Lecture (4) on Enterprise Architecture and Data Governance PDF

Lecture (4) Learning Objectives Enterprise Information Architecture Management and Data Governance Cloud...

Lecture (4) Learning Objectives Enterprise Information Architecture Management and Data Governance Cloud Information Services Add Systems: The Agility Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Enterprise architecture (EA) – The way IT systems and processes are structured. – Helps or impedes day-to-day operations and efforts to execute business strategy. – Solves two critical challenges: where are we going; how do we get there? Data Governance - data governance is everything you do to ensure data is secure, private, accurate, available, and usable. It includes the actions people must take, the processes they must follow, and the technology that supports them throughout the data life cycle Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Strategic Focus – Solve IT systems’ complexity – Overcome Poor business alignment Business and IT Benefits of EA – Cuts IT costs; increases productivity with information, insight, and ideas – Determines competitiveness, flexibility, and IT economics – Aligns IT capabilities with business strategy to grow, innovate, and respond to market demands – Reduces risk of buying or building systems and enterprise apps Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Business Application Data Technical Architecture Architecture Architecture Architecture Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Enterprise-wide Data Governance data governance is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal standards and policies that also control data usage. Effective data governance ensures that data is consistent and trustworthy and doesn't get misused – Crosses boundaries and used by people through the enterprise. – Increased importance through new regulations and pressure to reduce costs. – Reduces legal risks associated Dependent on Governance with unmanaged or Financial Health- Food Services care inconsistently managed Industry Industry Industry information Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Master Data & Management (MDM) – Creates high-quality trustworthy data: Running the business with transactional or operational use Improving the business with analytic use – Requires strong data governance to manage availability, usability, integrity, and security. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Politics: The People Conflict – Cultures of distrust between technology and employees may exist. – Genuine commitment to change can bridge the divide with support from the senior management. – Methodologies can only provide a framework, not solve people problems Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 1. Explain the relationship between complexity and planning. Give an example. As enterprise information systems become more complex, the importance of long-range IT planning increases dramatically. Companies cannot simply add storage, new apps, or data analytics on an as needed basis and expect those additions to work with the existing systems. The relationship between complexity and planning is easier to see in physical things such as skyscrapers and transportation systems. If you are constructing a simple cabin in a remote area, you do not need a detailed plan for expansion or to make sure that the cabin fits into its environment. If you are building a simple, single-user, non-distributed system, you would not need a well-thought out growth plan either. Therefore, it is no longer feasible to manage big data, content from mobiles and social networks, and data in the cloud without the well- designed set of plans, or blueprint, provided by EA. The EA guides and controls software add-ons and upgrades, hardware, systems, networks, cloud services, and other digital technology investments. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 2. Explain enterprise architecture. Enterprise architecture (EA) is the way IT systems and processes are structured. EA is an ongoing process of creating, maintaining, and leveraging IT. It helps to solve two critical challenges: where an organization is going and how it will get there. EA helps, or impedes, day-to-day operations and efforts to execute business strategy. There are two problems that the EA is designed to address: IT systems’ complexity. IT systems have become unmanageably complex and expensive to maintain. Poor business alignment. Organizations find it difficult to keep their increasingly expensive IT systems aligned with business needs. EA is the roadmap that is used for controlling the direction of IT investments and it is a significant item in long-range planning. It is the blueprint that guides the build out of overall IT capabilities consisting of four sub- architectures (see question 3). EA defines the vision, standards, and plan that guide the priorities, operations, and management of the IT systems supporting the business. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 3. What are the four components of EA? The four components are: Business Architecture (the processes the business uses to meet its goals); Application architecture (design of IS applications and their interactions); Data architecture (organization and access of enterprise data); Technical architecture (the hardware and software infrastructure that supports applications and their interactions) Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 4. What are the business benefits of EA? EA cuts IT costs and increases productivity by giving decision makers access to information, insights, and ideas where and when they need them. EA determines an organization’s competitiveness, flexibility, and IT economics for the next decade and beyond. That is, it provides a long-term view of a company’s processes, systems, and technologies so that IT investments do not simply fulfill immediate needs. EA helps align IT capabilities with business strategy—to grow, innovate, and respond to market demands, supported by an IT practice that is 100 percent in accord with business objectives. EA can reduce the risk of buying or building systems and enterprise apps that are incompatible or unnecessarily expensive to maintain and integrate. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 5. How can EA maintain alignment between IT and business strategy? EA starts with the organization’s target–where it is going— not with where it is. Once an organization identifies the strategic direction in which it is heading and the business drivers to which it is responding, this shared vision of the future will dictate changes in business, technical, information, and solutions architectures of the enterprise, assign priorities to those changes, and keep those changes grounded in business value. EA guides and controls software add-ons and upgrades, hardware, systems, networks, cloud services, and other digital technology investments which are aligned with the business strategy. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 6. What are the two ways that data are used in an organization?. Data are used in an organization for running the business (transactional or operational use) and for improving the business (analytic use.) Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 7. What is the function of data governance? Data governance is the process of creating and agreeing to standards and requirements for the collection, identification, storage, and use of data. The success of every data-driven strategy or marketing effort depends on data governance. Data governance policies must address structured, semi- structured, and unstructured data (discussed in Section 2.3) to ensure that insights can be trusted. Data governance allows managers to determine where their data originates, who owns them, and who is responsible for what—in order to know they can trust the available data when needed. Data governance is an enterprise-wide project because data cross boundaries and are used by people throughout the enterprise. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 8. Why has interest in data governance and MDM increased? 8. As data sources and volumes continue to increase, so does the need to manage data as a strategic asset in order to extract its full value. Making business data consistent, trusted, and accessible across the enterprise is a critical first step in customer-centric business models. With appropriate data governance and MDM, managers are able to extract maximum value from their data, specifically by making better use of opportunities that are buried within behavioral data. Strong data governance is needed to manage the availability, usability, integrity, and security of the data used throughout the enterprise so that data are of sufficient quality to meet business needs. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 9. What role does personal conflict or politics play in the success of data governance? 9. There may be a culture of distrust between technology and employees in an organization. To overcome this, there must be a genuine commitment to change. Such a commitment must come from senior management. A methodology, such as data governance, cannot solve people problems. It only provides a framework in which such problems can be solved. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved.