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Managing Data In Motion

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Managing Data in Motion

Managing Data in Motion Book
Author : April Reeve
Publisher : Newnes
Release : 2013-02-26
ISBN : 0123977916
Language : En, Es, Fr & De

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Book Description :

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

Managing Data in Motion

Managing Data in Motion Book
Author : April Reeve
Publisher : Morgan Kaufmann Pub
Release : 2013
ISBN : 9780123971678
Language : En, Es, Fr & De

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Book Description :

Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

IBM InfoSphere Streams Harnessing Data in Motion

IBM InfoSphere Streams Harnessing Data in Motion Book
Author : Chuck Ballard,Daniel M Farrell,Mark Lee,Paul D Stone,Scott Thibault,Sandra Tucker,IBM Redbooks
Publisher : IBM Redbooks
Release : 2010-09-14
ISBN : 0738434736
Language : En, Es, Fr & De

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Book Description :

In this IBM® Redbooks® publication, we discuss and describe the positioning, functions, capabilities, and advanced programming techniques for IBM InfoSphereTM Streams (V1). See: http://www.redbooks.ibm.com/abstracts/sg247970.html for the newer InfoSphere Streams (V2) release. Stream computing is a new paradigm. In traditional processing, queries are typically run against relatively static sources of data to provide a query result set for analysis. With stream computing, a process that can be thought of as a continuous query, that is, the results are continuously updated as the data sources are refreshed. So, traditional queries seek and access static data, but with stream computing, a continuous stream of data flows to the application and is continuously evaluated by static queries. However, with IBM InfoSphere Streams, those queries can be modified over time as requirements change. IBM InfoSphere Streams takes a fundamentally different approach to continuous processing and differentiates itself with its distributed runtime platform, programming model, and tools for developing continuous processing applications. The data streams consumable by IBM InfoSphere Streams can originate from sensors, cameras, news feeds, stock tickers, and a variety of other sources, including traditional databases. It provides an execution platform and services for applications that ingest, filter, analyze, and correlate potentially massive volumes of continuous data streams.

Data Management courseware based on CDMP Fundamentals

Data Management courseware based on CDMP Fundamentals Book
Author : Strategy Alliance BV ,And More Group BV
Publisher : Van Haren
Release : 2023-02-01
ISBN : 940180799X
Language : En, Es, Fr & De

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Book Description :

Besides the courseware publication (ISBN: 9789401807999), you are advised to obtain the DAMA DMBOK publication (ISBN: 9781634622349). Optionally, you can use the publication Data management: a gentle introduction (ISBN: 9789401805506) as inspiration for examples and quotes about the field of data management. This material is intended to prepare participants for the CDMP exam by DAMA International. The courseware can only be ordered by partners and is based on the current version of the DAMA DMBOK. The material will be updated when new versions of DMBOK are published. DAMA DMBOK is the industry reference for data management. It is published by DAMA International and is currently in its second version. The DMBOK is developed by professionals and can be seen as a collection of best practices. The domain of data management is divided into functional areas which are discussed in terms of definitions (what is it), goals (what are we trying to achieve), steps (what are typical activities), inputs/outputs, and participating roles. Developing and sustaining an effective data management function is far from an easy task. The DMBOK framework is adopted by many organizations as the foundation for their data management function: standardized language and good practices speed up the learning process. After the training, you have an overview of the field of data management, its terminology, and current best practices.

Meeting the Challenges of Data Quality Management

Meeting the Challenges of Data Quality Management Book
Author : Laura Sebastian-Coleman
Publisher : Academic Press
Release : 2022-01-25
ISBN : 0128217561
Language : En, Es, Fr & De

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Book Description :

Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges. The book enables data management professionals to help their organizations get more value from data by addressing the five challenges of data quality management: the meaning challenge (recognizing how data represents reality), the process/quality challenge (creating high-quality data by design), the people challenge (building data literacy), the technical challenge (enabling organizational data to be accessed and used, as well as protected), and the accountability challenge (ensuring organizational leadership treats data as an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly. The book describes core data quality management capabilities and introduces new and experienced DQ practitioners to practical techniques for getting value from activities such as data profiling, DQ monitoring and DQ reporting. It extends these ideas to the management of data quality within big data environments. This book will appeal to data quality and data management professionals, especially those involved with data governance, across a wide range of industries, as well as academic and government organizations. Readership extends to people higher up the organizational ladder (chief data officers, data strategists, analytics leaders) and in different parts of the organization (finance professionals, operations managers, IT leaders) who want to leverage their data and their organizational capabilities (people, processes, technology) to drive value and gain competitive advantage. This will be a key reference for graduate students in computer science programs which normally have a limited focus on the data itself and where data quality management is an often-overlooked aspect of data management courses. Describes the importance of high-quality data to organizations wanting to leverage their data and, more generally, to people living in today’s digitally interconnected world Explores the five challenges in relation to organizational data, including "Big Data," and proposes approaches to meeting them Clarifies how to apply the core capabilities required for an effective data quality management program (data standards definition, data quality assessment, monitoring and reporting, issue management, and improvement) as both stand-alone processes and as integral components of projects and operations Provides Data Quality practitioners with ways to communicate consistently with stakeholders

Intelligent Innovations in Multimedia Data Engineering and Management

Intelligent Innovations in Multimedia Data Engineering and Management Book
Author : Bhattacharyya, Siddhartha
Publisher : IGI Global
Release : 2018-09-07
ISBN : 1522571086
Language : En, Es, Fr & De

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Book Description :

With the ever-increasing volume of data, proper management of data is a challenging proposition to scientists and researchers, and given the vast storage space required, multimedia data is no exception in this regard. Scientists and researchers are investing great effort to discover new space-efficient methods for storage and archiving of this data. Intelligent Innovations in Multimedia Data Engineering and Management provides emerging research exploring the theoretical and practical aspects of storage systems and computing methods for large forms of data. Featuring coverage on a broad range of topics such as binary image, fuzzy logic, and metaheuristic algorithms, this book is ideally designed for computer engineers, IT professionals, technology developers, academicians, and researchers seeking current research on advancing strategies and computing techniques for various types of data.

Executing Data Quality Projects

Executing Data Quality Projects Book
Author : Danette McGilvray
Publisher : Academic Press
Release : 2021-05-27
ISBN : 0128180161
Language : En, Es, Fr & De

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Book Description :

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today’s data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization’s standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach Contains real examples from around the world, gleaned from the author’s consulting practice and from those who implemented based on her training courses and the earlier edition of the book Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online

Kubernetes Secrets Management

Kubernetes Secrets Management Book
Author : Alex Soto Bueno,Andrew Block
Publisher : Simon and Schuster
Release : 2023-01-17
ISBN : 1617298913
Language : En, Es, Fr & De

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Book Description :

Safely manage your secret information like passwords, keys, and certificates in Kubernetes. This practical guide is full of best practices and methods for adding layers of security that will defend the critical data of your applications. In Kubernetes Secrets Management you will find: Strategies for storing secure assets in Kubernetes Cryptographic options and how to apply them in Kubernetes Using the HashiCorp Vault server on Kubernetes for secure secrets storage Managing security with public cloud providers Applying security concepts using tools from the Kubernetes ecosystem End-to-end secrets storage from development to operations Implementing in Kubernetes in CI/CD systems Secrets, like database passwords and API keys, are some of the most important data in your application. Kubernetes Secrets Management reveals how to store these sensitive assets in Kubernetes in a way that’s protected against leaks and hacks. You’ll learn the default capabilities of Kubernetes secrets, where they’re lacking, and alternative options to strengthen applications and infrastructure. Discover a security-first mindset that is vital for storing and using secrets correctly, and tools and concepts that will help you manage sensitive assets such as certificates, keys, and key rotation. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Kubernetes relies on passwords, tokens, keys, certificates, and other sensitive information to keep your system secure. But how do you keep these “secrets” safe? In this concise, practical book you’ll learn secrets management techniques that go far beyond the Kubernetes defaults. About the book Kubernetes Secrets Management reveals security best practices and reliable third-party tools for protecting sensitive data in Kubernetes-based systems. In this focused guide, you’ll explore relevant, real-world examples like protecting secrets in a code repository, securing keys with HashiCorp Vault, and adding layers to maintain protection after a breach. Along the way, you’ll pick up secrets management techniques you can use outside Kubernetes, as well. What's inside Cryptographic options you can apply in Kubernetes Managing security with public cloud providers Secrets storage, from development to production End-to-end Kubernetes secrets management in CI/CD systems About the reader For readers experienced with Kubernetes and CI/CD practices. About the author Alex Soto is a director of developer experience at Red Hat, a Java Champion since 2007, an international speaker, and a teacher at Salle URL University. Andrew Block is a distinguished architect with Red Hat, and an active member of the open-source community. Table of Contents PART 1 SECRETS AND KUBERNETES 1 Kubernetes Secrets 2 An introduction to Kubernetes and Secrets PART 2 MANAGING SECRETS 3 Securely storing Secrets 4 Encrypting data at rest 5 HashiCorp Vault and Kubernetes 6 Accessing cloud secrets stores PART 3 CONTINUOUS INTEGRATION AND CONTINUOUS DELIVERY 7 Kubernetes-native continuous integration and Secrets 8 Kubernetes-native continuous delivery and Secrets

