What is data model:
Data model is defined in different ways; Here I discuss couple of definitions.
A Data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the real world. (wekipedia,2016)
A Data model says what information is to be contained in a database, how the information will be used, and how the items in the database will be related to each other. (Dictionary.com)
Data modeling is the process of documenting a complex software system design as an easily understood diagram, using text and symbols to represent the way data needs to flow. (Margaret Rouse)
Data model is managing a large quantity of organized or unorganized data. Data model identify clearly in data modeling.
Types of Data model:
• The conceptual Model
• The Logical Model
• The physical Model
How are data models layered and why?
In database management layers of data is most important, With the help of layers of data we design database.
External layer or External level:
External layer is prior planning level, in external layer we gathered views from users. External provides strong and well maintained security mechanism by hiding parts of the database from certain users. External layer allows users to access data, which design according to their needs, in this way different users access the same data at same time in different way.
Logical layer:
The logical layer is the planning part of the database. In this logical layer we write
Data is defined as useful raw material which is intended to be useful for both the originator and for the intended receiver. Data consists largely of facts and figures ideal for communicating the intended meaning. This data can be interpreted and can be categorised as follows;
The data structure represents the logical relationships between data elements. In addition the data also determines the organizational structure, access methods, and alternative processing assosiativitas level for information.
The conceptual model will have all of the attributes from the students as well as the instructors. It will also have the all of the constraints. This model will have software and hardware independency. At this level any changes to the database management system will not affect this model. The physical model will take all the information that comes from the conceptual model and describe it so that it can be saved and stored. This model will need to know the physical storage device and access method so that it can reach the information stored in the devices. The physical model, not like the conceptual, will be both software and hardware
Relational data is when you can put data in a computer one time and it grows
Data is the form of input, which can be produced into information. For example, 5000 could be the value of a piece of data that a business has. By adding context to this, for example if an organisation sold 1000 sandwiches in a week; this becomes information, which will influence important decisions
This model demonstrates the data attributes logical entities and relationships between these entities within a business function. It also helps to create the physical data model. Moreover, it shows more details while integrate business logic and business rules. This model is used to describe the domain concept and their relationship of the domain problem.
The data that is being stored in a database is known as Meta data. Meta data is also recognized as schema for the real world data. It expresses that what sort of data will be stored in the database, what will be size of a assured attribute of the real world data, how many and what qualities will be used to collect the data about the entity in the database.
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
Data comprises of factual information. Data are the facts from which information is derived. Data is not necessarily informative on its own but needs to be structured, interpreted, analysed and contextualised. Once data undergoes this process, it transforms in to information. Information should be accessible and understood by the reader without needing to be interpreted or manipulated in any way.
Data are raw facts that have no meaning until they are processed and organized to identify patterns and relationships between the data elements.
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
The word "data" may seem to be facts or numbers collected for future references and analysis of a subject that is being carefully examined, but data are pretty much used in all aspects of our lives. With these important facts and statistics, we can help an individual or a company reduce a significant amount of cost. These data can help companies such as Apple realized future growth potentials and where it can better maximize its income.
Data is any personal information held about an individual whether this be in paper format or digital format for example; audio format or online databases. Paper based storage used to be the norm but now digital technology has improved and more and more companies and organisations are using this as it is more user friendly and easier to access, for instance having a file in London and needing information in Manchester. This analogy can also be used in defining the difference between paper postage and digital transmission. The latter
Data Flow Modelling – This is the process of modelling and recording how data flows around a system. A Data Flow Model is made up of connected Data Flow Diagrams (DFD) which are supported by appropriate documentation. DFDs represent the processes and functions within a system (activates that transform data from one form to another), data stores (file storage, external entities (things that send data into a system or receive data from a system) and finally data flows (show the flow of data around the system).
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.