“More than 15 billion IoT devices will connect to the enterprise infrastructure by 2029.” Finding data is not going to be a challenge, clearly, but taking advantage of it all to drive business outcomes will be. Combining AI and machine learning (ML) with data collection and processing capabilities of the edge and the cloud may hold the answer.

Both businesses and governments have been forced to respond to the global pandemic by developing interactive user experiences and spatial applications using location-based data sets to visualize COVID cases, communicate confinement measures, and track vaccine rollout progress.

Maintaining quality while delivering increasingly complex products at increasing speeds is a challenge for software teams everywhere. Automating tests is essential to detect issues faster and speed up the development cycle, but it’s only one part of the equation. Managing and scaling a test automation practice, and implementing it inside an efficient DevOps cycle is even more important.

API gateway request transformation policies are incredibly powerful. There are many situations when an API developer can take advantage of request transformations to adjust the shape and values of a request to cleanly fit their API. Let’s say you’re deprecating a certain endpoint for your API, but you still need to support the old specification for a transition period.

We live in a dynamic world. It is safe to say that companies aim to speed up time-to-market and out-innovate their competition with Kafka, but at the same time struggle with some limitations. These can range from compliance-related setbacks for regulations such as GDPR, CCPA and HIPAA, to self-service slip-ups that could see a whole Kafka cluster going down. Even something as seemingly innocuous as configuring and creating a Kafka Topic can lead to operational U-turns, slowdowns and even downtime.

Over the past few years, many organizations have experienced the benefits of migrating their SAP solutions to Google Cloud. But this migration can do more than reduce IT maintenance costs and make data more secure. By leveraging BigQuery, SAP customers can complement their SAP investments and gain fresh insights by consolidating enterprise data and easily extending it with powerful datasets and machine learning from Google.

For more than three decades, Microsoft SQL Server has helped countless organizations store and manage their enterprise data, and it’s still one of the most widely used software applications on the planet. According to the DB-Engines database ranking, SQL Server remains the third most popular database management system, just behind Oracle and MySQL. Change data capture (CDC) is essential functionality for many businesses, especially those with real-time ETL use cases.

Supporting your digital strategy with the right technology is critically important. However, it’s even more important to recognize that the technology you choose should really center around enabling your organization’s business operations. Although technology alone cannot galvanize and nurture your ideal ecosystem, taking a balanced approach to your digital strategy is critical to success.

Data has become an incredibly powerful tool that helps brands streamline processes and improve customer services. To facilitate this, you will often need an API that moves data between applications without compromising the value of your information or creating vulnerabilities that can be exploited. Securing an API therefore becomes a crucial aspect of any data integration project. An API solution that meets security essentials will make it much more resistant to cyber threats.

For almost every website or web application you visit, web forms are the most popular method to collect information. Nowadays, most companies continue to rely on out-of-fashion CRM (customer relationship management) and ERP (enterprise resource planning) systems. Unfortunately, these do not allow users to import data with numerous variables into the portal, leaving employees with only one option – manually entering thousands of data entries one by one.