Eberhard Hechler's Books

Enterprise Master Data Management

An SOA Approach to Managing Core Information

By: Allen Dreibelbis,Eberhard Hechler,Ivan Milman,Martin Oberhofer,Paul van Run,Dan Wolfson

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Enterprise Master Data Management

An SOA Approach to Managing Core Information

By: Allen Dreibelbis,Eberhard Hechler,Ivan Milman,Martin Oberhofer,Paul van Run,Dan Wolfson

The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration

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Page Count

833

Publisher

Pearson Education

Published Date

ISBN 10

0132704277

ISBN 13

9780132704274

Apache Spark for the Enterprise: Setting the Business Free

By: Oliver Draese,Eberhard Hechler,Hong Min,Catherine Moxey,Pallavi Priyadarshini,Mark Simmonds,Mythili Venkatakrishnan,George Wang,IBM Redbooks

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Apache Spark for the Enterprise: Setting the Business Free

By: Oliver Draese,Eberhard Hechler,Hong Min,Catherine Moxey,Pallavi Priyadarshini,Mark Simmonds,Mythili Venkatakrishnan,George Wang,IBM Redbooks

Analytics is increasingly an integral part of day-to-day operations at today's leading businesses, and transformation is also occurring through huge growth in mobile and digital channels. Enterprise organizations are attempting to leverage analytics in new ways and transition existing analytics capabilities to respond with more flexibility while making the most efficient use of highly valuable data science skills. The recent growth and adoption of Apache Spark as an analytics framework and platform is very timely and helps meet these challenging demands. The Apache Spark environment on IBM z/OS® and Linux on IBM z SystemsTM platforms allows this analytics framework to run on the same enterprise platform as the originating sources of data and transactions that feed it. If most of the data that will be used for Apache Spark analytics, or the most sensitive or quickly changing data is originating on z/OS, then an Apache Spark z/OS based environment will be the optimal choice for performance, security, and governance. This IBM® RedpaperTM publication explores the enterprise analytics market, use of Apache Spark on IBM z SystemsTM platforms, integration between Apache Spark and other enterprise data sources, and case studies and examples of what can be achieved with Apache Spark in enterprise environments. It is of interest to data scientists, data engineers, enterprise architects, or anybody looking to better understand how to combine an analytics framework and platform on enterprise systems.

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IBM Redbooks

Published Date

ISBN 10

0738455040

ISBN 13

9780738455044

Beyond Big Data

Using Social MDM to Drive Deep Customer Insight

By: Martin Oberhofer,Eberhard Hechler,Ivan Milman,Scott Schumacher,Dan Wolfson

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Beyond Big Data

Using Social MDM to Drive Deep Customer Insight

By: Martin Oberhofer,Eberhard Hechler,Ivan Milman,Scott Schumacher,Dan Wolfson

Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends

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Page Count

261

Publisher

IBM Press

Published Date

ISBN 10

0133509818

ISBN 13

9780133509816

The Art of Enterprise Information Architecture

A Systems-Based Approach for Unlocking Business Insight

By: Mario Godinez,Eberhard Hechler,Klaus Koenig,Steve Lockwood,Martin Oberhofer,Michael Schroeck

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The Art of Enterprise Information Architecture

A Systems-Based Approach for Unlocking Business Insight

By: Mario Godinez,Eberhard Hechler,Klaus Koenig,Steve Lockwood,Martin Oberhofer,Michael Schroeck

Architecture for the Intelligent Enterprise: Powerful New Ways to Maximize the Real-time Value of Information Tomorrow’s winning “Intelligent Enterprises” will bring together far more diverse sources of data, analyze it in more powerful ways, and deliver immediate insight to decision-makers throughout the organization. Today, however, most companies fail to apply the information they already have, while struggling with the complexity and costs of their existing information environments. In this book, a team of IBM’s leading information management experts guide you on a journey that will take you from where you are today toward becoming an “Intelligent Enterprise.” Drawing on their extensive experience working with enterprise clients, the authors present a new, information-centric approach to architecture and powerful new models that will benefit any organization. Using these strategies and models, companies can systematically unlock the business value of information by delivering actionable, real-time information in context to enable better decision-making throughout the enterprise–from the “shop floor” to the “top floor.” Coverage Includes Highlighting the importance of Dynamic Warehousing Defining your Enterprise Information Architecture from conceptual, logical, component, and operational views Using information architecture principles to integrate and rationalize your IT investments, from Cloud Computing to Information Service Lifecycle Management Applying enterprise Master Data Management (MDM) to bolster business functions, ranging from compliance and risk management to marketing and product management Implementing more effective business intelligence and business performance optimization, governance, and security systems and processes Understanding “Information as a Service” and “Info 2.0,” the information delivery side of Web 2.0