XML in Data Management

XML in Data Management Book
Author : Peter Aiken,M. David Allen
Publisher : Elsevier
Release : 2004-07-01
ISBN : 0080521444
Language : En, Es, Fr & De

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Book Description :

XML in Data Management is for IT managers and technical staff involved in the creation, administration, or maintenance of a data management infrastructure that includes XML. For most IT staff, XML is either just a buzzword that is ignored or a silver bullet to be used in every nook and cranny of their organization. The truth is in between the two. This book provides the guidance necessary for data managers to make measured decisions about XML within their organizations. Readers will understand the uses of XML, its component architecture, its strategic implications, and how these apply to data management. Takes a data-centric view of XML Explains how, when, and why to apply XML to data management systems Covers XML component architecture, data engineering, frameworks, metadata, legacy systems, and more Discusses the various strengths and weaknesses of XML technologies in the context of organizational data management and integration

Big Data

Big Data Book
Author : Kiran Sood,Rajesh Kumar Dhanaraj,Balamurugan Balusamy,Simon Grima,R. Uma Maheshwari
Publisher : Emerald Group Publishing
Release : 2022-07-19
ISBN : 1802626077
Language : En, Es, Fr & De

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Book Description :

Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional.

Data Quality

Data Quality Book
Author : Rupa Mahanti
Publisher : Quality Press
Release : 2019-03-18
ISBN : 1951058682
Language : En, Es, Fr & De

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Book Description :

Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality Butterfly effect of data quality A detailed description of data quality dimensions and their measurement Data quality strategy approach Six Sigma - DMAIC approach to data quality Data quality management techniques Data quality in relation to data initiatives like data migration, MDM, data governance, etc. Data quality myths, challenges, and critical success factors Students, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout. About the Author Rupa Mahanti, Ph.D. is a Business and Information Management consultant and has worked in different solution environments and industry sectors in the United States, United Kingdom, India, and Australia. She helps clients with activities such as business process mapping, information management, data quality, and strategy. Having a work experience (academic, industry, and research) of more than a decade and half, Rupa has guided a doctoral dissertation and published a large number of research articles. She is an associate editor with the journal Software Quality Professional and a reviewer for several international journals. "This is not the kind of book that you'll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective." from the foreword by Thomas C. Redman, Ph.D., the Data Doc Dr. Mahanti provides a very detailed and thorough coverage of all aspects of data quality management that would suit all ranges of expertise from a beginner to an advanced practitioner. With plenty of examples, diagrams, etc. the book is easy to follow and will deepen your knowledge in the data domain. I will certainly keep this handy as my go-to reference. I can't imagine the level of effort and passion that Dr. Mahanti has put into this book that captures so much knowledge and experience for the benefit of the reader. I would highly recommend this book for its comprehensiveness, depth, and detail. A must-have for a data practitioner at any level. Clint D'Souza, CEO and Director, CDZM Consulting

Growing Business Intelligence

Growing Business Intelligence Book
Author : Larry Burns
Publisher : Technics Publications
Release : 2016-09-23
ISBN : 1634621492
Language : En, Es, Fr & De

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Book Description :

