In the race to interconnect our enterprise IT systems, the use of Application Programming Interface (API) technologies forms an essential means of applying glueing bonds between services, between applications and sometimes between apps, data services and entire operating systems. Essentially considered to be something of an open entity, when your Uber app needs a map, it channels Google Maps via an open API. But ever an open API is not always as open as it might be… and some are closed, internal and private, so what role do these technologies play in the new and diverse landscape of cloud-native business?
Terence Bennett is CEO of Las Vegas-headquartered DreamFactory, an organisation that specialises in the building, securing and documenting of internal & private REST APIs with built-in enterprise security on bare-metal, Virtual Machines (VMs) or containers. His definition of a private API is a proprietary function that might typically connect an organization’s own front-end (customer-facing) application to other services within its internal infrastructure.
We can think of this as a scenario where an organisation is both the producer and consumer of the API.
Beyond OpenAPI specs
In his own research, Bennett says his team has identified a bunch of other tools which use different methods to generate APIs. Some of these other tools are platform or database-specific. But given that many people in technology think that the practice of ‘API generation’ simply means generating an API against an OpenAPI spec, his team wanted to do something more progressive that involved wider use of automation and integration technologies.
NOTE: The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to HTTP APIs which allows both humans and computers to discover and understand the capabilities of the service without access to source code, documentation, or through network traffic inspection. When properly defined, a consumer can understand and interact with the remote service with a minimal amount of implementation logic.
“Organisations are increasingly turning to advanced API generation tools to streamline the process of building REST API integrations between diverse systems,” said Bennett. “These tools are playing a pivotal role in breaking down data silos and fostering seamless data exchange across various platforms within an enterprise. [We wanted to] explore how enterprises are leveraging these innovative solutions to enhance connectivity from isolated data systems to comprehensive data warehouses or data lakes and subsequently, to distribute this integrated data throughout the organisation via sophisticated data products.”
Breaking down data silos
Traditionally, data stored in siloed systems within an organisation posed significant challenges to data accessibility and interoperability. These silos hindered the ability to gain insights and make informed decisions based on comprehensive data analysis.
API generation tools are argued to have emerged as something of a game-changer, offering a solution to this problem by enabling the creation of custom REST APIs. These APIs facilitate secure and efficient communication between disparate systems, ensuring data can be shared and accessed in real-time. The automation provided by these tools reduces the complexity and time required to develop integrations, making data more accessible and actionable.
“A critical step in data management is consolidating information from various sources into a centralised repository, such as a data warehouse or data lake,” explained Bennett. “API generation tools streamline this process by providing a straightforward means to create integrations that automatically transfer data from siloed systems into these centralised data storage solutions. This consolidation enables organisations to store vast amounts of structured and unstructured data in a single location, simplifying data management and analysis. The automated nature of these tools ensures that the data remains up-to-date and accurate, providing a reliable foundation for analytics and business intelligence.”
The rise of ‘data products’
The ultimate goal of integrating data systems and consolidating data into warehouses or lakes is to improve decision-making and drive business value. API generation tools extend their utility by facilitating the extraction of this consolidated data into various data products. These products can range from analytical dashboards and reports to machine learning models and predictive analytics tools. By automating the creation of APIs for data extraction, organisations can efficiently distribute tailored data products to different departments or teams, enabling them to leverage relevant insights for strategic decision-making.
“The adoption of API generation tools represents a significant leap forward in how organisations manage and leverage their data. By automating the creation of REST API integrations, these tools are eliminating the technical barriers associated with data silos, facilitating efficient data consolidation and enhancing the distribution of data through customised data products. This revolution in enterprise integration not only optimises data management practices but also unlocks new opportunities for innovation and growth,” clarified DreamFactory’s Bennett.
As enterprises continue to navigate the complexities of digital transformation, the strategic deployment of API generation tools is becoming indispensable. These tools are not just simplifying the technical aspects of data integration; they are reshaping the data landscape within organisations, fostering a culture of data-driven decision-making and innovation.
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