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675

Publisher

Pearson Education

Published Date

ISBN 10

0137054629

ISBN 13

9780137054626

Accelerating Data Transformation with IBM DB2 Analytics Accelerator for z/OS

By: Ute Baumbach,Patric Becker,Uwe Denneler,Eberhard Hechler,Wolfgang Hengstler,Steffen Knoll,Frank Neumann,Guenter Georg Schoellmann,Khadija Souissi,Timm Zimmermann,IBM Redbooks

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Accelerating Data Transformation with IBM DB2 Analytics Accelerator for z/OS

By: Ute Baumbach,Patric Becker,Uwe Denneler,Eberhard Hechler,Wolfgang Hengstler,Steffen Knoll,Frank Neumann,Guenter Georg Schoellmann,Khadija Souissi,Timm Zimmermann,IBM Redbooks

Transforming data from operational data models to purpose-oriented data structures has been commonplace for the last decades. Data transformations are heavily used in all types of industries to provide information to various users at different levels. Depending on individual needs, the transformed data is stored in various different systems. Sending operational data to other systems for further processing is then required, and introduces much complexity to an existing information technology (IT) infrastructure. Although maintenance of additional hardware and software is one component, potential inconsistencies and individually managed refresh cycles are others. For decades, there was no simple and efficient way to perform data transformations on the source system of operational data. With IBM® DB2® Analytics Accelerator, DB2 for z/OS is now in a unique position to complete these transformations in an efficient and well-performing way. DB2 for z/OS completes these while connecting to the same platform as for operational transactions, helping you to minimize your efforts to manage existing IT infrastructure. Real-time analytics on incoming operational transactions is another demand. Creating a comprehensive scoring model to detect specific patterns inside your data can easily require multiple iterations and multiple hours to complete. By enabling a first set of analytical functionality in DB2 Analytics Accelerator, those dedicated mining algorithms can now be run on an accelerator to efficiently perform these modeling tasks. Given the speed of query processing on an accelerator, these modeling tasks can now be performed much quicker compared to traditional relational database management systems. This speed enables you to keep your scoring algorithms more up-to-date, and ultimately adapt more quickly to constantly changing customer behaviors. This IBM Redbooks® publication describes the new table type that is introduced with DB2 Analytics Accelerator V4.1 PTF5 that enables more efficient data transformations. These tables are called accelerator-only tables, and can exist on an accelerator only. The tables benefit from the accelerator performance characteristics, while maintaining access through existing DB2 for z/OS application programming interfaces (APIs). Additionally, we describe the newly introduced analytical capabilities with DB2 Analytics Accelerator V5.1, putting you in the position to efficiently perform data modeling for online analytical requirements in your DB2 for z/OS environment. This book is intended for technical decision-makers who want to get a broad understanding about the analytical capabilities and accelerator-only tables of DB2 Analytics Accelerator. In addition, you learn about how these capabilities can be used to accelerate in-database transformations and in-database analytics in various environments and scenarios, including the following scenarios: Multi-step processing and reporting in IBM DB2 Query Management FacilityTM, IBM Campaign, or Microstrategy environments In-database transformations using IBM InfoSphere® DataStage® Ad hoc data analysis for data scientists In-database analytics using IBM SPSS® Modeler

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Page Count

216

Publisher

IBM Redbooks

Published Date

ISBN 10

0738441198

ISBN 13

9780738441191

Enterprise Master Data Management

An SOA Approach to Managing Core Information

By: Allen Dreibelbis,Eberhard Hechler,Ivan Milman,Martin Oberhofer,Paul van Run,Dan Wolfson

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Enterprise Master Data Management

An SOA Approach to Managing Core Information

By: Allen Dreibelbis,Eberhard Hechler,Ivan Milman,Martin Oberhofer,Paul van Run,Dan Wolfson