How do we enable our organizations to enjoy the often significant benefits of BI and analytics, while at the same time minimizing the cost and risk of failure? In this book, I am not going to try to be prescriptive; I won’t tell you exactly how to build your BI environment. Instead, I am going to focus on a few core principles that will enable you to navigate the rocky shoals of BI architecture and arrive at a destination best suited for your particular organization. Some of these core principles include: · Have an overarching strategy, plan, and roadmap · Recognize and leverage your existing technology investments · Support both data discovery and data reuse · Keep data in motion, not at rest · Separate information delivery from data storage · Emphasize data transparency over data quality · Take an agile approach to BI development. This book will show you how to successfully navigate both the jungle of BI technology and the minefield of human nature. It will show you how to create a BI architecture and strategy that addresses the needs of all organizational stakeholders. It will show you how to maximize the value of your BI investments. It will show you how to manage the risk of disruptive technology. And it will show you how to use agile methodologies to deliver on the promise of BI and analytics quickly, succinctly, and iteratively. This book is about many things. But principally, it’s about success. The goal of any enterprise initiative is to succeed and to derive benefit—benefit that all stakeholders can share in. I want you to be successful. I want your organization to be successful. This book will show you how. This book is for anyone who is currently or will someday be working on a BI, analytics, or Big Data project, and for organizations that want to get the maximum amount of value from both their data and their BI technology investment. This includes all stakeholders in the BI effort—not just the data people or the IT people, but also the business stakeholders who have the responsibility for the definition and use of data. There are six sections to this book: In Section I, What Kind of Garden Do You Want?, we will examine the benefits and risks of Business Intelligence, making the central point that BI is a business (not IT) process designed to manage data assets in pursuit of enterprise goals. We will show how data, when properly managed and used, can be a key enabler of several types of core business processes. The purpose of this section is to help you define the particular benefit(s) you want from BI. In Section II, Building the Bones, we will talk about how to design and build out the “hardscape” (infrastructure) of your BI environment. This stage of the process involves leveraging existing technology investments and iteratively moving toward your desired target state BI architecture. In Section III, From the Ground Up, we explore the more detailed aspects of implementing your BI operational environment. In Section IV, Weeds, Pests and Critters, we talk about the myriad of things that can go wrong on a BI project, and discuss ways of mitigating these risks. In Section V, The Sustainable Garden, we talk about how to create a BI infrastructure that is easy and inexpensive to maintain. Finally, Section VI presents a case study illustrating the principles of this book, as applied to a fictional manufacturing company (the Blue Moon Guitar Company).

A Primer in Financial Data Management

A Primer in Financial Data Management Book
Author : Martijn Groot
Publisher : Academic Press
Release : 2017-05-10
ISBN : 0128099003
Language : En, Es, Fr & De

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Book Description :

A Primer in Financial Data Management describes concepts and methods, considering financial data management, not as a technological challenge, but as a key asset that underpins effective business management. This broad survey of data management in financial services discusses the data and process needs from the business user, client and regulatory perspectives. Its non-technical descriptions and insights can be used by readers with diverse interests across the financial services industry. The need has never been greater for skills, systems, and methodologies to manage information in financial markets. The volume of data, the diversity of sources, and the power of the tools to process it massively increased. Demands from business, customers, and regulators on transparency, safety, and above all, timely availability of high quality information for decision-making and reporting have grown in tandem, making this book a must read for those working in, or interested in, financial management. Focuses on ways information management can fuel financial institutions’ processes, including regulatory reporting, trade lifecycle management, and customer interaction Covers recent regulatory and technological developments and their implications for optimal financial information management Views data management from a supply chain perspective and discusses challenges and opportunities, including big data technologies and regulatory scrutiny

Information Security Management Handbook Volume 4

Information Security Management Handbook  Volume 4 Book
Author : Harold F. Tipton,Micki Krause Nozaki
Publisher : CRC Press
Release : 2010-06-22
ISBN : 1439819033
Language : En, Es, Fr & De

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Book Description :

Every year, in response to advancements in technology and new laws in different countries and regions, there are many changes and updates to the body of knowledge required of IT security professionals. Updated annually to keep up with the increasingly fast pace of change in the field, the Information Security Management Handbook is the single most

Kafka The Definitive Guide

Kafka  The Definitive Guide Book
Author : Gwen Shapira,Todd Palino,Rajini Sivaram,Krit Petty
Publisher : "O'Reilly Media, Inc."
Release : 2021-11-05
ISBN : 1492043036
Language : En, Es, Fr & De

