Importance Of Data Architecture And The Entire Enterprise Architecture

Architecture design is important because when a company is progressively receiving business and different aspects of the customers’ usage of the company changes the warehouse needs to frequently be updated. Continental planned for the company to use real-time data warehousing so they structured the design to accommodate for the demand of real-time information. The information then became easier to update the warehouse in a timely manner.

At this stage, the specifics of the scope and the general content of the project has been identified and is the first step in database development. It illustrates the overall picture of organizational data at a high level of abstraction. In addition,

According to Berson and Dubov (2011), there are four typical categories of drivers that explain the need for data management: Business Development, Sales and Marketing; Customer Service; Risk, Privacy, Compliance and Control; and Operational

Business organizations receive different types data, from different sources, in the form of sales records, customer databases,

Data management is vital to any business as this is a key tool to an organisations business improvement, as you can refer back to data, and compare them against benchmarks. Analysing data can provide evidence for possible future structure such as identify trends, as well as indicate where improvements can be made. However there are strict procedures to be followed when collecting and storing data.

There are several important steps to consider when designing a database, as a well-designed database should be deployed and not only support the accuracy and integrity of business information but also avoid redundant data and assist with has enterprise level reporting tasked. If we analyze the

With the amount of information and moving data, the development and use of these systems is imperative to stay ahead, innovative, and secure as a company. With such an overload of different information it would be nearly impossible for an individual to organize or recognize different patterns that a developed system can. Although, wise people are needed in order to create and develop them and without their knowledge and insight the systems can never be created successfully in the first place. People, information, and information systems are all an important parts of the puzzle to analyze data and create new management information systems that enable new ways to stay ahead of

A Data Model is the practice of developing a model that defines all the level entities of an enterprise at a logical level, how they relate to one another, their life cycles, the services and systems that act upon it, and the places of the entity’s application in the enterprise. An Enterprise Data Model (EDM) also defines each entity’s attributes and forms the ground of a common language in an enterprise (Rob, Coronel, & Crocke, 2008). This paper develops and illustrates a comprehensive enterprise data model for a particular group of choice in Wild Wood Apartments. The department of interest in the organization is the Administration Department and in particular the managerial level that manages the apartments. The paper further articulates the rules of operation within the department to allow for an application model. Finally, there is rule reflection, i.e. assessing the extent to which the data model reflects on the operating rules of the organization.

1. Given our studies of EA frameworks you are to identify five different criteria by which you can assess the strengths and weaknesses of the: TOGAF, FEA, LightWeight and Zachman framework. (50 points)

Data, data is essential in todays business environment. The amount of information that businesses collect is growing larger and larger everyday. This information can be simple such as a customers name, address, telephone number, gender, or credit card number. The data can also be more complicated and require more insight such as finding out what a customers shopping habits are or finding out how to cater your advertisements based on your clients. With the amount of data every growing we are faced with some issues. Mainly how does a company process all of this information and keep it safe at the same time. This data that is collected is stored and is never truly deleted or gone. Big question is are we equipped to handle all of this information on our own? Well we can but we need to use Information systems to compile it all, process it, and make sure it is safe. Management information systems are made up of computing and communications hardware, operating system software, applications software that support business operations, and staff to analyze and create systems that help to achieve business goals and objectives. Management information systems support a broad array of business operations and enable interaction with an organization 's suppliers, customers and service providers. Every company for the most part creates their own software that is specific to their goals and what they hope to achieve. Software such as ERP (enterprise resource planning) is used to support large

(b) A conceptual schema of all the data generated in the enterprise and how it was all related

Enterprise Architecture (EA) is a process of describing the structure and behavior of an enterprise (including its information systems), then planning and governing changes to improve the integrity and flexibility of the enterprise.

Data Organization is the stage where data is being stored and organized. The storage of the data can be image based, graph based, documents or key-values. An Extract-Transform-Load(ETL) step is usually needed before data is stored in the final

A fundamental concept of a data warehouse is the distinction between data and information. Data is composed of observable and recordable facts that are often found in operational or transactional systems. At Rutgers, these systems include the registrar’s data on students (widely known as the SRDB), human resource and payroll databases, course scheduling data, and data on financial aid. In a data warehouse environment, data only comes to have value to end-users when it is organized and presented as information. Information is an integrated collection of facts and is used as the basis for decision making.

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.