5 Top Tips for Effective L&D Data Requirements

A learning ecosystem can quickly grow and evolve into a complex web of unique tools and technologies serving specific needs. So inevitably, gaining meaningful L&D insights from these disparate systems can be difficult.

The good news is that your learning analytics platform can bring all that L&D data together so you can track and explore all your learning in one place. But first, you’ll need to ensure you’re getting all the data you need and that it’s in the proper format. This blog post covers data requirements for different systems and the questions you should be asking your vendors.

L&D data requirements for learning analytics

Throughout this blog series, we’ve outlined some key principles of data integration and explored system requirements, opportunities, and quirks in many of the platforms that make up your learning ecosystem.

So whether you’re working on an integration with an existing platform, writing an RFP, or discussing learning solutions with a vendor, you’ll be able to ask the right data requirement questions for:

5 top tips for L&D data requirements

We want to leave you with some parting words of wisdom as we wrap up this series, so here are our top five tips for successful data integrations:

  1. Discuss your L&D data requirements with your vendors. It’s important to make sure that your vendors understand your needs and that everyone has a clear and well-documented plan for integration from the start.
  2. Base your data requirements on reporting requirements. Don’t just pick the data you think would be nice to have. Take time to think about what reporting you and your stakeholders will need and define your requirements to support those needs.
  3. Review the documentation with your techies. It’s not uncommon for misunderstandings to arise about integration functionality when talking to non-technical salespeople. So when speaking with vendors, discuss what functionality they have to extract data. Get a copy of their documentation for your technical team or your learning analytics platform (LAP) vendor’s technical team to review.
  4. Use xAPI where possible, but CSVs exported via API are a good plan B. Ideally, choose products with xAPI support, but a product with CSV data export functionality can also work well. Be aware that not all xAPI implementations are good—or even usable—so be sure you know the details of the xAPI tracking before assuming it will meet your requirements.
  5. Consider ongoing maintenance. If a vendor is developing integration functionality for you or does not have existing clients using that functionality, make sure you discuss ongoing integration maintenance. Ensure your contract requires the vendor to maintain your integration, and talk with the vendor about how tracking for any future product features will be implemented.

Keep your data tidy with xAPI Governance.

If you’ve found this series helpful, you might also enjoy our xAPI Governance guide. It talks about how to set up processes and procedures to ensure the quality and compatibility of your data as you bring it all together from various sources.

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How clean is your learning data?

Good reporting stands on the foundation of good data. So if the underlying data is missing, inaccurate, or misleading, that reporting isn’t going to be useful. That’s why having an xAPI data governance strategy is critical for success.

This handy guide covers everything you need to know about creating your own strategy—including best practices, helpful tools, and technology for cleaning up and maintaining good data.

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