Download or read book Machine Learning with Business Rules on IBM Z Acting on Your Insights written by Mike Johnson and published by IBM Redbooks. This book was released on 2019-12-11 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions. Note: Important changes since this document was written: This document was written for an older release of Operational Decision Manager for z/OS (ODM for z/OS). ODM for z/OS 8.9.1 required the writing of custom Java code to access a Watson Machine Learning for z/OS Scoring Service (this can be seen in ). Since that time ODM for z/OS version 8.10.1 has been released and much improves the integration experience. Integrating the two products no longer requires custom Java code. Using ODM for z/OS 8.10.1 or later you can use an automated wizard in the ODM tooling to: Browse and select a model from Watson Machine Learning Import the Machine Learning data model into your rule project Automatically generate a template rule that integrates a call to the Watson Machine Learning scoring service Download and read this document for: Individual introductions to ODM for z/OS and Machine learning Discussions on the benefits of using the two technologies together Information on integrating if you have not yet updated to ODM for z/OS 8.10.1 For information about the machine learning integration in ODM for z/OS 8.10.1 see IBM Watson Machine Learning for z/OS integration topic in the ODM for z/OS 8.10.x Knowledge Center

Download or read book Machine Learning with Business Rules on IBM Z written by Mike Johnson and published by . This book was released on 2018 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions.

Download or read book Turning Data into Insight with IBM Machine Learning for z OS written by Samantha Buhler and published by IBM Redbooks. This book was released on 2018-09-11 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The exponential growth in data over the last decade coupled with a drastic drop in cost of storage has enabled organizations to amass a large amount of data. This vast data becomes the new natural resource that these organizations must tap in to innovate and stay ahead of the competition, and they must do so in a secure environment that protects the data throughout its lifecyle 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 analytics to exist and run on the same platform. For years, some businesses chose to move their sensitive data off IBM Z to platforms that include data lakes, Hadoop, and warehouses for analytics processing. 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 analytics. At the core of data gravity is the conviction that analytics must exist and run where the data resides. An IBM client eloquently compares this change in analytics strategy to a shift from "moving the ocean to the boat to moving the boat to the ocean," where the boat is the analytics and the ocean is the data. IBM respects and invests heavily on data gravity because it recognizes the tremendous benefits that data gravity can deliver to you, including reduced cost and minimized security risks. IBM Machine Learning for z/OS® is one of the offerings that decidedly move analytics to Z where your mission-critical data resides. 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 z/OS version 1.1.0 and describes its unique value proposition. It provides step-by-step guidance for you to get started with the program, including best practices for capacity planning, installation and configuration, administration and operation. Through a retail example, the book shows how you can use the versatile and intuitive web user interface to quickly train, build, evaluate, and deploy a model. 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 z/OS.

Download or read book Turning Data Into Insight with IBM Machine Learning for Z OS written by Samantha Buhler and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimized Inferencing and Integration with AI on IBM zSystems Introduction Methodology and Use Cases written by Makenzie Manna and published by IBM Redbooks. This book was released on 2022-11-30 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).

Download or read book Machine Learning Governance for Managers written by Francesca Lazzeri and published by Springer. This book was released on 2023-12-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment, performance measurement, and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices. Particular emphasis is given to ramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance. Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized. Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.

Download or read book Systems of Insight for Digital Transformation Using IBM Operational Decision Manager Advanced and Predictive Analytics written by Whei-Jen Chen and published by IBM Redbooks. This book was released on 2015-12-03 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems of record (SORs) are engines that generates value for your business. Systems of engagement (SOE) are always evolving and generating new customer-centric experiences and new opportunities to capitalize on the value in the systems of record. The highest value is gained when systems of record and systems of engagement are brought together to deliver insight. Systems of insight (SOI) monitor and analyze what is going on with various behaviors in the systems of engagement and information being stored or transacted in the systems of record. SOIs seek new opportunities, risks, and operational behavior that needs to be reported or have action taken to optimize business outcomes. Systems of insight are at the core of the Digital Experience, which tries to derive insights from the enormous amount of data generated by automated processes and customer interactions. Systems of Insight can also provide the ability to apply analytics and rules to real-time data as it flows within, throughout, and beyond the enterprise (applications, databases, mobile, social, Internet of Things) to gain the wanted insight. Deriving this insight is a key step toward being able to make the best decisions and take the most appropriate actions. Examples of such actions are to improve the number of satisfied clients, identify clients at risk of leaving and incentivize them to stay loyal, identify patterns of risk or fraudulent behavior and take action to minimize it as early as possible, and detect patterns of behavior in operational systems and transportation that lead to failures, delays, and maintenance and take early action to minimize risks and costs. IBM® Operational Decision Manager is a decision management platform that provides capabilities that support both event-driven insight patterns, and business-rule-driven scenarios. It also can easily be used in combination with other IBM Analytics solutions, as the detailed examples will show. IBM Operational Decision Manager Advanced, along with complementary IBM software offerings that also provide capability for systems of insight, provides a way to deliver the greatest value to your customers and your business. IBM Operational Decision Manager Advanced brings together data from different sources to recognize meaningful trends and patterns. It empowers business users to define, manage, and automate repeatable operational decisions. As a result, organizations can create and shape customer-centric business moments. This IBM Redbooks® publication explains the key concepts of systems of insight and how to implement a system of insight solution with examples. It is intended for IT architects and professionals who are responsible for implementing a systems of insights solution requiring event-based context pattern detection and deterministic decision services to enhance other analytics solution components with IBM Operational Decision Manager Advanced.

