Author: Gero Schmidt
Publisher: IBM Redbooks
ISBN: 0738460095
Category : Computers
Languages : en
Pages : 120
Book Description
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 Cloud Pak for Data with IBM Spectrum Scale Container Native
Author: Gero Schmidt
Publisher: IBM Redbooks
ISBN: 0738460095
Category : Computers
Languages : en
Pages : 120
Book Description
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.
Publisher: IBM Redbooks
ISBN: 0738460095
Category : Computers
Languages : en
Pages : 120
Book Description
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 Cloud Pak for Data
Author: Hemanth Manda
Publisher: Packt Publishing Ltd
ISBN: 1800567405
Category : Computers
Languages : en
Pages : 337
Book Description
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 FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook 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 learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho 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.
Publisher: Packt Publishing Ltd
ISBN: 1800567405
Category : Computers
Languages : en
Pages : 337
Book Description
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 FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook 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 learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho 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.
SingleStore Database on High Performance IBM Spectrum Scale Filesystem with Red Hat OpenShift and IBM Cloud Pak for Data
Author: Nilesh Suryawanshi
Publisher: IBM Redbooks
ISBN: 0738460818
Category : Computers
Languages : en
Pages : 34
Book Description
This IBM® blueprint describes the SingleStoreDB that is running on Red Hat OpenShift in a containerized environment. The SingleStoreDB deployment uses the IBM Spectrum® Scale container native access storage class to create persistent volumes (PVs) for the SingleStoreDB pods deployment. This document also describes the process that is used to expand a SingleStoreDB volume on IBM Spectrum Scale and an IBM Spectrum Scale PV on a Red Hat OpenShift cluster for IBM Spectrum Scale to verify that the SingleStoreDB remained intact after the volume is expanded. The procedure to create a sample database that is named stockDB, and the data analytical stats for reading and writing the data also are included. The sample data was captured for comparison statistics for SingleStoreDB that is deployed on the IBM Spectrum Scale Cluster File System and local storage. These comparison statistics emphasize the notable difference between the sample data sets. Finally, this document also explains the procedure that is used to create the same sample database with the unlimited storage feature in SingleStore by using IBM Cloud® Object Storage.
Publisher: IBM Redbooks
ISBN: 0738460818
Category : Computers
Languages : en
Pages : 34
Book Description
This IBM® blueprint describes the SingleStoreDB that is running on Red Hat OpenShift in a containerized environment. The SingleStoreDB deployment uses the IBM Spectrum® Scale container native access storage class to create persistent volumes (PVs) for the SingleStoreDB pods deployment. This document also describes the process that is used to expand a SingleStoreDB volume on IBM Spectrum Scale and an IBM Spectrum Scale PV on a Red Hat OpenShift cluster for IBM Spectrum Scale to verify that the SingleStoreDB remained intact after the volume is expanded. The procedure to create a sample database that is named stockDB, and the data analytical stats for reading and writing the data also are included. The sample data was captured for comparison statistics for SingleStoreDB that is deployed on the IBM Spectrum Scale Cluster File System and local storage. These comparison statistics emphasize the notable difference between the sample data sets. Finally, this document also explains the procedure that is used to create the same sample database with the unlimited storage feature in SingleStore by using IBM Cloud® Object Storage.