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Book Description :

Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes. Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. You'll examine: Best practices for deploying and configuring Kafka Kafka producers and consumers for writing and reading messages Patterns and use-case requirements to ensure reliable data delivery Best practices for building data pipelines and applications with Kafka How to perform monitoring, tuning, and maintenance tasks with Kafka in production The most critical metrics among Kafka's operational measurements Kafka's delivery capabilities for stream processing systems

Mastering Identity and Access Management with Microsoft Azure

Mastering Identity and Access Management with Microsoft Azure Book
Author : Jochen Nickel
Publisher : Packt Publishing Ltd
Release : 2019-02-26
ISBN : 1789131154
Language : En, Es, Fr & De

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Book Description :

Start empowering users and protecting corporate data, while managing identities and access with Microsoft Azure in different environments Key FeaturesUnderstand how to identify and manage business drivers during transitionsExplore Microsoft Identity and Access Management as a Service (IDaaS) solutionOver 40 playbooks to support your learning process with practical guidelinesBook Description Microsoft Azure and its Identity and access management are at the heart of Microsoft's software as service products, including Office 365, Dynamics CRM, and Enterprise Mobility Management. It is crucial to master Microsoft Azure in order to be able to work with the Microsoft Cloud effectively. You’ll begin by identifying the benefits of Microsoft Azure in the field of identity and access management. Working through the functionality of identity and access management as a service, you will get a full overview of the Microsoft strategy. Understanding identity synchronization will help you to provide a well-managed identity. Project scenarios and examples will enable you to understand, troubleshoot, and develop on essential authentication protocols and publishing scenarios. Finally, you will acquire a thorough understanding of Microsoft Information protection technologies. What you will learnApply technical descriptions to your business needs and deploymentsManage cloud-only, simple, and complex hybrid environmentsApply correct and efficient monitoring and identity protection strategiesDesign and deploy custom Identity and access management solutionsBuild a complete identity and access management life cycleUnderstand authentication and application publishing mechanismsUse and understand the most crucial identity synchronization scenariosImplement a suitable information protection strategyWho this book is for This book is a perfect companion for developers, cyber security specialists, system and security engineers, IT consultants/architects, and system administrators who are looking for perfectly up–to-date hybrid and cloud-only scenarios. You should have some understanding of security solutions, Active Directory, access privileges/rights, and authentication methods. Programming knowledge is not required but can be helpful for using PowerShell or working with APIs to customize your solutions.

Data Management at Scale

Data Management at Scale Book
Author : Piethein Strengholt
Publisher : O'Reilly Media
Release : 2020-07-29
ISBN : 1492054755
Language : En, Es, Fr & De

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Book Description :

As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Healthcare Data Analytics and Management

Healthcare Data Analytics and Management Book
Author : Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
Publisher : Academic Press
Release : 2018-11-15
ISBN : 0128156368
Language : En, Es, Fr & De

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Book Description :

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

Technologies and Applications for Big Data Value

Technologies and Applications for Big Data Value Book
Author : Edward Curry,Sören Auer,Arne J. Berre,Andreas Metzger,María S. Pérez,Sonja Zillner
Publisher : Springer Nature
Release : 2022
ISBN : 3030783073
Language : En, Es, Fr & De

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Book Description :

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.

The Apache Ignite Book

The Apache Ignite Book Book
Author : Michael Zheludkov,Shamim Bhuiyan
Publisher : Lulu.com
Release : 2019-02-25
ISBN : 0359439373
Language : En, Es, Fr & De

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Book Description :

Apache Ignite is one of the most widely used open source memory-centric distributed, caching, and processing platform. This allows the users to use the platform as an in-memory computing framework or a full functional persistence data stores with SQL and ACID transaction support. On the other hand, Apache Ignite can be used for accelerating existing Relational and NoSQL databases, processing events & streaming data or developing Microservices in fault-tolerant fashion. This book addressed anyone interested in learning in-memory computing and distributed database. This book intends to provide someone with little to no experience of Apache Ignite with an opportunity to learn how to use this platform effectively from scratch taking a practical hands-on approach to learning. Please see the table of contents for more details.