Data source

A data source is the location where data that is being used originates from. A data source may be the initial location where data is born or where physical information is first digitized, however even the most refined data may serve as a source, as long as another process accesses and utilizes it. A data source is the place where data originates from, or where physical information is first digitized. It can be a database, a flat file, live measurements from physical devices, or scraped web data.?

In short, data source refers to the physical or digital location where data can be stored as a data table, data object, or another storage format. It’s also where someone can access data for further use — analysis, processing, visualization, etc.

Most data sources can be divided into two main categories: machine data sources and file data sources. Let’s look at each of them in more detail.

Machine Data Sources

The machine data source is created on the client machine, be it a computer, a phone, an Internet of things, or another device. It is available to users currently logged onto the system and cannot be shared with other machines. They can be further categorized into user data sources (available only to a particular user) and system data sources (available to all the system users).

File Data Sources

File Data Sources are not assigned to particular machines, applications, systems, or users. They can be shared between devices. These data sources are usually stored in separate text files. They do not have a data source name (DSN) like machine data sources. Such data sources include spreadsheets, text documents, PDFs, images, and audio and video files.

To better understand the functionality of data sources, let’s look at how data sources help us manipulate the data.

Data Model

A data source is a place where the data is modeled, that is organized in a logical structure. Thus, a data model is a set of fundamental rules of how data is organized inside a data source. It is used to represent the relationship between different data elements and helps to manipulate data consistently. For good use of data, it should be meant in a readable or in any other way clear format for users or machines. Examples of data models include tables in a database or fields in a report. The most common models are hierarchical, relational, unified modeling language (UML), entity-relationship, object-oriented, and dimensional data models.

Data Source and Connectors

Data Source Connectors are used to facilitate the flow of data between applications, databases, analytics tools, etc. It makes it easier for organizations to access and analyze their data quickly and efficiently. In other words, connectors also provide a unified platform that allows different applications to communicate, allowing organizations to make better decisions faster. For example, the IT team uses Tableau for reporting and forecasting. In that case, it can use connectors to connect to the data it needs, including those contained in Jira, Confluence, Excel files, cloud databases, etc.

Copy and Share Data Sources

As we already figured out, machine data sources are hard to manage, as their capabilities are limited within one device, system, user, etc. File data sources, on the contrary, are more eligible for different manipulations. Like most digital assets, they can be copied and shared with other devices or users. Data sources can be copied and shared in a variety of ways. Some can be downloaded to a local computer and sent via email, cloud storage, or other file-sharing services. Another way is to export the data source as a CSV, Excel, or other file format and then share the file. Finally, data sources can be shared by providing access to the source, such as a web page or database.

Conclusion

Data has become a valuable commodity in the modern economy, as it is increasingly used to make decisions, optimize business processes and create new products and services. Businesses use data to gain insights and competitive advantages. Data sources help teams manipulatу the data more effectively. They are used for data collection, organizing it in a structured, easy-to-use form, providing access, and moving to the required destinations. Data sources are indispensable for system integrations, with the help of connectors, APIs, or other technical methods that help to migrate data to where it is needed.