You open a website. The data you need is right there, laid out in rows, clearly labeled, exactly what your project requires. Then you realize you have to get it out of the page and into a spreadsheet, and that is where things stop being simple. Copying row by row is not realistic if there are hundreds of results. Building a scraper requires knowing how the site is structured in code. Hiring someone to do it takes time and budget you may not have. And if the site updates its l

Every piece of data you have ever needed from a website was already sitting there, visible on the screen. The problem was never access. It was format. Web pages are built to be read by humans, not processed by spreadsheets. The information is real, it is current, and it is public. But it lives inside a visual layout designed for a browser, not inside the rows and columns your analysis needs. That gap between what you can see and what you can actually use is where most data co

The NC.gov grant opportunities page lists every active state grant program in one place, organized by category. Getting that data into a spreadsheet manually means copying row by row across dozens of programs. With the Minexa.ai Chrome extension, the whole page becomes a structured dataset in a few minutes. Here is exactly what the process looks like, step by step. What data you get Each row on the NC.gov grant opportunities page contains four fields Minexa extracts cleanly: