What is data integrity?
Data integrity refers to the accuracy, validity, and completeness of data throughout its lifecycle. Data might lose integrity and become compromised through replication, alteration, or data loss. Anything which has the potential to change data after the fact could result in its being compromised. Data might even be compromised from the point of collection, through inappropriate collection methods and techniques, or source selection.
How do you ensure data integrity?
1. Background research
This is a given. you need to know your subject to have any chance of identifying things that look out of place. General reading around a topic and comparison with other, existing data sources can help give you an idea of what to expect, as well as highlight deviations and anomalies.
2. Really developing a partnership with the client
They will have the background data, sector sales data and more. Don’t bank on it being volunteered, but you can bet your bottom dollar it’ll surface if the research data doesn’t meet their expectations. To this end, making sure you really become an extension of your clients’ internal teams and becoming intimately familiar with their business and what they do can help give you a ‘sixth sense’ when it comes to understanding their data, especially when it might be compromised.
3. Press them for information
Following on from the previous point, don’t always expect useful information to be immediately provided. Press them for what you need. In the same way you might tell a client specifically and unequivocally what information and resources you need when briefing for a creative project, tell them what you need when briefing for data collection projects. See what results they’re expecting & don’t be afraid to question how well-founded this is. Ask for previous results, the context of these results and the methodologies used.