Download or read book Getting Started Journey to Modernization with IBM Z written by Makenzie Manna and published by IBM Redbooks. This book was released on 2021-03-15 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modernization of enterprise IT applications and infrastructure is key to the survival of organizations. It is no longer a matter of choice. The cost of missing out on business opportunities in an intensely competitive market can be enormous. To aid in their success, organizations are facing increased encouragement to embrace change. They are pushed to think of new and innovative ways to counter, or offer, a response to threats that are posed by competitors who are equally as aggressive in adopting newer methods and technologies. The term modernization often varies in meaning based on perspective. This IBM® Redbooks® publication focuses on the technological advancements that unlock computing environments that are hosted on IBM Z® to enable secure processing at the core of hybrid. This publication is intended for IT executives, IT managers, IT architects, System Programmers, and Application Developer professionals.

Download or read book Enabling Real time Analytics on IBM z Systems Platform written by Lydia Parziale and published by IBM Redbooks. This book was released on 2016-08-08 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regarding online transaction processing (OLTP) workloads, IBM® z SystemsTM platform, with IBM DB2®, data sharing, Workload Manager (WLM), geoplex, and other high-end features, is the widely acknowledged leader. Most customers now integrate business analytics with OLTP by running, for example, scoring functions from transactional context for real-time analytics or by applying machine-learning algorithms on enterprise data that is kept on the mainframe. As a result, IBM adds investment so clients can keep the complete lifecycle for data analysis, modeling, and scoring on z Systems control in a cost-efficient way, keeping the qualities of services in availability, security, reliability that z Systems solutions offer. Because of the changed architecture and tighter integration, IBM has shown, in a customer proof-of-concept, that a particular client was able to achieve an orders-of-magnitude improvement in performance, allowing that client's data scientist to investigate the data in a more interactive process. Open technologies, such as Predictive Model Markup Language (PMML) can help customers update single components instead of being forced to replace everything at once. As a result, you have the possibility to combine your preferred tool for model generation (such as SAS Enterprise Miner or IBM SPSS® Modeler) with a different technology for model scoring (such as Zementis, a company focused on PMML scoring). IBM SPSS Modeler is a leading data mining workbench that can apply various algorithms in data preparation, cleansing, statistics, visualization, machine learning, and predictive analytics. It has over 20 years of experience and continued development, and is integrated with z Systems. With IBM DB2 Analytics Accelerator 5.1 and SPSS Modeler 17.1, the possibility exists to do the complete predictive model creation including data transformation within DB2 Analytics Accelerator. So, instead of moving the data to a distributed environment, algorithms can be pushed to the data, using cost-efficient DB2 Accelerator for the required resource-intensive operations. This IBM Redbooks® publication explains the overall z Systems architecture, how the components can be installed and customized, how the new IBM DB2 Analytics Accelerator loader can help efficient data loading for z Systems data and external data, how in-database transformation, in-database modeling, and in-transactional real-time scoring can be used, and what other related technologies are available. This book is intended for technical specialists and architects, and data scientists who want to use the technology on the z Systems platform. Most of the technologies described in this book require IBM DB2 for z/OS®. For acceleration of the data investigation, data transformation, and data modeling process, DB2 Analytics Accelerator is required. Most value can be achieved if most of the data already resides on z Systems platforms, although adding external data (like from social sources) poses no problem at all.

