What are major categories of APIs and what are their characteristics? (I.e. Private, Partner, Public). What are examples of each?
The major categories of APIs include public, partner, and private APIs. Public APIs allow organizations to expose the functionalities and information of their applications or systems to third parties (De, 2017). The third parties may or may not have a business relationship with the organizations. The main features of public APIs include a focus on external consumers, open availability, catalog listing, usage without terms and conditions limitations, and subscription-based APIs. Public APIs may require consumers to use API keys and registration (De, 2017). An example is Google Maps API.
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Companies use partner APIs strategically to facilitate communication and software integration with their strategic business partners. Partner APIs are characterized by a company to company integration. They are hidden from the public (De, 2017). They are also characterized by onboarding mechanisms with validation workflows for a firm to access the APIs. They are, however, only used with trusted and known partners. An example includes the integration between a company and an accounting firm. Others such as Twitter- or Pinterest-firm integration require companies to request for access to Twitter or Pinterest customer data.
Firms use private APIs to facilitate the internal integration of various systems and applications. The main features include a secure way of using and providing APIs characterized by point to point integration and the use of authentication and authorization mechanism to ensure secure access to the APIs (De, 2017). Private APIs are not accessible to the public and operate within a company. Amazon’s private API is an example in which the firm uses the APIs to handle its operations. A menu management system is another example of a private API, which only the administrator uses it to monitor the menu that is viewed by online ordering system users. Another example is the order retrieval system that only the staff uses to restore and display instructions.
2. What is data abstraction? What's an example of it?
Data abstraction involves a reduction of a specific data set to a simple form (Pakhira, 2012). Achieving abstraction involves replacing or deleting elements of anything to create a new collection of essential features. Data abstractions aim to organize the applications that will use compound data objects to allow them to function on abstract data. Here, the applications use data without making assumptions regarding the data as the assumptions are not required to execute the task at hand (Pakhira, 2012). The abstract data is independent of the applications using it. For instance, a social network application such as Facebook deal with a wide variety of data related to an individual. The data can include name, address, email or id. Instead of creating variables for these data groups, the developers can create abstractions for individuals by defining the data for an individual as fields in the abstraction. An individual can then be represented as a single entity. Rather than having thousands of variables, the application can possess less than twenty variables and multiple fields for each variable. Abstraction reduces the complexity of data to a manageable and simple form.
3. What is logical data and what is physical data? What are examples of each?
The concept of logic data applies to a higher data standard or organizational data. Logical data describe dimensional or relational structures independent of the physical implementation details (Kendall & Kendall, 2020. Logical data allows architects to describe what data is stored in a system and the relationship between the data. Architects use two key techniques when dealing with data, which are organization criteria and the consistency data structure. An Example of logical data for a retail business may include a description of the store, goods, and time, and the way these elements related to each other.
Physical data describes mostly all the interaction data and artifacts in a database. It is built using the Database Management System's native database language (DBMS) and defines dimensional or relational structures focused for a specific database (Kendall & Kendall, 2020). It demonstrates how systems store data. The database managers use physical data to determine the scale of the database structures and its planning ability. Examples include file organization, data structures, storage format for data attributes, and physical records of attributes. The data describes the file organizations, indexes, and base relations required to access data in a system.
Manager
Orders are forwarded to the database after being accepted on the Restaurant system. The flow for delivering the order includes:
A customer places an order at the system platform
The platform forwards the order to the restaurant system
The manager accepts the order
The order is forwarded to the database (DB),
The DB forwards the order to the Sale API, which then forwards it to the sale system
After accepting the order, the sales system updates the order status and forwards it to the sale API.
The sale API forwards the updated order status to the DB, which then forwards it to the order API.
The Restaurant system updates the order status, before sending the updated status to the order API.
The Order API updates the order states before dispatching the order through the restaurant platform.
Importance of API
Instant payment transactions illustrate the significance of APIs in daily retail purchases by showing how the technology enhances convenience and enables people to transact from any location globally through practical network infrastructures. The entire world relies on APIs to access information, acquire a degree, work, or engage in financial transactions. APIs powered by events can help ensure appropriate access to services wherever they are required to improve lives.
References
De, B. (2017). API Management An Architect’s Guide to Developing and Managing APIs for Your Organization . Apress.
Kendall, K. E., & Kendall, J. E. (2020). Systems analysis and design . Harlow Pearson.
Pakhira, M. K. (2012). Database management system. Prentice-Hall of India Pv.
