Financial and operational reporting for NetSuite can be a challenge. As is the case with many ERP systems, NetSuite’s reporting capabilities tend to be somewhat restrictive. It can be difficult to pull information from multiple NetSuite modules into a single, cohesive report. In other instances, information for which there ought to be a fairly straightforward reporting process turns out to be inaccessible.

If you compare the world 10 years ago with today's era, you can easily see the difference. From the difference, we don’t mean how the world looks, rather we mean how it functions now and used to function then. What do you think has changed in how the world functions now compared to back then? Is it purely due to digitalization? Or is it just a mere change? Keeping these questions aside, let us tell you that recent data suggests that people spend around 3 hours and 15 minutes on their phones daily.

After 20 years of dashboards, today’s line-of-business users expect more value from their analytics, and it’s up to your business to keep updated - or risk getting left behind. There was a time when product teams could purchase basic dashboards and data visualizations, and that was more than enough to satisfy the average user’s business intelligence (BI) and analytics needs. Today, however? Not so much.

Today, we're looking at MySQL vs MS SQL Server. Relational database management systems (RDBMS) form the backbone of enterprise IT. The main difference between MySQL and Microsoft SQL Server is that MySQL is an open-source RDBMS known for its cross-platform compatibility and cost-effectiveness, while Microsoft SQL Server is a commercial RDBMS primarily designed for the Windows platform, offering advanced features and tight integration with Microsoft technologies.

RAG and Fine-Tuning are two prominent LLM customization approaches. While RAG involves providing external and dynamic resources to trained models, fine-tuning involves further training on specialized datasets, altering the model. Each approach can be used for different use cases. In this blog post, we explain each approach, compare the two and recommend when to use them and which pitfalls to avoid.

Your API documentation is just as important as your API. It defines how easy it is for users to learn, understand, and use your open-source or paid-for product. In this post, DreamFactory highlights eight of the best API documentation examples from well-known tools. You can use these examples for inspiration when creating your API docs. Here are the key takeaways to know about each of these API documentation examples.

As demand for machine learning (ML) grows, rigorous testing and quality assurance are crucial. ML models need quality training data and robust algorithms. Without thorough testing, inaccurate outcomes can occur, especially in sectors like healthcare, finance, and transportation. A 2023 ScienceDirect report found data leakage in 294 academic publications across 17 disciplines, highlighting the need to address this issue in ML-based science.

In the previous article, we set up the AI API with AWS Lambda and Gateway, integrated it with Moesif, and then connected Stripe with Moesif. We now have the infrastructure to begin billing for API usage. In this article, we move on to configuring Moesif with the following steps in the API monetization journey: First, let’s set the prices we want to charge for API usage in Moesif.

Data has become the lifeblood of businesses across all industries. With the exponential growth of data collection and processing, the importance of data compliance has skyrocketed. And navigating this complex business landscape is vital for any organization handling sensitive information. 5 key takeaways from this post on mastering data compliance are.