Securing IBM Spectrum Scale with QRadar and IBM Cloud Pak for Security
Author: IBM
Publisher: IBM Redbooks
ISBN: 0738460141
Category : Computers
Languages : en
Pages : 54
Book Description
Cyberattacks are likely to remain a significant risk for the foreseeable future. Attacks on organizations can be external and internal. Investing in technology and processes to prevent these cyberattacks is the highest priority for these organizations. Organizations need well-designed procedures and processes to recover from attacks. The focus of this document is to demonstrate how the IBM® Unified Data Foundation (UDF) infrastructure plays an important role in delivering the persistence storage (PV) to containerized applications, such as IBM Cloud® Pak for Security (CP4S), with IBM Spectrum® Scale Container Native Storage Access (CNSA) that is deployed with IBM Spectrum scale CSI driver and IBM FlashSystem® storage with IBM Block storage driver with CSI driver. Also demonstrated is how this UDF infrastructure can be used as a preferred storage class to create back-end persistent storage for CP4S deployments. We also highlight how the file I/O events are captured in IBM QRadar® and offenses are generated based on predefined rules. After the offenses are generated, we show how the cases are automatically generated in IBM Cloud Pak® for Security by using the IBM QRadar SOAR Plugin, with a manually automated method to log a case in IBM Cloud Pak for Security. This document also describes the processes that are required for the configuration and integration of the components in this solution, such as: Integration of IBM Spectrum Scale with QRadar QRadar integration with IBM Cloud Pak for Security Integration of the IBM QRadar SOAR Plugin to generate automated cases in CP4S. Finally, this document shows the use of IBM Spectrum Scale CNSA and IBM FlashSystem storage that uses IBM block CSI driver to provision persistent volumes for CP4S deployment. All models of IBM FlashSystem family are supported by this document, including: FlashSystem 9100 and 9200 FlashSystem 7200 and FlashSystem 5000 models FlashSystem 5200 IBM SAN Volume Controller All storage that is running IBM Spectrum Virtualize software
Publisher: IBM Redbooks
ISBN: 0738460141
Category : Computers
Languages : en
Pages : 54
Book Description
Cyberattacks are likely to remain a significant risk for the foreseeable future. Attacks on organizations can be external and internal. Investing in technology and processes to prevent these cyberattacks is the highest priority for these organizations. Organizations need well-designed procedures and processes to recover from attacks. The focus of this document is to demonstrate how the IBM® Unified Data Foundation (UDF) infrastructure plays an important role in delivering the persistence storage (PV) to containerized applications, such as IBM Cloud® Pak for Security (CP4S), with IBM Spectrum® Scale Container Native Storage Access (CNSA) that is deployed with IBM Spectrum scale CSI driver and IBM FlashSystem® storage with IBM Block storage driver with CSI driver. Also demonstrated is how this UDF infrastructure can be used as a preferred storage class to create back-end persistent storage for CP4S deployments. We also highlight how the file I/O events are captured in IBM QRadar® and offenses are generated based on predefined rules. After the offenses are generated, we show how the cases are automatically generated in IBM Cloud Pak® for Security by using the IBM QRadar SOAR Plugin, with a manually automated method to log a case in IBM Cloud Pak for Security. This document also describes the processes that are required for the configuration and integration of the components in this solution, such as: Integration of IBM Spectrum Scale with QRadar QRadar integration with IBM Cloud Pak for Security Integration of the IBM QRadar SOAR Plugin to generate automated cases in CP4S. Finally, this document shows the use of IBM Spectrum Scale CNSA and IBM FlashSystem storage that uses IBM block CSI driver to provision persistent volumes for CP4S deployment. All models of IBM FlashSystem family are supported by this document, including: FlashSystem 9100 and 9200 FlashSystem 7200 and FlashSystem 5000 models FlashSystem 5200 IBM SAN Volume Controller All storage that is running IBM Spectrum Virtualize software
Hybrid Cloud Infrastructure and Operations Explained
Author: Mansura Habiba
Publisher: Packt Publishing Ltd
ISBN: 1803233672
Category : Computers
Languages : en
Pages : 344
Book Description
