WHAT IS DATA?
Since the invention of computers, people have used the term data to refer to computer information, and this information was either transmitted or stored. But that is not the only data definition; there exist other types of data as well. So, what is the data? Data can be texts or numbers written on papers, or it can be bytes and bits inside the memory of electronic devices, or it could be facts that are stored inside a person’s mind
Data are units of information, often numeric, that are collected through observation. In a more technical sense, data are a set of values of qualitative or quantitative variables about one or more persons or objects, while a datum is a single value of a single variable.
TYPES OF DATA
Quantitative Data Type
This data type tries to quantify things and it does by considering numerical values that make it countable in nature. The price of a smartphone, discount offered, number of ratings on a product, the frequency of processor of a smartphone, or ram of that particular phone, all these things fall under the category of Quantitative data types.
The key thing is that there can be an infinite number of values a feature can take. For instance, the price of a smartphone can vary from x amount to any value and it can be further broken down based on fractional values. The two subcategories which describe them clearly are:
Discrete
The numerical values which fall under are integers or whole numbers are placed under this category. The number of speakers in the phone, cameras, cores in the processor, the number of sims supported all these are some of the examples of the discrete data type.
Continuous
The fractional numbers are considered as continuous values. These can take the form of the operating frequency of the processors, the android version of the phone, wifi frequency, temperature of the cores, and so on.
How To Analyze Data?
Ideally, there are two ways to analyze the data:
- Data Analysis in Qualitative Research
- Data Analysis in Quantitative Research
1. Data Analysis in Qualitative Research
Data analysis and research in subjective information work somewhat better than numerical information as the quality information consists of words, portrayals, pictures, objects, and sometimes images. Getting knowledge from such entangled data is a confounded procedure; thus, it is usually utilized for exploratory research as well as data analysis.
Finding Patterns in the Qualitative Data
Although there are a few different ways to discover patterns in the printed data, a word-based strategy is the most depended and broadly utilized global method for research and analysis of data. Prominently, the process of data analysis in qualitative research is manual. Here the specialists, as a rule, read the accessible information and find monotonous or frequently utilized words.
2. Data Analysis in Quantitative Research
Preparing Data for Analysis
The primary stage in research and analysis of data is to do it for the examination with the goal that the nominal information can be changed over into something important. The preparation of data comprises the following.
- Data Validation
- Data Editing
- Data Coding
For quantitative statistical research, the utilization of descriptive analysis regularly gives supreme numbers. However, the analysis is never adequate to show the justification behind those numbers. Still, it is important to think about the best technique to be utilized for research and analysis of data fitting your review survey and what story specialists need to tell.
Consequently, enterprises ready to make due in the hypercompetitive world must have a remarkable capacity to investigate complex research information, infer noteworthy bits of knowledge, and adjust to new market needs.
WHAT IS DATA API
Quantitative Data Type
This data type tries to quantify things and it does by considering numerical values that make it countable in nature. The price of a smartphone, discount offered, number of ratings on a product, the frequency of processor of a smartphone, or ram of that particular phone, all these things fall under the category of Quantitative data types.
The key thing is that there can be an infinite number of values a feature can take. For instance, the price of a smartphone can vary from x amount to any value and it can be further broken down based on fractional values. The two subcategories which describe them clearly are:
Discrete
The numerical values which fall under are integers or whole numbers are placed under this category. The number of speakers in the phone, cameras, cores in the processor, the number of sims supported all these are some of the examples of the discrete data type.
Continuous
The fractional numbers are considered as continuous values. These can take the form of the operating frequency of the processors, the android version of the phone, wifi frequency, temperature of the cores, and so on.
You can also apply the same technique to a survey form where user experience is recorded on a scale of very poor to very good. The differences between various classes are not clear therefore can’t be quantified directly.
WHAT IS AN API?
In computing, an application programming interface is an interface that defines interactions between multiple software applications or mixed hardware-software intermediaries
What is an API?
An API is a set of programming code that enables data transmission between one software product and another. It also contains the terms of this data exchange.
How API works.
Application programming interfaces consist of two components:
- Technical specification describing the data exchange options between solutions with the specification done in the form of a request for processing and data delivery protocols
- Software interface written to the specification that represents it
The software that needs to access information (i.e., X hotel room rates for certain dates) or functionality (i.e., a route from point A to point B on a map based on a user’s location) from another software, calls its API while specifying the requirements of how data/functionality must be provided. The other software returns data/functionality requested by the former application.
And the interface by which these two applications communicate is what the API specifies.
The Red Hat specialists note that APIs are sometimes considered contracts, where documentation is an agreement between the parties: “If party first sends a remote request structured a particular way, this is how the second party’s software will respond.” The API documentation is a manual for developers that includes all necessary information on how to work with the API and use the services it provides. We will talk more about the documentation in one of the next sections.
Each API contains and is implemented by function calls – language statements that request software to perform particular actions and services. Function calls are phrases composed of verbs and nouns, for example:
- Start or finish a session
- Get amenities for a single room type
- Restore or retrieve objects from a server.
Function calls are described in the API documentation.
APIs serve numerous purposes. Generally, they can simplify and speed up software development. Developers can add functionality (i.e., recommender engine, accommodation booking, image recognition, payment processing) from other providers to existing solutions or build new applications using services by third-party providers. In all these cases, specialists don’t have to deal with source code, trying to understand how the other solution works. They simply connect their software to another one. In other words, APIs serve as an abstraction layer between two systems, hiding the complexity and working details of the latter.
Types of APIs
APIs by availability aka release policies
In terms of release policies, APIs can be private, partner, and public.
Types of APIs by availability
Private APIs. These application software interfaces are designed for improving solutions and services within an organization. In-house developers or contractors may use these APIs to integrate a company’s IT systems or applications, build new systems or customer-facing apps leveraging existing systems. Even if apps are publicly available, the interface itself remains available only for those working directly with the API publisher. The private strategy allows a company to fully control the API usage.
Partner APIs. Partner APIs are openly promoted but shared with business partners who have signed an agreement with the publisher. The common use case for partner APIs is software integration between two parties. A company that grants partners with access to data or capability benefits from extra revenue streams. At the same time, it can monitor how the exposed digital assets are used, ensure whether third-party solutions using their APIs provide decent user experience, and maintain corporate identity in their apps.
Public APIs. Also known as developer-facing or external, these APIs are available for any third-party developers. A public API program allows for increasing brand awareness and receiving an additional source of income when properly executed.
There are two types of public APIs – open (free of charge) and commercial ones. The open API definition suggests that all features of such an API are public and can be used without restrictive terms and conditions. For instance, it’s possible to build an application that utilizes the API without explicit approval from the API supplier or mandatory licensing fees. The definition also states that the API description and any related documentation must be openly available, and that the API can be freely used to create and test applications.
Commercial API users pay subscription fees or use APIs on a pay-as-you-go basis. A popular approach among publishers is to offer free trials, so users can evaluate APIs before purchasing subscriptions.
APIs by use cases
APIs can be classified according to the systems for which they are designed.
Database APIs. Database APIs enable communication between an application and a database management system. Developers work with databases by writing queries to access data, change tables, etc. The Drupal 7 Database API, for example, allows users to write unified queries for different databases, both proprietary and open source (Oracle, MongoDB, PostgreSQL, MySQL, CouchDB, and MSSQL).
Another example is ORDS database API, which is embedded into Oracle REST Data Services.
Operating systems APIs. This group of APIs defines how applications use the resources and services of operating systems. Every OS has its set of APIs, for instance, Windows API or Linux API (kernel–user space API and kernel internal API).
Apple provides API reference for macOS and iOS in its developer documentation. APIs for building applications for Apple’s macOS desktop operating system are included in the Cocoa set of developer tools. Those building apps for the iOS mobile operating system use Cocoa Touch – a modified version of Cocoa.
Remote APIs. Remote APIs define standards of interaction for applications running on different machines. In other words, one software product accesses resources located outside the device that requests them, which explains the name. Since two remotely located applications are connected over a communications network, particularly the internet, most remote APIs are written based on web standards. Java Database Connectivity API and Java Remote Method Invocation API are two examples of remote application programming interfaces.
Web APIs. This API class is the most common. Web APIs provide machine-readable data and functionality transfer between web-based systems which represent client server architecture. These APIs mainly deliver requests from web applications and responses from servers using Hypertext Transfer Protocol (HTTP).
Developers can use web APIs to extend the functionality of their apps or sites. For instance, the Pinterest API comes with tools for adding users’ Pinterest data like boards or Pins to a website. Google Maps API enables the addition of a map with an organization’s location.
WHAT IS DATA API?
What is Google Data API?
A Google Data API is an API based upon the Google Data protocol. The Google Data protocol is based on the Atom 1.0 and RSS 2.0 syndication formats, plus the Atom Publishing Protocol (APP). The Google Data protocol extends those standards in various ways, using the extension mechanisms built into the standards.
