Systems | Development | Analytics | API | Testing

In the data landscape, the people are represented by two separate yet equally important groups. The data engineers who design the Lego blocks and the data scientists who build something extraordinary out of them. These are their stories. DUN DUN! And we’re back! Last time, we went over the toolkit needed to get your foot in the door as a data engineer. You’ve gotten over the first hurdle, but I hope you haven’t fallen prey to the Dunning-Kruger Effect.

This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.

Successful usability testing takes time and expertise to plan and execute. Moderated usability testing involves a process of user research, participant recruitment, testing user flows, and analyzing data. The end results will uncover prioritized problem areas that, when addressed, will provide new ways to satisfy and retain your users. Different UX methods are dynamically used depending on the team’s goals, product, and audience.

In recent years, manufacturers faced major disruptions. Supply chain issues, unexpected product demand spikes, and delivery driver shortages led to longer lead times. While you can’t completely control external factors like these, you have far more control over your own internal manufacturing cycle times. This post will cover what cycle times are, the benefits of reducing them, and four strategies to help with cycle time reduction. .

For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.

With today’s accelerated development schedules, your team will likely rely on high-quality testers to help create great user experiences and improve software testing outcomes. Many companies have turned to on-demand freelance testers to ramp up in-house teams for better, more thorough QA coverage. Here’s the catch; this strategy only works if the testers you employ have the right skills for the job.

In a digital-first world, delivering business apps with high efficiency and top-notch quality is critical to your business success and customer satisfaction. Oracle is a major ERP application used by the world’s biggest companies to ensure business runs smoothly, but Oracle deployments are heavy, risky, and slow. How can organizations make them more efficient?

Programmers spend more time coding APIs than debugging, testing, or documenting APIs. Building APIs manually is an arduous task that prevents professionals from focusing on other tasks. Luckily, you don’t have to waste time creating APIs by hand. Instead, you can rely on instant API generation that does most of the work for you. Of course, you want to make sure you choose the right types of API generation for your projects.