Studio, Azure Data Studio, and Configuration Manager Design, implement, manage, and govern on-premises, hybrid, or Azure database infrastructures Install and configure SQL Server on Windows and Linux Master modern maintenance and monitoring with extended events, Resource Governor, and the SQL Assessment API Automate tasks with maintenance plans, PowerShell, Policy-Based Management, and more Plan and manage data recovery, including hybrid backup/restore, Azure SQL Database recovery, and geo-replication Use availability groups for high availability and disaster recovery Protect data with Transparent Data Encryption, Always Encrypted, new Certificate Management capabilities, and other advances Optimize databases with SQL Server 2019’s advanced performance and indexing features Provision and operate Azure SQL Database and its managed instances Move SQL Server workloads to Azure: planning, testing, migration, and post-migration