In this chapter, we expand on the discussion of risk in chapter two to cover how you can incorporate an understanding of and management of your security risks in a cloud environment. We talk about identifying threats, assessing and testing for vulnerabilities, and the best practices around this process. You should be able to take these ideas here and asses your own risks, as well as the risks of any potential cloud providers.

This chapter talks about how you and your provider can manage the cloud environment and how to understand the division of responsibilities between you and your provider. This includes the difference between a bare metal server and a managed environment, as well as how to secure any management interfaces. You'll know what managing a cloud environment takes so you can decide whether you want to do it yourself or leave to the provider.

This chapter covers what a provider can do with hardware at the end of its lifespan. That hardware may still have retrievable data on it, so it's important to understand what options your provider has to protect it. We cover some standard techniques, including U.S. Department of Defense policy. You should be able to ask the right questions of your provider about what they do with old hardware, as well take care to improve your own efforts.

In this final chapter, we’ll look back on key takeaways from this book, present an outlook on the future of application data management (ADM), and provide next steps for implementing ADM in your enterprise. 

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. 

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. 

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:

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.

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.

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.