Enterprise Data Management Architecture And Implementation Plan

There are several dimensions by which data can be valued, including financial or business, regulatory, legal and privacy. A useful exercise to help determine the value of data, and to which risks it is vulnerable, is to create a data flow diagram. The diagram shows how data flows through your organization and beyond so you can see how it is created, amended, stored, accessed and used. Don't, however, just classify data based on the application that creates it, such as CRM or Accounts. This type of distinction may avoid many of the complexities of data classification, but it is too blunt an approach to achieve suitable levels of security and access.

Data Innovations Office facilitates cross-sector analytical insight generation to drive competitive value and optimize the use of its resources and financial assets. Under the Chief Data Officer’s leadership this office provides analytical services to many other business units. An agency relationship exists between Data Innovations Office and all other business units who use its services. At the same time, this office employs services of third party business analytics service providers. At times, the third party companies may need a database to create solutions which pose a great value. They might not be able to generate these databases on their own due to sheer volume of data and lack of very expensive data processing environments. Although these companies are hired to provide services solely for the interest of the principal – in our case Citigroup- they might see a potential to profit from selling their findings to other corporations. The principal limits such behavior by establishing appropriate incentives for the agent through the Master Service Agreements and by incurring monitoring costs. A non-disclosure agreement is also signed by the agent to legally prevent them from releasing any of their findings.

Data are “raw facts that describe the characteristics of an event or object” (Baltzan 6). Managers used to have to collect data manually along with analyzing it. This was a very time consuming process which could also be complicated in different aspects. If businesses lack data this can cause them to make unethical business decisions. For example, if they don’t have the correct data needed they may order in too many products or not enough causing a surplus or shortage in products/supplies. Being able to collect and analyze data quickly everyday helps make a business make better decision. Data in this day and age is important for a business to obtain so they can make the best possible decisions for their company to be successful. This can help a business know how much to order, how much was sold, and their customer numbers. A company can also see where they are getting most of their customers from when collecting data from surveys. Data allows us to see if a company is doing good or bad and

The authors consist of Robert Miller, Kristine Parsons and David Lifer. Robert Miller is in charge of Business Information systems at Central Michigan University. While Kristine Parsons and David Lifer are apart of the Accounting/ MIS program at Ashland University.

Due to the “centralized management of systems development” from the San Antonio office, the data systems support the “single USAA customer image,” and information is treated confidentially as the chief source of the organization[4]. USAA has decided to develop its IT infrastructure to better answer the demands of its members. By the 1980’s the company’s many divisions had started developing their own systems. McDermott saw the need to create an Information Services Division to integrate all the company’s systems and member information. His new vision of USAA is that the company is so integrated that members lose something of value when they go to a competitor”[5].

Enterprise view of data is required to maximize the efficiency of the organization as a whole (csu, n.d.). The sharing of data and maintaining the transparency is achieved by integrating the data within the system. Integrating the data is a complex task as there is always certain information that is sensitive and it is not meant to be shared with each and every department or individual working within or outside the organization. Making enterprise data strategy demands administrators to understand that the data is critical and is an asset to the organization. Wayne Eckerson describes enterprise view of data as the enterprise data strategy built by the organization to have a successful growth rate plan. He also points out that only one in 10 organizations have such sort of strategy as most of them don’t put together the required soft skills that are needed to manage change incurred by the strategy and the investment for data management techniques and tools to certify the delivery of high quality and consistent data supported with business initiatives and strategies (Eckerson, 2011). Most of the organizations face a lot of difficulties in maintaining the data quality. The cost of data quality incurred is much higher and it sometimes contributes to forty percent of the problems related to IT in a corporation this problem occurs because of the inaccurate data (steria, 2012). One major issue when creating an enterprise view

Businesses using data is not a new concept; however, the role of data within industries has increased dramatically over the years to the point that it is essential for a business to understand how to handle data in order to continue operations. In today’s bustling digital age, professionals credit a certain type of data called “big data” with helping businesses gain insight on consumers. Big data is created whenever you travel to your favorite restaurant, make a particular move in a video game, swipe your card to purchase your favorite pair of Crocs, or tell your Facebook friends what you had for breakfast. It is data that is too large to be captured and processed by standard business

The need for a significant data management component came from several sources. First, the University of Central Arkansas College of Business has a Business Advisory Council, which advises the college

There are many things that have to happen correctly in the design phase in order for an enterprise-level business system to be effective. In order for the system to be effective, it should align with strategy, reduce costs, improve productivity, promote timely execution, enable better decision making, leverage emerging technologies, ensure acceptable levels of control and risk management, optimize the skills and capabilities of the organization, and promote collaboration across the extended enterprise. (The

Databases have been in use since the early days of computing programs. An Information Technology services company, such as Getronics, not only utilizes databases for information and record management, it earns revenue by providing database management services. Getronics uses Microsoft SQL Server 2000 as its database software. The clients that contract Getronics for Information Technology services rely and depend on the accuracy and currency of the database information that is stored. Databases will continue to exist and expand as more companies become more of aware of the importance of record and data management.

Data managers are responsible for carrying out the data management. They could range from researchers, graduate students, research assistants, information technology experts and research librarians. These data managers are accountable for the dataset throughout its life cycle to guarantee its functionality and proficiency for reusing the information during and after a given research project is finished (Texas A & M University, 2015).

The data dictionary has evolved from being a repository of fundamental database attributes, data models and definitions of elements, files, records, users to a critical framework component for enabling application, data and system integration (Stonebraker, 2010). Data dictionaries have evolved to fill the need enterprises have for unifying and integrating diverse, often previously siloed databases and legacy systems together, creating more agile, advanced and comprehensive data models that define a business' entire value chain (Asscher, 1984). Integrating customer and sales data across the enterprise has led to Customer Relationship Management (CRM) systems becoming more effective in attracting, selling and serving prospects and customers both. At a system architectural level, the data dictionary acts as the catalyst of Master Data Management (MDM) integration which integrates siloed, legacy systems to make

ACCORDING TO DAMA-DMBOK – “DATA MANAGEMENT IS THE DEVELOPMENT, EXECUTION AND SUPERVISION OF PLANS, POLICIES, PROGRAMS AND PRACTICES THAT CONTROL, PROTECT, DELIVER AND ENHANCE THE VALUE

The concepts presented in Fisher’s “The Data Asset: How Smart Companies Govern Their Data for Business Success” are reflective of the fundamental points that were emphasized in the referenced white papers. Additionally, Fisher expands upon these theoretical concepts and illustrates the benefits of their application through real-world examples of organizational pursuits of master data management and data governance.

This report examines the emergence of U-commerce and the implications on data management it’s faced with. Through research of real cases, the paper will examine how U-commerce has been implemented into the operations of businesses and the roles that it plays. It will also provide basic examples of the four elements which make up U-commerce, Ubiquitous, Universal, Unique, and Unison. The paper will address the importance and growing concern of data management of this technology. Enterprise data has never been more accessible to users and across devices than it is now. Assuring the right data makes it to the right places and people, can be very critical to a business’s operations or decision strategies. With a multitude of devices with various interfaces, U-commerce’s data management stability, and privacy is continuously at risk and monitored. The paper will provide a sound rational for why today’s businesses need to make sure that data management is a top priority, as they move into new phases of outlets for doing business, and share business related information.