Ibm Cloud Pak For Data
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Ibm Cloud Pak For Data On Ibm Z
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Author : Jasmeet Bhatia
language : en
Publisher: IBM Redbooks
Release Date : 2025-03-31
Ibm Cloud Pak For Data On Ibm Z written by Jasmeet Bhatia and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Computers categories.
Most industries are susceptible to fraud, which poses a risk to both businesses and consumers. According to The National Health Care Anti-Fraud Association, health care fraud alone causes the nation around $68 billion annually. This statistic does not include the numerous other industries where fraudulent activities occur daily. In addition, the growing amount of data that enterprises own makes it difficult for them to detect fraud. Businesses can benefit by using an analytical platform to fully integrate their data with artificial intelligence (AI) technology. With IBM Cloud Pak® for Data on IBM Z, enterprises can modernize their data infrastructure, develop, and deploy machine learning (ML) and AI models, and instantiate highly efficient analytics deployment on IBM LinuxONE. Enterprises can create cutting-edge, intelligent, and interactive applications with embedded AI, colocate data with commercial applications, and use AI to make inferences. This IBM Redguide publication presents a high-level overview of IBM Z. It describes IBM Cloud Pak for Data (CP4D) on IBM Z and IBM LinuxONE, the different features that are supported on the platform, and how the associated features can help enterprise customers in building AI and ML models by using core transactional data, which results in decreased latency and increased throughput. This publication highlights real-time CP4D on IBM Z use cases. Real-time Clearing and Settlement Transactions, Trustworthy AI and its Role in Day-To-Day Monitoring, and the Prevention of Retail Crimes are use cases that are described in this publication. Using CP4D on IBM Z and LinuxONE, this publication shows how businesses can implement a highly efficient analytics deployment that minimizes latency, cost inefficiencies, and potential security exposures that are connected with data transportation.
Ibm Cloud Pak For Data
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Author : Hemanth Manda
language : en
Publisher: Packt Publishing
Release Date : 2021-10-08
Ibm Cloud Pak For Data written by Hemanth Manda and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-08 with categories.
Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key Features: Explore data virtualization by accessing data in real time without moving it Unify the data and AI experience with the integrated end-to-end platform Explore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scale Book Description: Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What You Will Learn: Understand the importance of digital transformations and the role of data and AI platforms Get to grips with data architecture and its relevance in driving AI adoption using IBM's AI Ladder Understand Cloud Pak for Data, its value proposition, capabilities, and unique differentiators Delve into the pricing, packaging, key use cases, and competitors of Cloud Pak for Data Use the Cloud Pak for Data ecosystem with premium IBM and third-party services Discover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVs Who this book is for: This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.
Ibm Cloud Pak For Data Version 4 5 A Practical Hands On Guide With Best Practices Examples Use Cases And Walk Throughs
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Author : Simon Cambridge
language : en
Publisher: IBM Redbooks
Release Date : 2024-11-11
Ibm Cloud Pak For Data Version 4 5 A Practical Hands On Guide With Best Practices Examples Use Cases And Walk Throughs written by Simon Cambridge and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-11 with Computers categories.
IBM Cloud Pak for Data platform is a unified, integrated and collaborative data and artificial intelligence (AI) platform that helps organizations collect, organize, and analyze data and infuse AI within and across business process and applications. Its ultimate goal is to deliver deeper business insights that enable smarter business outcomes. IBM Cloud Pak for Data delivers a set of capabilities core to a data fabric. A data fabric can help organizations improve productivity and reduce complexities when accessing, managing, and understanding disparate, siloed data that is distributed across a hybrid cloud landscape. The platform offers a wide selection of IBM and third-party services that span the entire data lifecycle. Deployment options include an on-premises software version that is built on the Red Hat OpenShift Container Platform, and a fully or partially managed version that can run on the IBM Cloud, and other hyper-scalers, such as Amazon Web Services (AWS) and Microsoft Azure. This IBM Redbooks publication provides a broad understanding of the IBM Cloud Pak for Data concepts and architecture, and the services that are available in the product. In addition, several common use cases and hands-on scenarios are included that help you better understand the capabilities of this product. This publication is for IBM Cloud Pak for Data customers who seek best practices and real-world examples of how to best implement their solutions while optimizing the value of their existing and future technology, data, and skills investments.
