Today in the food-service industry, a spot of deal (POS) system is the most widely used technology. It allows retailers to use every facet of their business. In most cases, POS systems are electric systems which allow businesses to preserve and analyze a multitude of inventory and deal data on a continuing basis.
Much just like a computer, the POS system includes two basic parts: the touchscreen and the program that runs the system. It allows cashiers to type in customer's orders through the process. Moreover, matching to Chen and Lee (2010), "The idea of sales (POS) system supplies the information analysis ability and can be used to examine consumers' purchasing tendencies as well as forecast needs. "
As it shows above, a POS system is quite essential for retail business, especially Panda restaurant who is going to franchise more nationwide stores. So setting up a POS system and developing a proper repository is at the top of its agenda.
The modern repository (a hierarchical model) appeared in the mid-1960s. Relating to Rob and Coronel (2009), "A data model is a comparatively simple representation, usually visual, of more technical real-world data buildings" (p. 31). Also in the middle 1960s, a different type of repository model, network model, appeared. Network structure was developed to represent the more technical data connections that hierarchical framework cannot model.
Both hierarchical and network models are called flat-file databases to distinguish from relational databases. In June, 1970, E. F. Codd proposed the relational model. It was an announcement of the introduction of the relational repository. Compared to former database methods, the relational databases model hid complexities from end-users. In addition, relational databases model had flexible and standard query terminology (SQL).
In 1976, Peter Chen shown the Entity-Relationship (ER) model. ER models are represented in an entity relationship diagram (ERD), that could be utilized to depict venture data modeling. Organization Data Modeling is "a consistent view and knowledge of data elements and their interactions across the enterprise" ("Venture", Para. 2). This type of data modeling provides usage of information scattered throughout an venture under the control of different divisions or departments with different directories and data models.
In the mid-1980s, Object-oriented (OO) and extended-relational data models (ERDM) arrived. Although the OO and ERDM concentrate on different fields, their principles and strategies are merging to help another Internet burgeoning.
2. Technical explanation of a point of sales relational repository.
Fundamentals of relational databases
Tables, primary tips and foreign keys
Tables in the relational model are used to symbolize "things" in the real world. They constitute rows and columns. Each table should represent only 1 thing. These exact things (or entities) can be real-world things or events. For instance, a real-world thing in X restaurant might be considered a customer, an inventory item, or a supplier. Examples of occasions could be telephone-orders, buys from suppliers or credit-based card transactions.
The relational model requires that all row in a desk be unique. If duplicate rows are allowed in a table, then there is absolutely no way to distinctively address confirmed row via development. This will generate all sorts of ambiguities and issues that should be avoided. To guarantee uniqueness for a desk, female key is designated. As Rob and Coronel (2009) described, an initial key is "an identifier made up of one or more attributes that distinctively identifies a row" (p. 671). Each stand can have only 1 primary key, even though it can be made up of several attributes.
Although primary keys are essential to individual tables, they would be of little use if databases contain only impartial and unrelated tables. But at the time the data source administrator (DBA) starts off to create human relationships that join collectively multiple tables, major keys become essential. Another important term-foreign key-emerges along with this process. A international key in a stand used to research a primary type in another desk.
The way a spot of sales relational repository works
Retrieving data from store controller
Translating transaction synopsis log (TLOG) data
Storing data in a RDB
3. Comparisons between flat-file databases and relational data source.
The flat-file data source is ideal for small amounts of data that should be human readable or edited yourself. Essentially it is a couple of strings in a single or more documents that can be parsed to get the info they store. The flat-file data source is great for saving simple lists and data beliefs. But it can get complicated whenever a DBA make an effort to replicate more complex data structures. That's not impossible to store intricate data in a flat-file data source. The truth is that doing so can be more costly with time and processing electricity compared to a relational database. The techniques used for saving the more technical data types are also more likely to render the record unreadable and un-editable to anyone looking after the repository.
The typical flat-file databases is split utilizing a common delimiter. If the info is easy enough, this may be a comma, but more technical strings are usually split up using tabs, new lines, or a blend of characters not likely to be found in the record itself.
One of the key problems with using flat data for a good semi-active databases is the fact that it is very susceptible to corruption. There is absolutely no inherent locking mechanism that detects when a file has been used or modified, and so this needs to be done on the script level. Regardless of whether care is taken to lock and uncover the record on each access, a active script can cause a "race condition" which is easy for a record to be wiped clean by several operations that are preventing for the lock; the timing of document locks will become more and more important as a niche site gets occupied.
The relational databases like Oracle, MySQL, Microsoft SQL Server, and so forth have a more logical structures to store data. Dining tables may be used to represent real world objects. For example, a desk called VENDOR could have the columns seller name, supplier address, and vendor phone number. These columns describe the details of every seller and each row in the desk represents a new vendor.
The "relation" originates from the actual fact that the dining tables can be associated with each other. For instance certain products in an inventory desk could be cross-referenced with the merchandise desk to provide more information about any of it. These varieties of relations can be quite complex in dynamics and would be hard to replicate in the standard flat-file format.
Retail businesses, X restaurant included, require adaptable and customizable reporting functions of their database systems to analyze sales and determine which products (entries) are profitable and that are not. A smartly designed point of deal relational data source could provide perfect alternatives for those requirements. One major advantage of the relational model is the fact that there should be no duplication of any data. No duplication really helps to maintain data source integrity; on the other hand, it saves a lot more time to process. Also, a relational database is versatile to retrieve, form, and edit data through different applications. For instance, X restaurant can access the databases and create a variety of sales records by time frame, item, server and so on.
Based on all the discussion above, a spot of sales relational repository system is the right solution for X restaurant to manage proficiently and even generate income.
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