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Solve jigsaw puzzle

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Page Count

833

Publisher

Pearson Education

Published Date

ISBN 10

0132704277

ISBN 13

9780132704274

The Art of Enterprise Information Architecture

A Systems-Based Approach for Unlocking Business Insight

By: Mario Godinez,Eberhard Hechler,Klaus Koenig,Steve Lockwood,Martin Oberhofer,Michael Schroeck

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The Art of Enterprise Information Architecture

A Systems-Based Approach for Unlocking Business Insight

By: Mario Godinez,Eberhard Hechler,Klaus Koenig,Steve Lockwood,Martin Oberhofer,Michael Schroeck

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Solve jigsaw puzzle

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Page Count

675

Publisher

Pearson Education

Published Date

ISBN 10

0137054629

ISBN 13

9780137054626

Beyond Big Data

Using Social MDM to Drive Deep Customer Insight

By: Martin Oberhofer,Eberhard Hechler,Ivan Milman,Scott Schumacher,Dan Wolfson

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Beyond Big Data

Using Social MDM to Drive Deep Customer Insight

By: Martin Oberhofer,Eberhard Hechler,Ivan Milman,Scott Schumacher,Dan Wolfson

Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult--often, because it's so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM's leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM's enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends

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Page Count

261

Publisher

Pearson Education

Published Date

ISBN 10

013350980X

ISBN 13

9780133509809

Deploying AI in the Enterprise

IT Approaches for Design, DevOps, Governance, Change Management, Blockchain, and Quantum Computing

By: Eberhard Hechler,Martin Oberhofer,Thomas Schaeck

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Deploying AI in the Enterprise

IT Approaches for Design, DevOps, Governance, Change Management, Blockchain, and Quantum Computing

By: Eberhard Hechler,Martin Oberhofer,Thomas Schaeck

Your company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise. You will learn about AI’s capabilities, potential, limitations, and challenges. This book teaches you about the role of AI in the context of well-established areas, such as design thinking and DevOps, governance and change management, blockchain, and quantum computing, and discusses the convergence of AI in these key areas of the enterprise. Deploying AI in the Enterprise provides guidance and methods to effectively deploy and operationalize sustainable AI solutions. You will learn about deployment challenges, such as AI operationalization issues and roadblocks when it comes to turning insight into actionable predictions. You also will learn how to recognize the key components of AI information architecture, and its role in enabling successful and sustainable AI deployments. And you will come away with an understanding of how to effectively leverage AI to augment usage of core information in Master Data Management (MDM) solutions. What You Will Learn Understand the most important AI concepts, including machine learning and deep learning Follow best practices and methods to successfully deploy and operationalize AI solutions Identify critical components of AI information architecture and the importance of having a plan Integrate AI into existing initiatives within an organization Recognize current limitations of AI, and how this could impact your business Build awareness about important and timely AI research Adjust your mindset to consider AI from a holistic standpoint Get acquainted with AI opportunities that exist in various industries Who This Book Is For IT pros, data scientists, and architects who need to address deployment and operational challenges related to AI and need a comprehensive overview on how AI impacts other business critical areas. It is not an introduction, but is for the reader who is looking for examples on how to leverage data to derive actionable insight and predictions, and needs to understand and factor in the current risks and limitations of AI and what it means in an industry-relevant context.

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Solve jigsaw puzzle

Age

Page Count

331

Publisher

Apress

Published Date

ISBN 10

1484262050

ISBN 13

9781484262054

Book's by Eberhard Hechler

Enterprise Master Data Management

Enterprise Master Data Management

Apache Spark for the Enterprise: Setting the Business Free

Apache Spark for the Enterprise: Setting the Business Free

Beyond Big Data

Beyond Big Data

The Art of Enterprise Information Architecture

The Art of Enterprise Information Architecture

Accelerating Data Transformation with IBM DB2 Analytics Accelerator for z/OS

Accelerating Data Transformation with IBM DB2 Analytics Accelerator for z/OS

Enterprise Master Data Management

Enterprise Master Data Management

The Art of Enterprise Information Architecture

The Art of Enterprise Information Architecture

Beyond Big Data

Beyond Big Data

Deploying AI in the Enterprise

Deploying AI in the Enterprise

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