Modernize and migrate smoothly to hybrid cloud infrastructure and successfully mitigate complexities relating to the infrastructure, platform, and production environment Key FeaturesPresents problems and solutions for application modernization based on real-life use casesHelps design and implement efficient, highly available, and scalable cloud-native applicationsTeaches you how to adopt a cloud-native culture for successful deployments on hybrid cloud platformsBook Description Most organizations are now either moving to the cloud through modernization or building their apps in the cloud. Hybrid cloud is one of the best approaches for cloud migration and the modernization journey for any enterprise. This is why, along with coding skills, developers need to know the big picture of cloud footprint and be aware of the integration models between apps in a hybrid and multi-cloud infrastructure. This book represents an overview of your end-to-end journey to the cloud. To be future agnostic, the journey starts with a hybrid cloud. You'll gain an overall understanding of how to approach migration to the cloud using hybrid cloud technologies from IBM and Red Hat. Next, you'll be able to explore the challenges, requirements (both functional and non-functional), and the process of app modernization for enterprises by analyzing various use cases. The book then provides you with insights into the different reference solutions for app modernization on the cloud, which will help you to learn how to design and implement patterns and best practices in your job. By the end of this book, you'll be able to successfully modernize applications and cloud infrastructure in hyperscaler public clouds such as IBM and hybrid clouds using Red Hat technologies as well as develop secure applications for cloud environments. What you will learnStrategize application modernization, from the planning to the implementation phaseApply cloud-native development concepts, methods, and best practicesSelect the right strategy for cloud adoption and modernizationExplore container platforms, storage, network, security, and operationsManage cloud operations using SREs, FinOps, and MLOps principlesDesign a modern data insight hub on the cloudWho this book is for This book is for cloud-native application developers involved in modernizing legacy applications by refactoring and rebuilding them. Cloud solution architects and technical leaders will also find this book useful. It will be helpful to have a basic understanding of cloud-native application development and cloud providers before getting started with this book.
Publisher: Packt Publishing Ltd
ISBN: 1803233672
Category : Computers
Languages : en
Pages : 344
Book Description
Modernize and migrate smoothly to hybrid cloud infrastructure and successfully mitigate complexities relating to the infrastructure, platform, and production environment Key FeaturesPresents problems and solutions for application modernization based on real-life use casesHelps design and implement efficient, highly available, and scalable cloud-native applicationsTeaches you how to adopt a cloud-native culture for successful deployments on hybrid cloud platformsBook Description Most organizations are now either moving to the cloud through modernization or building their apps in the cloud. Hybrid cloud is one of the best approaches for cloud migration and the modernization journey for any enterprise. This is why, along with coding skills, developers need to know the big picture of cloud footprint and be aware of the integration models between apps in a hybrid and multi-cloud infrastructure. This book represents an overview of your end-to-end journey to the cloud. To be future agnostic, the journey starts with a hybrid cloud. You'll gain an overall understanding of how to approach migration to the cloud using hybrid cloud technologies from IBM and Red Hat. Next, you'll be able to explore the challenges, requirements (both functional and non-functional), and the process of app modernization for enterprises by analyzing various use cases. The book then provides you with insights into the different reference solutions for app modernization on the cloud, which will help you to learn how to design and implement patterns and best practices in your job. By the end of this book, you'll be able to successfully modernize applications and cloud infrastructure in hyperscaler public clouds such as IBM and hybrid clouds using Red Hat technologies as well as develop secure applications for cloud environments. What you will learnStrategize application modernization, from the planning to the implementation phaseApply cloud-native development concepts, methods, and best practicesSelect the right strategy for cloud adoption and modernizationExplore container platforms, storage, network, security, and operationsManage cloud operations using SREs, FinOps, and MLOps principlesDesign a modern data insight hub on the cloudWho this book is for This book is for cloud-native application developers involved in modernizing legacy applications by refactoring and rebuilding them. Cloud solution architects and technical leaders will also find this book useful. It will be helpful to have a basic understanding of cloud-native application development and cloud providers before getting started with this book.
