Analysis of the Use, Importance, and Implementation of a Data Dictionary

Data objects can model relational data or advanced data types such as graphics, movies, and audio. Smalltalk, C++, Java, and others are objects used in object-oriented data. The object-relational is a combination of relational and object-oriented databases. Traditional and advanced data types can be used to construct database management systems. These systems can connect to a company’s website and update records as needed. Database Approach The main purpose of a database is data storage that can be stored and retrieved when needed. A popular common language called structured query language (SQL) is used to store and retrieve data in relational database. This language enables the systems to run a report or modify data or remove the data from the database. A database management system (DBMS) controls all aspects of a database, this is not limited to the creation, maintenance, and use of database. The DBMS ensures proper applications are able to access the database. An important purpose of a DBMS is to maintain the data definitions (data dictionary) for all the data elements in the database. It also enforces data integrity and security measures. Data Models Data models provide a contextual framework and graphical representation that aid in the definition of data elements. In a relational database, the data model lays the foundation for the database and identifies important entities,

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,

Up until this point, Third Star Financial Services has operated via a succession of mergers and acquisitions where systems were inherited but never integrated into the network. Its data management has been virtually non-existent and entirely ineffective. Evidence of this can be found in the absence of an enterprise-wide data management solution and the presence of several disparate systems operating independently with no measurable benefit to the company. Due to a lack of actionable data, management makes decisions based on instinct rather than through analysis. A direct consequence of this is a steadily declining market share and loss of high-level employees to competing companies. Fortunately, this discrepancy has been identified and Third Star executives have established the new goal of modernizing and streamlining operations. Using concepts outlined by the Data Management Association (DAMA), this proposed enterprise architecture will allow Third Star to transform their data from a liability to an asset.

There are certain challenges that are to be faced with this zillion of bytes of data; one of the major is integrating and retrieval of data and incorporating with the enterprise system(Dubois, 2001).

A data dictionary may be simply defined as a descriptive list of names, definitions, and elements of data captured in a database. The American Health Information Management Association (AHIMA) defines a data dictionary as, “A descriptive list of the names, also called representations or displays, and definitions of data elements to be collected in an information system or database.” Descriptively, a data dictionary is the “Rosetta Stone” of healthcare. According to legend, the Rosetta Stone may be used as an idiomatic decoder that unites disparate languages and codes. The data dictionary is no different.

A Database Management System or (DBMS) is an essential tool for any organization or company in today’s modern world. A DBMS is “a group of programs that manipulate the database and provide an interface between the database and its users and other application programs” (Stair & Reynolds, 2011, p. 189). So in choosing the right DBMS there are many factoring issues with choosing the right one for the company or organization. When choosing a DBMS one has to think about how the system will ultimately help the company or organization with day to day processes and the goals of the company or organization.

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

New applications will utilize off-the-shelf software components that have been customized per Riordan’s specifications and further messaged to ensure that each application will integrate smoothly with all the others in order to create a single cohesive whole. Great effort will be made to ensure that the data structures used in each are consistent in order to simplify the creation of the enterprise’s database. To help facilitate this, we will create an umbrella application that will integrate each other system as a module. This umbrella application will be extendable as needed and will act as a single-launch point for the various systems utilized by Riordan. We will also be working closely with Riordan’s IT department to develop a bridge that will enable them to easily port their existing databases into the new one automatically.

Course Description This course covers database concepts. Topics include data analysis, the principal data models with emphasis on the relational model, entity-relationship diagrams, database design, normalization, and database administration. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • • University policies: You must be logged into the student website to view this document. Instructor policies: This

Wailgum, T. (2008, 05 28). Master data management : companies struggle to find the truth in massive data flows. Retrieved from

Coronel, C. (2013). Database Systems: Design, Implementation, and Management, Tenth Edition. Mason, Ohio, United States: Cengage Learning.

Since 1960 and beyond the need for an efficient data management and retrieval of data has always been an issue due to the growing need in business and academia. To resolve these issues a number of databases models have been created. Relational databases allow data storage, retrieval and manipulation using a standard Structured Query Language (SQL). Until now, relational databases were an optimal enterprise storage choice. However, with an increase in growth of stored and analyzed data, relational databases have displayed a variety of limitations. The limitations of scalability, storage and efficiency of queries due to the large volumes of data [1] [2].

Business executives will also enjoy having data in a singular location. It is much easier to deal with a single set of data than to search through duplicate systems or data sets. For this reason, data consolidation becomes necessary and is preferred by leaders of the

The invention of relational databases have brought a number of changes to the business world in which they operate specially for the businesses whose prime focus is on its customers, their likes and dislikes to win more market share. There is no such concept as “one size fits all” in using this technology, it varies from industry to industry. One thing may work for some businesses and may not work for others, therefore it is advisable that one should shop around before investing in any of the technologies because it is vital to find an industry-specific solution. One technique to narrow the search for industry-specific solutions is to find out what our competitors are using to gain more customer base.

Information explosion are refers not only to the increasing amount of information available in digital form, but to the phenomenal growth in the breadth of information dissemination. This approach is often viewed as the result of: