Systems | Development | Analytics | API | Testing

As the pace of data grows, modern companies struggle to get a unified view and extract insights across all their disparate sources. Heck, just accessing all the enterprise datasets can be hard and requires too many email chains with the IT department. Luckily, integrating data from different systems and external sources can be simplified with the right data integration technique.

The more effectively you do mobile application testing, the fewer problems you will come across in the future. However, testing doesn’t have to be challenging. You can easily get it right if the proper techniques, tools and procedures are in place. In this article, we’ll discuss 10 of the most popular mobile application testing techniques and outline their key benefits.

As a developer supporting a growing business, you’ll likely spend a lot of time thinking about scaling. We live in a wonderful time to be solving scale problems. Computers are so fast and capable that many of the development decisions you make when writing backend systems won’t noticeably impact performance(until your app reaches an absolutely massive scale). If this weren’t the case, we’d all be writing web servers in C.

Learn about the best Python test automation frameworks for reducing the manual work in your testing projects.

Static analysis helps development teams that are under pressure. Quality releases needed to be delivered on time. Coding and compliance standards need to be met. And mistakes are not an option. That’s why development teams are using static analysis tools / source code analysis tools. Here, we discuss static analysis and the benefits of using static analysis tools.

Qlik and its NGO partners focus on leveraging data to bring a positive impact to the world. While we are still seeing the effects of the COVID pandemic throughout society, there are tremendous lessons that we can carry forward to be better prepared for the next likely pandemic.

Dataform, now GA, lets data engineers build SQL pipelines in BigQuery while following best practices like Git, CI/CD, and code lifecycle management.

A flexible, automated analytic workflow tool that integrates with BigQueryML allows no-code forecasting and model training.

Choosing the right data integration tool is crucial for businesses that want to streamline their data workflows, automate processes, and make better data-driven decisions. Two popular ETL tools on the market are Airbyte and Integrate.io, each offering unique features and functionalities catering to different data management use cases.

Increased costs and wasted resources are on the rise as software systems have moved from monolithic applications to distributed, service-oriented architectures. As a result, over the past few years, interest in observability has seen a marked rise. Observability, borrowed from its control theory context, has found a real sweet spot for organizations looking to answer the question “why,” that monitoring alone is unable to answer.