There is that old joke about a guy lost in the countryside who stops and asks for directions only to be told: “If I were you, I wouldn’t start from here.”

I thought about that baffling wisdom during a conversation about the use of production data in testing and development. If you were to ask why copies are used, what answers do you think you‘ll hear?

In the main, I’m guessing it will be because that’s the way it has always been done. Sure, but dig further and underpinning the ‘why’ is belief that it is the best way to ensure quality in systems testing. So the challenge comes when you’re told that it simply isn’t true.

Yes, production data is just the starting point and manual methods are then used to edit and extract relevant data but do conventional methods meet project objectives? Put aside for a second the need to mask sensitive live data and look again at the issue of quality.

Undoubtedly, quality data is the key to success but a copy of production data does not guarantee that – all it guarantees is high volume.

Manual techniques can enhance test data but not to any significant degree. Even automation tools such as QTP and LoadRunner improve richness but only to a certain extent and the risk is that defects and bugs remain undetected.

So working with the ‘if I were you, I wouldn’t start from here’ logic, projects should start with low volume data that offers a rich combination of scenarios.

And what is the quickest, most cost effective and timely way to achieve that? With software that is capable of creating data – (no more fears over live data leaks) – and that generates a richer coverage of characteristics that will deliver the functionality that you and your team have been tasked with. True or false?