Document Based Data Modeling Technique

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,

An enterprise data model presents an abstraction of a more complicated real-world event or object. Generally, a data is graphical simple representation, of an interconnected real organization’s data structures. The main function of the data model is to help in understanding the complexities of a particular organization. A data model within a database environment brings out the data structures, their transformations, constraints, relations, and characteristics, thus providing a blueprint of

The idea of relational database was first introduced by E.F.Codd at IBM in 1970. It is a kind of computer database in which data is stored in Relations and is represented in the form of tables with rows and columns. Databases can vary in sizes, ranging from very small and simple to very large and complex ones. Database users can access the data practically in an unlimited number of ways. Relational databases help in finding the information in a quick and efficient manner that one is looking for.Today many popular databases use the model of relational database.

Though non-relational databases have been around since the 1960s, many companies have used relational databases to store data[2] but over the past decade with companies generating vast amounts of data, relational databases are unable to effectively manage these large data collections[1]. An ever increasing amount of companies is now, however, turning to non-relational databases known as NoSQL databases as they are more effective at handling these large amounts of data thus the reason we have seen an increase in its popularity over the past decade[2]. The term NoSQL database which stands for Not Only SQL[3] is defined as a database that

A relational database Management system (RDBMS) is the physical and logical implementation of a relational

Firstly a relational database contains a set of tables which basically are linked collectively by the relationships between the tables. Also it is also known as reason such as a database is called relational database.

It has become hard to scale relational databases in the direction and to the degree needed to manage big data in a successful and less expensive way. Instead, a new system, known as “NoSQL” or “Not Only SQL”, has been created that makes the processing of terabytes and even petabytes of data possible (Paghy, “RDBMS to NoSQL”).

Some of the challenges faced by relational databases were the mismatch that resulted when transforming graphs into tables. On the other hand, when a database was needed only for simples tasks like logging, the relational database had too much more than what was required. Web applications have many different types of attributes which does not fit easily into a relational database, which makes it a burden to handle. For example, videos, text and source code are different types of attributes from the web, which have to be stored in various tables if relational databases are used, because of its strict schema. Qualities like these, make RDBMS, a not-so-wise choice to handle blogs and other web applications. The massive data that has to be taken care of in web applications complicates data handling for famous webpages like Amazon, Google and Facebook. Factors like trillions and trillions of read and write requests which needs to be responded with minimal or no latency, leads these organizations to maintain their own hardware in clusters of thousands. The “One solution for all” is

Students should identify concepts evenly from the subject they have studied in a block and write down as to how these concepts applied or could be used in the learned subject.

The Relational database and the No SQL database are both appropriate database methods depending on the way they are being implemented and the purpose of the business for which they are being incorporated. However, both the database approaches have distinct wide variety of characteristics, based on which they can be compared and contrasted in the following way.

Answer: The term data warehouse is often used to refer to a system that extracts data from one or more sources, in order to transform and store in a model suitable for presentation and analysis. It can also be used to refer to just the database used in the aforementioned type of system. There are two main approaches to building a data warehouse, the Kimball approach and the Inmon approach.

It is easier to compare no-SQL systems to the characteristics of traditional relational databases because they have evolved from them. No-SQL models can be characterised by:

Paper-based documents have been widely used by people since paper was invented. Business, customers and suppliers use paper-based documents like letters, flyers, catalogue, invoice etc. to communicate. Businesses use paper-based documents to refer back to any concerns or catch up on people who have not paid.

The modern RDBMS advancements are not capable of supporting unstructured information with ideal space necessity. The plan winds up plainly mind-boggling and is henceforth troublesome for designers. The requirement for unstructured information administration is so annoying with conventional RDBMS arrangements (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). Moreover, RDBMS turns out to be an exorbitant answer for creating light-footed web applications with direct information investigation necessities. NoSQL is developing as a proficient possibility in this situation, which connects the issues related with RDBMS innovation. The market development can credit to creative dispatches of NoSQL arrangements, and collective endeavors by NoSQL sellers and clients. The endeavors of organizations, to enhance their market offerings, are creating the request of NoSQL, as a back-end bolster (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). The emergence of agile software development is creating the demand for NoSQL (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). They offer users much more avenues to accept data in many different forms. NoSQL is adaptable as SQL but offers many more uses that can apply to many organizations.

Along with the system design, detailed numerical models (e.g. control models, mathematical models, data constraints) can be added into the analytical framework to decrease the uncertainty of simulation results. In this process, the qualitative models should be validated to ensure consistency with numerical models. During this process, the expressions of propositional logics and linear temporal logics are replaced by High Order Logics. An example of numerical model implementation is demonstrated in Fig 5; after specifying plant power, a form of proportional-integral-derivative (PID) control can be implemented and assigned to the software “Control Routine”. Note that the meaning and actual values of each parameter are gathered from the