Ibm Cloud Pak For Data With Ibm Spectrum Scale Container Native
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Author : Gero Schmidt
language : en
Publisher: IBM Redbooks
Release Date : 2021-12-17
Ibm Cloud Pak For Data With Ibm Spectrum Scale Container Native written by Gero Schmidt and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-17 with Computers categories.
This IBM® Redpaper® publication describes configuration guidelines and best practices when IBM Spectrum® Scale Container Native Storage Access is used as a storage provider for IBM Cloud® Pak for Data on Red Hat OpenShift Container Platform. It also provides the steps to install IBM Db2® and several assemblies within IBM Cloud Pak® for Data, including Watson Knowledge Catalog, Watson Studio, IBM DataStage®, Db2 Warehouse, Watson Machine Learning, Watson OpenScale, Data Virtualization, Data Management Console, and Apache Spark. This IBM Redpaper publication was written for IT architects, IT specialists, developers, and others who are interested in installing IBM Cloud Pak for Data with IBM Spectrum Scale Container Native.
Ibm Storage Fusion Backup And Restore For Ibm Cloud Pak For Data
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Author : Paulina Acevedo
language : en
Publisher: IBM Redbooks
Release Date : 2023-06-07
Ibm Storage Fusion Backup And Restore For Ibm Cloud Pak For Data written by Paulina Acevedo and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-07 with Computers categories.
IBM Cloud Pak® for Data can be protected with IBM Spectrum FusionTM. This IBM Redpaper publication covers backing up IBM Cloud Pak for Data with a non-disruptive (online) backup and then restoring to an alternate cluster. During an online backup, normal runtime operations in the Cloud Pak for Data cluster continue while the backup completes. The backup process includes creating policies and automating backups in IBM Spectrum Fusion, then protecting Cloud Pak for Data, protecting IBM Spectrum Fusion namespace and the IBM Spectrum® Protect Plus (SPP) catalog. Backup and restore is supported from IBM Storage Fusion HCI to IBM Spectrum Fusion software as well as from IBM Storage Fusion Software to IBM Storage Fusion HCI. IBM Spectrum Fusion HCI and IBM Spectrum Fusion have become IBM Storage Fusion HCI System and IBM Storage Fusion. This edition uses the IBM Spectrum brand names and will be updated with the next edition. IBM Spectrum Fusion must be at 2.3 or higher with "Backup" service installed. If using IBM Storage Fusion 2.5.2, the "Backup (Legacy)" service should be used.
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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Author : Joseph Dain
language : en
Publisher: IBM Redbooks
Release Date : 2020-08-11
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover written by Joseph Dain and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-11 with Computers categories.
This IBM® Redpaper publication explains how IBM Spectrum® Discover integrates with the IBM Watson® Knowledge Catalog (WKC) component of IBM Cloud® Pak for Data (IBM CP4D) to make the enriched catalog content in IBM Spectrum Discover along with the associated data available in WKC and IBM CP4D. From an end-to-end IBM solution point of view, IBM CP4D and WKC provide state-of-the-art data governance, collaboration, and artificial intelligence (AI) and analytics tools, and IBM Spectrum Discover complements these features by adding support for unstructured data on large-scale file and object storage systems on premises and in the cloud. Many organizations face challenges to manage unstructured data. Some challenges that companies face include: Pinpointing and activating relevant data for large-scale analytics, machine learning (ML) and deep learning (DL) workloads. Lacking the fine-grained visibility that is needed to map data to business priorities. Removing redundant, obsolete, and trivial (ROT) data and identifying data that can be moved to a lower-cost storage tier. Identifying and classifying sensitive data as it relates to various compliance mandates, such as the General Data Privacy Regulation (GDPR), Payment Card Industry Data Security Standards (PCI-DSS), and the Health Information Portability and Accountability Act (HIPAA). This paper describes how IBM Spectrum Discover provides seamless integration of data in IBM Storage with IBM Watson Knowledge Catalog (WKC). Features include: Event-based cataloging and tagging of unstructured data across the enterprise. Automatically inspecting and classifying over 1000 unstructured data types, including genomics and imaging specific file formats. Automatically registering assets with WKC based on IBM Spectrum Discover search and filter criteria, and by using assets in IBM CP4D. Enforcing data governance policies in WKC in IBM CP4D based on insights from IBM Spectrum Discover, and using assets in IBM CP4D. Several in-depth use cases are used that show examples of healthcare, life sciences, and financial services. IBM Spectrum Discover integration with WKC enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of data. The integration improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.
Become Data Driven With Ibm Z Infused Data Fabric
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Author : Makenzie Manna
language : en
Publisher: IBM Redbooks
Release Date : 2022-08-02
Become Data Driven With Ibm Z Infused Data Fabric written by Makenzie Manna and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-02 with Computers categories.
The expansion of digital transformation initiatives resulted in the exponential rise of data generation. It is now apparent that for organizations to meet their rapidly changing business needs, they must use their most current data to fuel their insights. However, how to do so efficiently and effectively is still a challenge for most organizations that are trying to solve today’s complex business problems. Contributing to this challenge is that organizations are turning to a hybrid cloud approach of their IT infrastructure, scaling to include on-premises and cloud environments, in response to the data growth. This approach results in the requirement to integrate various data formats from disparate data sources into a central and unified view for use in analytics and AI, with security and privacy as a top priority. As a solution, organizations are adopting the emerging architectural approach. This approach enables efficient data integration across environments, simplifies the delivery of disparate data throughout an organization, and enables self-service data consumption and governance. Organizations with investments in the IBM Z platform have a unique opportunity to integrate them into their data fabric strategy. A data fabric strategy makes mission-critical data that is on Z readily available for real-time decision making by using data where it originates, which achieves faster time-to-insight. This IBM Redbooks publication introduces the emerging concept of a data fabric and how integration of valuable data that is stored on IBM Z enables deeper insights and improved AI capabilities. The intended audience for this publication includes data science professionals, such as Data Stewards, who want to develop and implement practices for building out a data governance framework that is facilitated by data fabric for AI workloads on IBM Z. The audience also can include anyone who wants to use the rich capabilities of the IBM Z environment by using a data fabric that is infused with their business-critical data and applications that are on the platform.
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover
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Author : Joseph Dain
language : en
Publisher:
Release Date : 2020
Cataloging Unstructured Data In Ibm Watson Knowledge Catalog With Ibm Spectrum Discover written by Joseph Dain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Database management categories.
Turning Data Into Insight With Machine Learning For Ibm Z Os
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Author : Makenzie Manna
language : en
Publisher: IBM Redbooks
Release Date : 2025-08-06
Turning Data Into Insight With Machine Learning For Ibm Z Os written by Makenzie Manna and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-06 with Computers categories.
The exponential growth in data over the last decade coupled with a drastic adoption of artificial intelligence has opened organizations up to valuable insights, opportunities for improvements in efficiency, increases in profits, and overall deliver more business value both internally to employees and shareholders and externally to clients and consumers. The data that fuels these insights is the foundation that these organizations must tap in to innovate and they must capitalize on the most advanced AI capabilities to stay ahead of the competition, and they must do so in a secure environment that protects the data throughout its lifecycle and data access in real-time at any time. When it comes to security, nothing can rival IBM Z, the multi-workload transactional platform that powers the core business processes of the majority of the Fortune 500 enterprises with unmatched security, availability, reliability, and scalability. With core transactions and data originating on IBM Z , it simply makes sense for AI to exist and run on the same platform. For years, some businesses chose to move their sensitive data off IBM Z, however, the massive growth of digital data, the punishing cost of security exposures as well as the unprecedented demand for instant actionable intelligence from data in real time have convinced them to rethink that decision and, instead, embrace the strategy of data gravity for AI. Transaction gravity is the other force here which eludes to the trillions of transactions that move through IBM Z as it hosts some of the worlds most mission critical workloads that runs the global economy. It is this dual strategy of data and transaction gravity that sets IBM Z apart. For organizations to get real-time business and operational insights at scale, the AI workloads must be co-located with the transactional applications and where the data originates. IBM Z has made tremendous invests in this space, starting at the hardware silicon level with the industry first Telum on-chip AI inference accelerator introduced with IBM z16 all the way up the stack with our enterprise grade AI/ML software offerings with a robust and optimized open source ecosystem support. Machine Learning for IBM z/OS is one of IBM's flagship offerings that helps organizations deploy machine learning models on IBM z/OS environments natively close to their most mission critical workloads and infuse them with AI. In the inherently secure Z environment, your machine learning scoring services can co-exist with your transactional applications and data, supporting high throughput and minimizing response time while delivering consistent service level agreements (SLAs). This book introduces Machine Learning for IBM z/OS version 3.1.0 and describes its unique value proposition in addition to the business value of AI on the IBM Z platform. It provides guidance for you to get started with aligning your business goals and use cases for AI. It outlines the various patterns for accessing and consuming IBM Z data in on-premises, cloud, and hybrid environments. It discusses in detail the steps and best practices for model building, deployment, and inferencing and post deployment monitoring. The book includes examples of how you can use the versatile and intuitive web user interface of MLz to quickly train, evaluate, and deploy a model. Through a batch job elapsed time prediction example, the book explores the value of MLz in such a use case and shows how to apply the batch job elapsed time model with MLz for application integration and provides insight into how MLz can be leveraged within machine learning operations to operationalize AI on IBM Z. Most importantly, it examines use cases across industries to illustrate how you can easily turn your massive data into valuable insights with Machine Learning for IBM z/OS.
Enabling Ibm Cloud Pak For Multicloud Management To Connect Kubernetes Clusters Using Ibm Secure Gateway
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Author : Michael Bubel
language : en
Publisher: IBM Redbooks
Release Date : 2020-11-20
Enabling Ibm Cloud Pak For Multicloud Management To Connect Kubernetes Clusters Using Ibm Secure Gateway written by Michael Bubel and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-20 with Computers categories.
In today's dynamically changing IT landscape, it is highly likely that a company's cloud strategy spans multiple cloud providers. Such a span is known as the hydrid multi-cloud landscape. The challenges that quickly surface in an IT department's list of responsibilities now encompass managing environments that are running on multiple cloud providers. The traditional IT administrators find themselves using individual dashboards for each of the cloud providers to monitor and manage those environments. In turn, each of the cloud provider's dashboards have their own unique features that require a learning curve to become productive. The traditional IT administrator must now become a specialized hybrid cloud engineer with different hats for each of the cloud providers. This dynamic led to the quick realization of the need for a tool that provides a common dashboard for managing a company's hybrid cloud landscape. IBM® is one such company that quickly recognized this need and used their experience in years of systems management tools created the IBM Cloud® Pak for Multicloud Management. This paper describes the steps that are required to connect a Kubernetes management dashboard that is provided with the IBM Cloud Pak® for Multicloud Management running on an on-premises private cloud to Kubernetes clusters that are running on public clouds. An IBM Cloud service that is called IBM Secure Gateway is at the core of this connection. The procedure to set up the Kubernetes clusters to use the IBM Secure Gateway service also is described this paper.