Systems | Development | Analytics | API | Testing

The digital revolution has truly transformed modern organizations, embedding data and analytics in every business process and customer interaction. Advances in technology enable smart supply chains with predictive analytics, automated logistics for same-day delivery, and AI advisors that reduce medical errors. As this continues, workers in all roles will need new a new skill—data literacy—to collaborate with these systems and each other.

The financial services industry, like so many others, has undergone long-lasting changes in recent years. With the emergence of new technologies, new regulations, and unprecedented market changes, institutions have had to contend with unpredictability and rising consumer expectations. To effectively manage constant change, financial firms have to find a way to balance innovation and efficient process execution with risk.

Businesses and organizations of all types have embraced cloud integration to transform data into business intelligence. The reason for this is simple: more and more business operations are happening in hybrid cloud — or even fully cloud-to-cloud – environments, and without proper tools to manage data in the cloud, data can become siloed, overlooked, or lost altogether.

Integration tests are slow and difficult to maintain because they have substantially more system touch points than unit tests and hence change more often. These elaborate or sophisticated tests provide a role that unit tests cannot replace, thus there is no way to avoid creating them while focusing solely on unit tests.

The KPIs that apply to each product are as different as products come. There are infinite variables that come into play when determining what exactly a KPI should be. Because these KPIs are centered around customer journeys, they are all user-based and purposely omit technical-based KPIs (such as crashes or errors). In a recent article in our Product Analytics Academy, we covered what makes a strategy a good one when understanding and choosing relevant metrics to form KPIs based on product analytics.

The company is an industrial engineering group with customers in over 100 countries served by 50,000 employees. Over the past decades, the company has established itself as a global leader in the industrial and mechanical engineering industry. Their portfolio covers commodity solutions for residential and commercial buildings for modern, highly customized solutions for state-of-the-art skyscrapers.

The Covid-19 pandemic has resulted in an unprecedented global economic landscape that is dominated by loose monetary policies, low borrowing costs and influx of capital in the equity markets. Against that backdrop, Mergers and Acquisitions (M&A) activity has surged since 2021 as companies are trying to take advantage of the current environment and adapt to the new business realities shaped by the global pandemic.

Developers test their code in chunks as it is written. Error monitoring during the development cycle alerts engineers when conflicts arise and helps them identify the root cause. So, you may wonder then, in the age of DevOps and continuous delivery, is end-to-end testing still needed? Not only is it viable, but it is also essential to validate requirements, configurations, and functionality.

On behalf of the product and engineering teams at Perforce, I am pleased to announce the official release of Helix Digital Asset Management, or Helix DAM for short. Helix DAM is the newest addition to the Digital Creation & Planning Suite. It is purpose-built to help teams capitalize on and secure their creative digital assets.