Using Live Data in Database Development Work

Posted by Phil Factor on Simple Talk See other posts from Simple Talk or by Phil Factor
Published on Fri, 10 Jun 2011 12:29:00 GMT Indexed on 2011/06/20 16:34 UTC
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Guest Editorial for Simple-Talk Newsletter

... in which Phil Factor reacts with some exasperation when coming across a report that a majority of companies were still using financial and personal data for both developing and testing database applications.

If you routinely test your development work using real production data that contains personal or financial information, you are probably being irresponsible, and at worst, risking a heavy financial penalty for your company. Surprisingly, over 80% of financial companies still do this. Plenty of data breaches and fraud have happened from the use of real data for testing, and a data breach is a nightmare for any organisation that suffers one. The cost of each data breach averages out at around $7.2 million in the US in notification, escalation, credit monitoring, fines, litigation, legal costs, and lost business due to customer churn, £1.9 million in the UK. 70% of data breaches are done from within the organisation.

Real data can be exploited in a number of ways for malicious or criminal purposes. It isn't just the obvious use of items such as name and address, date of birth, social security number, and credit card and bank account numbers: Data can be exploited in many subtle ways, so there are excellent reasons to ensure that a high priority is given to the detection and prevention of any data breaches. You'll never successfully guess all the ways that real data can be exploited maliciously, or the ease with which it can be accessed.

It would be silly to argue that developers never need access to a copy of the database containing live data. Developers sometimes need to track a bug that can only be replicated on the data from the live database. However, it has to be done in a very restrictive harness. The law makes no distinction between development and production databases when a data breach occurs, so the data has to be held with all appropriate security measures in place. In Europe, the use of personal data for testing requires the explicit consent of the people whose data is being held. There are federal standards such as GLBA, PCI DSS and HIPAA, and most US States have privacy legislation. The task of ensuring compliance and tight security in such circumstances is an expensive and time-consuming overhead. The developer is likely to suffer investigation if a data breach occurs, even if the company manages to stay in business.

Ironically, the use of copies of live data isn't usually the most effective way to develop or test your data. Data is usually time-specific and isn't usually current by the time it is used for testing, Existing data doesn't help much for new functionality, and every time the data is refreshed from production, any test data is likely to be overwritten. Also, it is not always going to test all the 'edge' conditions that are likely to flush out bugs. You still have the task of simulating the dynamics of actual usage of the database, and here you have no alternative to creating 'spoofed' data.

Because of the complexities of relational data, It used to be that there was no realistic alternative to developing and testing with live data. However, this is no longer the case. Real data can be obfuscated, or it can be created entirely from scratch. The latter process used to be impractical, now that there are plenty of third-party tools to choose from. The process of obfuscation isn't risk free. The process must access the live data, and the success of the obfuscation process has to be carefully monitored.

Database data security isn't an exciting topic to you or I, but to a hacker it can be an all-consuming obsession, especially if there is financial or political gain involved. This is not the sort of adversary one would wish for and it is far better to accept, and work with, security restrictions that exist for using live data in database development work, especially when the tools exist to create large realistic database test data that can be better for several aspects of testing.

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