Download or read book Apache Spark Implementation on IBM z OS written by Lydia Parziale and published by IBM Redbooks. This book was released on 2016-08-13 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term big data refers to extremely large sets of data that are analyzed to reveal insights, such as patterns, trends, and associations. The algorithms that analyze this data to provide these insights must extract value from a wide range of data sources, including business data and live, streaming, social media data. However, the real value of these insights comes from their timeliness. Rapid delivery of insights enables anyone (not only data scientists) to make effective decisions, applying deep intelligence to every enterprise application. Apache Spark is an integrated analytics framework and runtime to accelerate and simplify algorithm development, depoyment, and realization of business insight from analytics. Apache Spark on IBM® z/OS® puts the open source engine, augmented with unique differentiated features, built specifically for data science, where big data resides. This IBM Redbooks® publication describes the installation and configuration of IBM z/OS Platform for Apache Spark for field teams and clients. Additionally, it includes examples of business analytics scenarios.

Download or read book IBM Spectrum Discover Metadata Management for Deep Insight of Unstructured Storage written by Joseph Dain and published by IBM Redbooks. This book was released on 2019-10-01 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book IBM System Storage Business Continuity Part 1 Planning Guide written by Charlotte Brooks and published by IBM Redbooks. This book was released on 2007-03-07 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: A disruption to your critical business processes could leave the entire business exposed. Today's organizations face ever-escalating customer demands and expectations. There is no room for downtime. You need to provide your customers with continuous service because your customers have a lot of choices. Your competitors are standing ready to take your place. As you work hard to grow your business, you face the challenge of keeping your business running without a glitch. To remain competitive, you need a resilient IT infrastructure. This IBM Redbooks publication introduces the importance of Business Continuity in today's IT environments. It provides a comprehensive guide to planning for IT Business Continuity and can help you design and select an IT Business Continuity solution that is right for your business environment. We discuss the concepts, procedures, and solution selection for Business Continuity in detail, including the essential set of IT Business Continuity requirements that you need to identify a solution. We also present a rigorous Business Continuity Solution Selection Methodology that includes a sample Business Continuity workshop with step-by-step instructions in defining requirements. This book is meant as a central resource book for IT Business Continuity planning and design. The companion title to this book, IBM System Storage Business Continuity: Part 2 Solutions Guide, SG24-6548, describes detailed product solutions in the System Storage Resiliency Portfolio.

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Download or read book IBM z OS Mainframe Security and Audit Management Using the IBM Security zSecure Suite written by Axel Buecker and published by IBM Redbooks. This book was released on 2011-08-18 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every organization has a core set of mission-critical data that must be protected. Security lapses and failures are not simply disruptions—they can be catastrophic events, and the consequences can be felt across the entire organization. As a result, security administrators face serious challenges in protecting the company's sensitive data. IT staff are challenged to provide detailed audit and controls documentation at a time when they are already facing increasing demands on their time, due to events such as mergers, reorganizations, and other changes. Many organizations do not have enough experienced mainframe security administrators to meet these objectives, and expanding employee skillsets with low-level mainframe security technologies can be time-consuming. The IBM® Security zSecure suite consists of multiple components designed to help you administer your mainframe security server, monitor for threats, audit usage and configurations, and enforce policy compliance. Administration, provisioning, and management components can significantly reduce administration, contributing to improved productivity, faster response time, and reduced training time needed for new administrators. This IBM Redbooks® publication is a valuable resource for security officers, administrators, and architects who wish to better understand their mainframe security solutions.

Download or read book The Advocate written by and published by . This book was released on 2001-08-14 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Advocate is a lesbian, gay, bisexual, transgender (LGBT) monthly newsmagazine. Established in 1967, it is the oldest continuing LGBT publication in the United States.

Download or read book IBM z15 8561 Technical Guide written by Octavian Lascu and published by IBM Redbooks. This book was released on 2022-07-13 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redbooks® publication describes the features and functions the latest member of the IBM Z® platform, the IBM z15TM (machine type 8561). It includes information about the IBM z15 processor design, I/O innovations, security features, and supported operating systems. The z15 is a state-of-the-art data and transaction system that delivers advanced capabilities, which are vital to any digital transformation. The z15 is designed for enhanced modularity, which is in an industry standard footprint. This system excels at the following tasks: Making use of multicloud integration services Securing data with pervasive encryption Accelerating digital transformation with agile service delivery Transforming a transactional platform into a data powerhouse Getting more out of the platform with IT Operational Analytics Accelerating digital transformation with agile service delivery Revolutionizing business processes Blending open source and Z technologies This book explains how this system uses new innovations and traditional Z strengths to satisfy growing demand for cloud, analytics, and open source technologies. With the z15 as the base, applications can run in a trusted, reliable, and secure environment that improves operations and lessens business risk.

Download or read book AI and education written by Miao, Fengchun and published by UNESCO Publishing. This book was released on 2021-04-08 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]