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Quality Assurance: Implementation

This page takes the reader through the three phases of submission in terms of the QA input, processes and output. It should be read with Quality Assurance: approach which is the logical flow of how data is proposed to be collected, integrated and output and the data journeys which pictorially chart these data journeys.

What does QA look like for in-year collection?

It should be clear that the quality assurance (QA) approach for in-year collection will differ from the current approach.

However, it shares some of the validation reporting and many of the principles. This section explains the difference between the current submit once model and the in-year model.

The key tenets of in-year QA are:

  • Data quality assurance (QA) will continue to be a priority for data submitted to HESA as described in detail in QA: Approach
  • There will be better visualisation of data to help HE providers check their data quality.
  • Data validation will occur at various stages and be supported by an enhanced experience in terms of operational and management information.
  • The data quality assurance procedure will be less complicated, as the data submitted by the HE provider should be similar to that used by the provider themselves and at the time they are using it.
  • The requirements and schedule of onward outputs will determine when and what data must have been submitted, integrated, quality assured and signed-off.

This first diagram is a composite of the three distinct QA steps. These are 'Input QA: how to submit data into the schema', 'Integration QA: how data is brought together' and 'Output QA: transforming the submitted data into statutory and other outputs for the provider to review before being sent on to the data customers'.

The submissions are expected to be returned close to the events. As more data is submitted in line with these events, more integration will be performed, richer QA feedback will be available and fitness for purpose for outputs will improve.

In the remainder of this section, each of these QA steps will be explained in more detail.

Input QA

This diagram shows the first of the three QA processes - how data is submitted and an example of what rules would be run.


Integration QA

Now the data is integrated with data from previous submissions and - if applicable - previous years. 


Output QA

Now sufficient data has been submitted at an acceptable level of quality to be formatted for one or more outputs. This is where the provider will receive these outputs in either raw or summarised form, before releasing to the data customers.