How can I normalize user-uploaded datasets for our SaaS?

One thing I noticed is that you didn't mention the database type or the kind of data you're trying to normalize. It usually falls on data entry to tackle this mess—whether that’s asking users to fix their datasets or insisting they follow a specific format. Implementing a template might save you a ton of hassle in the long run. I mean, you could theoretically use AI for some adjustments, but it isn't a magic solution. Just something to consider!

Focus on defining which file formats your system will accept. You could go down the XML route and use libraries to parse those or simply stick with CSV files. Once you make that decision, you can provide templates and clear guidelines to users for creating their import files. Don’t overcomplicate things trying to predict every scenario, just set clear parameters to keep things manageable!

Before you focus on efficiency, try to ensure that the system actually works with various file types. Are the datasets coming in as plain text, XML, JSON, or Excel? You'll need to distinguish these formats first. My advice is to account for how different users could structure their files. If a specific attribute, like 'Genre', always appears in a particular column, then accommodate for that flexibility. Understanding the file size and frequency of uploads will also guide how you approach this. Ultimately, if users can’t upload standard templates, it might take time and resources to develop a workaround, which may lead them to just stick with your templates instead.

I see you're dealing with XLSX and CSV files, which helps narrow it down! It might be best to ask users to use specific headers in their files so that you can easily manage any column order issues. This way, you can streamline the import process on your end.