Building a Red Hat OpenShift Environment on IBM Z
Author: Lydia Parziale
Publisher: IBM Redbooks
ISBN: 0738460745
Category : Computers
Languages : en
Pages : 152
Book Description
Cybersecurity is the most important arm of defense against cyberattacks. With the recent increase in cyberattacks, corporations must focus on how they are combating these new high-tech threats. When establishing best practices, a corporation must focus on employees' access to specific workspaces and information. IBM Z® focuses on allowing high processing virtual environments while maintaining a high level of security in each workspace. Organizations not only need to adjust their approach to security, but also their approach to IT environments. To meet new customer needs and expectations, organizations must take a more agile approach to their business. IBM® Z allows companies to work with hybrid and multi-cloud environments that allows more ease of use for the user and efficiency overall. Working with IBM Z, organizations can also work with many databases that are included in IBM Cloud Pak® for Data. IBM Cloud Pak for Data allows organizations to make more informed decisions with improved data usage. Along with the improved data usage, organizations can see the effects from working in a Red Hat OpenShift environment. Red Hat OpenShift is compatible across many hardware services and allows the user to run applications in the most efficient manner. The purpose of this IBM Redbooks® publication is to: Introduce IBM Z and LinuxONE platforms and how they work with the Red Hat OpenShift environment and IBMCloud Pak for Data Provide examples and the uses of IBM Z with Cloud Paks for Data that show data gravity, consistent development experience, and consolidation and business resiliency The target audience for this book is IBM Z Technical Specialists, IT Architects, and System Administrators.
Publisher: IBM Redbooks
ISBN: 0738460745
Category : Computers
Languages : en
Pages : 152
Book Description
Cybersecurity is the most important arm of defense against cyberattacks. With the recent increase in cyberattacks, corporations must focus on how they are combating these new high-tech threats. When establishing best practices, a corporation must focus on employees' access to specific workspaces and information. IBM Z® focuses on allowing high processing virtual environments while maintaining a high level of security in each workspace. Organizations not only need to adjust their approach to security, but also their approach to IT environments. To meet new customer needs and expectations, organizations must take a more agile approach to their business. IBM® Z allows companies to work with hybrid and multi-cloud environments that allows more ease of use for the user and efficiency overall. Working with IBM Z, organizations can also work with many databases that are included in IBM Cloud Pak® for Data. IBM Cloud Pak for Data allows organizations to make more informed decisions with improved data usage. Along with the improved data usage, organizations can see the effects from working in a Red Hat OpenShift environment. Red Hat OpenShift is compatible across many hardware services and allows the user to run applications in the most efficient manner. The purpose of this IBM Redbooks® publication is to: Introduce IBM Z and LinuxONE platforms and how they work with the Red Hat OpenShift environment and IBMCloud Pak for Data Provide examples and the uses of IBM Z with Cloud Paks for Data that show data gravity, consistent development experience, and consolidation and business resiliency The target audience for this book is IBM Z Technical Specialists, IT Architects, and System Administrators.
IBM Spectrum Discover: Metadata Management for Deep Insight of Unstructured Storage
Author: Joseph Dain
Publisher: IBM Redbooks
ISBN: 0738457868
Category : Computers
Languages : en
Pages : 152
Book Description
This IBM® Redpaper publication provides a comprehensive overview of the IBM Spectrum® Discover metadata management software platform. We give a detailed explanation of how the product creates, collects, and analyzes metadata. Several in-depth use cases are used that show examples of analytics, governance, and optimization. We also provide step-by-step information to install and set up the IBM Spectrum Discover trial environment. More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data such as: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.
Publisher: IBM Redbooks
ISBN: 0738457868
Category : Computers
Languages : en
Pages : 152
Book Description
This IBM® Redpaper publication provides a comprehensive overview of the IBM Spectrum® Discover metadata management software platform. We give a detailed explanation of how the product creates, collects, and analyzes metadata. Several in-depth use cases are used that show examples of analytics, governance, and optimization. We also provide step-by-step information to install and set up the IBM Spectrum Discover trial environment. More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data such as: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research.
Cataloging Unstructured Data in IBM Watson Knowledge Catalog with IBM Spectrum Discover
Author: Joseph Dain
Publisher: IBM Redbooks
ISBN: 073845902X
Category : Computers
Languages : en
Pages : 108
Book Description
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.
Publisher: IBM Redbooks
ISBN: 073845902X
Category : Computers
Languages : en
Pages : 108
Book Description
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.
Accelerating Modernization with Agile Integration
Author: Adeline SE Chun
Publisher: IBM Redbooks
ISBN: 0738458368
Category : Computers
Languages : en
Pages : 650
Book Description
The organization pursuing digital transformation must embrace new ways to use and deploy integration technologies, so they can move quickly in a manner appropriate to the goals of multicloud, decentralization, and microservices. The integration layer must transform to allow organizations to move boldly in building new customer experiences, rather than forcing models for architecture and development that pull away from maximizing the organization's productivity. Many organizations have started embracing agile application techniques, such as microservice architecture, and are now seeing the benefits of that shift. This approach complements and accelerates an enterprise's API strategy. Businesses should also seek to use this approach to modernize their existing integration and messaging infrastructure to achieve more effective ways to manage and operate their integration services in their private or public cloud. This IBM® Redbooks® publication explores the merits of what we refer to as agile integration; a container-based, decentralized, and microservice-aligned approach for integration solutions that meets the demands of agility, scalability, and resilience required by digital transformation. It also discusses how the IBM Cloud Pak for Integration marks a significant leap forward in integration technology by embracing both a cloud-native approach and container technology to achieve the goals of agile integration. The target audiences for this book are cloud integration architects, IT specialists, and application developers.
Publisher: IBM Redbooks
ISBN: 0738458368
Category : Computers
Languages : en
Pages : 650
Book Description
The organization pursuing digital transformation must embrace new ways to use and deploy integration technologies, so they can move quickly in a manner appropriate to the goals of multicloud, decentralization, and microservices. The integration layer must transform to allow organizations to move boldly in building new customer experiences, rather than forcing models for architecture and development that pull away from maximizing the organization's productivity. Many organizations have started embracing agile application techniques, such as microservice architecture, and are now seeing the benefits of that shift. This approach complements and accelerates an enterprise's API strategy. Businesses should also seek to use this approach to modernize their existing integration and messaging infrastructure to achieve more effective ways to manage and operate their integration services in their private or public cloud. This IBM® Redbooks® publication explores the merits of what we refer to as agile integration; a container-based, decentralized, and microservice-aligned approach for integration solutions that meets the demands of agility, scalability, and resilience required by digital transformation. It also discusses how the IBM Cloud Pak for Integration marks a significant leap forward in integration technology by embracing both a cloud-native approach and container technology to achieve the goals of agile integration. The target audiences for this book are cloud integration architects, IT specialists, and application developers.
Making Data Smarter with IBM Spectrum Discover: Practical AI Solutions
Author: Ivaylo B. Bozhinov
Publisher: IBM Redbooks
ISBN: 0738459135
Category : Computers
Languages : en
Pages : 170
Book Description
More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data, such as the following examples: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM® Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on-premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum® Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research. This IBM Redbooks® publication presents several use cases that are focused on artificial intelligence (AI) solutions with IBM Spectrum Discover. This book helps storage administrators and technical specialists plan and implement AI solutions by using IBM Spectrum Discover and several other IBM Storage products.
Publisher: IBM Redbooks
ISBN: 0738459135
Category : Computers
Languages : en
Pages : 170
Book Description
More than 80% of all data that is collected by organizations is not in a standard relational database. Instead, it is trapped in unstructured documents, social media posts, machine logs, and so on. Many organizations face significant challenges to manage this deluge of unstructured data, such as the following examples: Pinpointing and activating relevant data for large-scale analytics Lacking the fine-grained visibility that is needed to map data to business priorities Removing redundant, obsolete, and trivial (ROT) data Identifying and classifying sensitive data IBM® Spectrum Discover is a modern metadata management software that provides data insight for petabyte-scale file and Object Storage, storage on-premises, and in the cloud. This software enables organizations to make better business decisions and gain and maintain a competitive advantage. IBM Spectrum® Discover provides a rich metadata layer that enables storage administrators, data stewards, and data scientists to efficiently manage, classify, and gain insights from massive amounts of unstructured data. It improves storage economics, helps mitigate risk, and accelerates large-scale analytics to create competitive advantage and speed critical research. This IBM Redbooks® publication presents several use cases that are focused on artificial intelligence (AI) solutions with IBM Spectrum Discover. This book helps storage administrators and technical specialists plan and implement AI solutions by using IBM Spectrum Discover and several other IBM Storage products.