Data migration is a complex realm in information and technology. There are a lot of different techniques and strategies that data engineers and organizational leaders can implement in order to make the most out of their data, but there isn’t a clear-cut one-size-fits-all solution anywhere on the market. Data integration might be the first thing that comes to mind when discussing data migration. Data integration is the movement of data from one system to a target system. There’s a lot more that goes into data integration, but that’s for another day. An application programming interface, or API, is another aspect wherein data migration plays a major role.
APIs represent a series of rules that define the ways in which computers interact with one another. Essentially, an API sits between an application and a web server and processes the information transfer. Now, there are many different APIs that exist, and learning how to use them to your advantage can elevate entire organizations.
The Rise of APIs
While APIs used to be relatively uncommon for organizations or vendors to implement, today they are inescapable. Nearly every company has an application that needs to read and write data. Implementing these can be a pain.
That being said, APIs are sort of a necessary evil in the virtual economy that persists in our modern society. When taking into consideration how many cloud-based applications a single enterprise organization utilizes, the value of an API is immediately demonstrated. The APIs allow these hundreds to thousands of applications to communicate with one another in order to fabricate a seamless work-flow and help in delivering a powerful customer experience.
Data-security is also a major thread in the current consumer and corporate mindset. Using APIs, developers can boost security with the use of tokens, signatures, and a TLS, or transport layer security, encryption.
Modeling Source Data
When it comes to implementing and utilizing an API, the first hurdle to clear will be understanding the specifics of the API being integrated. This sounds like it should be a relatively simple and straightforward process, but that can vary greatly depending on the amount of associated documentation that accompanies the API.
Gaining an understanding of the specific API can take a bit of trial and error, and it may be helpful to create a test account in order to run some trial data. This can also help developers understand how to read and write to the specific API. Once there is a basic understanding of the API integration and how it’s going to be utilized moving forward, developers can start really digging into the meat of the process.
With a general understanding of how to read and write to the API, there is likely going to be internal data that needs to be written to the API. Choosing how to model this data is the next important step in the API integration.
Many organizations rely on an event-based model because they’re simple to build and implement. However, they can cause some complications with data-streams down the line. Another popular option is to query the data directly from the data warehouse using SQL.
Gathering Destination Data
There are going to be certain situations that require developers to fetch data before an API can be written to. This can be an important step in the workflow as it can help reduce data-based errors likely to occur.
This can specifically be the case with data that is easy to duplicate, like a user-email. The API may recognize and identify user emails as unique, when in fact they already exist within the source, your data warehouse.
Making sure to correctly match the data being transferred to and from a 3rd party API will be integral to utilizing APIs properly.
Mapping Data Fields
Mapping data fields is a vital part of any data transfer process. This is because it directly impacts the quality of your data. While this process essentially just makes sure that data is labeled correctly when it’s transferred from the source platform to the target platform, it is one of the most crucial stages in the whole process.
If data is mislabeled and that goes unnoticed, it could drastically change the way that the numbers are analyzed, predictions that result, and actions taken by the company and the professionals within.
The modern technology stack is increasing in both complexity and functionality. There is almost no avoiding 3rd party APIs in the current virtual economy, and being prepared to implement and work with them can be a major advantage for any organization.
Understanding the influence data has in our world highlights the importance of being able to correctly and accurately move, transfer, and share data between systems and platforms. In turn, helping organizations reach their fullest potential.