Systems | Development | Analytics | API | Testing

In our latest research, conducted this year with AIIA and FuriosaAI, we wanted to know more about global AI Infrastructure plans, including respondents’: 1) Compute infrastructure growth plans 2) Current scheduling and compute solutions experience, and 3) Model and AI framework use and plans for 2024. Read on to dive into key findings! Download the survey report now →

Tech debt is the cost of choosing quick solutions over better ones, requiring future rework. It is a fact of life for developers–when work piles up and deadlines approach, you prioritize what’s most important. In the short term, taking the easy road keeps your release schedule on track and your applications running smoothly, at least on the surface.

Struggling to ensure accurate and efficient data exchange? EDI data mapping is the answer to streamlining your business’s communication pipeline. This indispensable process converts data into universally recognizable formats for seamless transactions with trading partners. Discover how to implement EDI data mapping effectively with our comprehensive guide, designed to give you the edge in today’s data-driven marketplace.

Achieving product-led growth (PLG) is a continuous goal for independent software vendors (ISVs) and enterprises aiming to scale efficiently and sustainably. The challenge is differentiating your product enough in a crowded market to retain users, and unlock new revenue streams. Traditional approaches to product-led growth often fall short in meeting the dynamic needs of today's data-driven users, who seek immediate, actionable insights within the applications they use.

Fivetran and Databricks bring you machine learning, simplified.

Understanding BAI file integration is essential for financial experts looking to optimize data management and reconciliation across banking platforms. Our guide demystifies integrating BAI files into your financial systems, exploring the techniques, benefits, and best practices for a smooth transition that can save time and reduce errors.

It's summer of 1997, and I’m seven years old. I’ve just finished typing up my last homework assignment of the year, and a few loud keyboard taps later, it’s saved to a floppy disk, ready for printing at the school library. I grab my headphones and press play on my Walkman: Fleetwood Mac – Rumors.

Geospatial data can give a business a competitive edge — especially when it’s combined with the company’s own data resources. Considering a new store location? You’ll want to analyze not just where your nearest competitors and potential customers are, but also retail footfall numbers, historical traffic patterns, distance from distribution centers, environmental factors, potential delivery times to customers and more. You need geospatial data to make it all happen.

We’re constantly bombarded by data points and it takes real effort to make sense of them. While having a lot of information is a good thing, it’s easy to get overwhelmed and miss what’s really important. Businesses especially need to be able to sort the wheat from the chaff and assess their data accurately. But, how do you go about this exactly?