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Information And Data Management

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Data management comprises all the disciplines related to managing data as a valuable resource. The official definition provided by DAMA is that "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise." This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database management.



Data model

The term data model actually refers to two very different things: a description of data structure and the way data are organized using, for example, a database management system.

Data structure

A data model describes the structure of the data within a given domain and, by implication, the underlying structure of that domain itself. A data model may thus represent classes of entities about which a company wishes to hold information, the attributes of that information, and relationships among those entities. The model describes the organization irrespective of how data might be represented in a computer system.

The entities represented by a data model can be the tangible entities, but models that include such concrete entity classes tend to change over time. Robust data models often identify abstractions of such entities. For example, a data model might include an entity class called "Person", representing all the people who interact with an organization. Such an abstract entity class is typically more appropriate than ones called "Vendor" or "Employee", which identify specific roles played by those people.

A proper conceptual data model describes an organization's semantics. It is a collection of assertions about the nature of the organization. Proper entity classes are named with natural language words instead of technical jargon. Likewise, properly named relationships form concrete assertions about the organization. For example, an relationship called "is composed of" operating on entity classes "Order" and "Line item" forms the concrete assertion "Each Order is composed of one or more Line items."

Data organization

Another kind of data model describes how to organize data using a database management system or other data management technology. It describes, for example, relational tables and columns or object-oriented classes and attributes. Such a data model is sometimes referred to as the physical data model, but in the original ANSI three schema architecture, it is called "logical". In that architecture, the physical model describes the storage media (cylinders, tracks, and tablespaces). Ideally, this model is derived from the more conceptual data model described above. It may differ, however, to account for constraints like processing capacity and usage patterns.

While data analysis is a common term for data modeling, the activity actually has more in common with the ideas and methods of synthesis (inferring general concepts from particular instances) than it does with analysis (identifying component concepts from more general ones). {Presumably we call ourselves systems analysts because no one can say systems synthesists.} Data modeling strives to bring the data structures of interest together into a cohesive, inseparable, whole by eliminating unnecessary data redundancies and by relating data structures with relationships.
Information And Data Management
Effective data management plays an essential role for any growing business. Information technology has generated advanced tools for analyzing and managing data. Use of these tools can improve the performance of almost any operation. Steps made in capturing mass data electronically have developed the need for effective management strategies. Getting more and more data and transforming it into usable information is a major concern of today's services and industries.

New technologies require new expertise, internal procedures and decision-making methods. Earlier companies were creating electronic databases, which were non-relational and difficult to use. Now with the use of highly sophisticated software and high-speed computers, businesses are reaping huge benefits from the computer/information revolution. Businesses are continuously making steps in managing data by using various tools to optimize information for sorting, searching and presentation in meaningful formats.

Many software programs and database applications are available on the market that enable companies to manipulate data in real time, capture knowledge for future use, ease the progress of operations to save time and costs and also to coordinate operations with partners.

The amount of data storage necessary and the duration it is kept online is growing swiftly, yet resources to manage data are limited. Data storage is a test to those companies wishing to maximize the value of their available data and also a huge task for storage professionals to manage and protect this data. Enterprises are struggling to bring together highly reliable platforms that can recognize where data is located in a company and whether it is utilized efficiently. Data management solutions must track, monitor and be vigilant of the conditions of your company data. It should also manage and distribute data efficiently. It should unify and simplify the administration of storage infrastructure.

Data is growing exponentially. Companies need maximum scalability, performance and production for data rigorous applications. They also need an easy to use, backup tool that provides transparency to where and how data and storage is utilized. Before choosing such and important process as data management, be sure to research your options and go with a solution that is flexible and scalable.
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Both Andrew E & Halstatt Pires are contributors for EditorialToday. The above articles have been edited for relevancy and timeliness. All write-ups, reviews, tips and guides published by EditorialToday.com and its partners or affiliates are for informational purposes only. They should not be used for any legal or any other type of advice. We do not endorse any author, contributor, writer or article posted by our team.

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