Systems | Development | Analytics | API | Testing

5 Essential APIs for Application Integration

Trying to determine what applications your organization needs? The application integration question can be a challenging exercise. According to a recent study, only 30% of companies succeed at digital transformation. Their lack of innovation proved one key point: companies must be agile and quick enough to implement new technologies if they wish to remain competitive.

A Complete Process Automation Solution to Let Financial RegTechs Work Faster, Together

The financial services industry is vast, complex, and almost infinite in its diversity. So, too, are the regulatory agencies overseeing this industry. For example, the US market's regulatory framework is incredibly complex: More than 50 state or local and more than a dozen federal agencies coexist to keep the financial services marketplace healthy, competitive, and safe for consumers. The missions of the agencies overseeing the financial services industry vary as widely as the sector itself.

HTTP Status Code to Use for CRUD Operation

When responding to our clients, we can utilize various status codes defined by the HTTP protocol. Others wish to fully utilize HTTP's library of codes to inform their clients of any issues; some APIs simply use the most fundamental codes and develop their own error-signaling systems on top of them. This tutorial explains the CRUD actions and the status codes you should employ for a clean API design.

Go Hybrid & Multi-Cloud or Don't Go

Over the past few months industry analysts have been making some pretty controversial recommendations for data management in the cloud. For a thoughtful and entertaining analysis, I strongly recommend you spend a few minutes watching the keynote session by Pat Moorhead, CEO Moor Insights & Strategy, at the Evolve 2022 Data event in New York. His takeaway: “The world is very much going to be hybrid and multi-cloud.” His delivery—priceless.

Making Data Actionable

Too many data teams focus on data movement and creating data pipelines without aligning those activities to business outcomes. Data teams are meant to make data flows work so much of their focus involves managing data connections across the data ecosystem. Pulling data from Salesforce or ensuring reverse ETL from a data warehouse helps support successful data movement and overall data pipeline development. It doesn't always align to a more effective supply chain or cost savings.