Systems | Development | Analytics | API | Testing

Enterprise Performance Management (EPM) is the backbone of smarter business decisions—it brings structure to planning, budgeting, reporting, and analysis. But when handled manually, it can quickly become a grind: endless spreadsheets, complex data mapping, and reports that swallow valuable time. The work is essential, yet the process often slows teams down, leaving less room for the insights leaders actually need.

After spending months of development work to build ODBC connectors for REST APIs, the performance still falls short of your expectations. You can’t recover the time spent, and you need a new solution. This scenario is all-too familiar for developers. Here, we discuss how you can improve your REST API, making it ready for enterprise-level users.

If you are looking for a reporting solution that can handle complex data and deliver fast results, you might want to check out Jet Reports from insightsoftware. Jet Reports is a powerful Excel-based reporting tool that directly connects to your Microsoft Dynamics ERP and allows you to create custom reports and dashboards with ease using real-time data. Jet Reports is designed to make your reporting experience fast and smooth.

Many people in project management think of Microsoft Excel as an inferior tool. They worry about version control with collaboration across the business, especially when dealing with large enterprise projects. However, Excel can be a powerful project management tool when used with the right add-ins. When you understand the unique challenges of enterprise projects and how Excel can serve those needs, you can learn to use it wisely.

Regulatory compliance is a given for any organization. Every business must remain compliant with local, national, and international laws. Compliance is a requirement, but it has other ripple effects. With compliance comes trust, which fosters talent retention, customer renewal, and additional sales through word-of-mouth. But when laws constantly sprout up and change, staying compliant can become a complicated and arduous process.

You collect massive amounts of data every day: streaming logs, transaction records, user interactions, and sensor data. The goal is transforming this into valuable near real-time analytics and business intelligence. But here’s the problem: most data lakes turn into data swamps where valuable insights get buried under poor organization and slow performance. Apache Iceberg and Trino provide the foundation for organized, high-performance data storage and querying.

After spending hours perfecting your BI dashboard, you export a report only to watch headers shift, page breaks split tables, and logos resize unpredictably. What should take minutes becomes hours of manual reformatting before documents meet compliance standards. This repeats daily across enterprises. Modern BI platforms optimize for responsive dashboards that adapt to screens, but operational documents require absolute precision.

If your organization relies on Informatica’s Information Lifecycle Management (ILM) for business reporting, recent announcements about the platform entering maintenance mode have likely raised important questions about your reporting strategy. Understanding what this transition means and how to protect your critical data access are essential for maintaining business continuity.

When it comes to dashboards, there are usually two schools of thought: self-service dashboards users can build themselves or finished dashboards. In our world, we call these finished dashboards managed dashboards. There is no right or wrong choice. Self-service dashboards are excellent for exploration and flexibility. Managed dashboards are just as valuable because they give users exactly what they need without forcing them to do extra work to get to the data.

Picture this: You’re a CFO presenting quarterly results to the board. A sharp-eyed member questions a major variance in your forecasting model. You’re ready, you explain that your AI system caught the anomaly early. But then comes the kicker: “How exactly did the AI reach that conclusion?” Suddenly, your confidence wavers. If your best answer is, “I’m not sure, but the algorithm is sophisticated,” you’re not alone, but you’re on thin ice.