Articles by Vikram Chalana

Chapter 8: Getting Started with ADM

Throughout this book, we have explored the benefits and key value proposition of application data management (ADM). ADM is a business-led, decentralized initiative that helps improve data quality by implementing data governance on top of key enterprise applications. Improving both data quality and the processes that feed data into these enterprise applications enables your business to enhance trust in your data. This is a critical step for companies seeking to participate in the digital economy and leverage advanced analytics. 

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Chapter 7: ADM in the IT Stack

For the enterprise architect, the first steps in understanding application data management (ADM) in the enterprise stack are to distinguish master data from application data and then select the appropriate tool—master data management (MDM) vs. ADM—to administer each type of data. Master data are typically managed inside a central MDM application. Application data, in contrast, are data that are used by and stored in a single key application. In contrast to master data, they are managed locally for that application. 

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Chapter 6: ADM Adoption in the Enterprise

Today successful organizations are starting to value data as a strategic asset, and companies are ultimately working towards the same strategic goal—make the data they have as useful as possible to the organization and to the entities that interact with them. Organizations need to take the following actions to meet this goal:

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Chapter 5: Application Data Management Capabilities

Application data management (ADM) is a framework that can be vital to your company's data governance strategy. It involves managing data in key enterprise applications, such as your ERP systems, to ensure that data is timely and of high quality. The processes and tools that are elements of ADM provide key capabilities for both reactive and proactive governance, helping ensure smooth business operations and high confidence in your data.

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Chapter 4: Data Governance and Stewardship in ERP

Data governance and data stewardship are terms that are often thrown around within organizations today, but rarely with a common definition that triggers action. Essentially, data governance is the cycle of defining attributes that are necessary to maintain order, efficiency, and control of data in information systems. Data stewardship is the process of leveraging these attributes to maintain order, efficiency, and control.

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Chapter 3: Data as a Strategic Asset in Your Digital Journey

Every business, large or small, across industries from manufacturing and retail to education is being disrupted by fundamental shifts in digital and data resources. Companies that successfully adapt to these transformations and implement policies to treat data as a strategic asset will emerge as the leaders of tomorrow. 

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Chapter 2: ERP System – The Key Enterprise Application

Organizations create and deliver value in the form of a product or service, which they offer to consumers or to other organizations. For example, manufacturing organizations create tangible products such as cars,
batteries, and electronic devices, while other organizations create
intangible ‘‘products’’ or services such as insurance, healthcare, and
consulting. Regardless of the type of organization, however, the product or service is created via a business process—a sequence of interconnected tasks or activities that take a set of inputs and convert them into the desired output. 

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Popular Chapters

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  • Chapter 7: Phase Four: Transition

    In the final phase, transition, we go through what you can expect at go-live, followed by lengthy discussions regarding service level agreements, operations process training, and transition to cloud operations. We talk about intricacies of system stabilization and monitoring. Finally, we explore the options for business continuity and security

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  • Chapter 6: Phase Three: Build

    In the third phase, build, we walk through developing proofs of concept for your project. The chapter discusses how to take advantage of a provision-shared infrastructure, as well as strategies for building and testing that infrastructure. There is an examination on how to build and mitigate databases and applications, as well as planning the phase cutover. It also looks at automated provisioning and automated services.

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  • Chapter 5: Phase Two: Model

    The second phase of moving SAP to the cloud, model, contains an overview of the second half of onboarding to the cloud. It examples infrastructure requirements and design and walks the reader through the process of developing a workload analysis. The chapter discusses application and business process discovery as well as operational run books and migration strategy.

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From The Blog

  • Encryption

    The previous chapters [of SAP in the Cloud: Security Essentials] discussed how cloud providers can prevent an attacker from accessing your data. But what happens if an attacker does gain access? Does this mean it’s game over, data’s stolen, start running damage control? Not necessarily. This is where encryption can help you. In this chapter excerpt, we’ll cover what encryption is and how you can use it to protect your cloud-based SAP system.

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