The Billion Dollar (Data Integration) Mistake
How would you like to wake up to an extra billion dollars, or maybe nine, in the bank? This has happened to a teacher in India. He discovered to his astonishment a balance of $9.8 billion in his bank account!
How would you like to be the bank who gave the client an extra nine Billion dollars? Oh, to be a fly on the wall when the IT department got that call. How do you even begin to explain? Imagine the scrambling to track down the source of the data error.
This was a glaringly obvious error, which is easily caught. But there is potential for many smaller data errors. These errors may go undetected and add up hurting your bottom line. How could this type of data glitch happen? More importantly, how can you protect your organization from these types of errors in your data?
A primary source of data mistakes is insufficient testing during Data Integration. Any change or movement of data harbors risk to its integrity. Unfortunately there are often insufficient IT resources to adequately validate the data. Some organizations validate the data manually. This is a lengthy, unreliable process, fraught with data errors. Furthermore manual testing does not scale well to large data volumes or complex data changes. So the validation is often incomplete. Finally some organizations simply lack the resources to conduct any level of data validation altogether.
Many of our customers have been able to successfully address this issue via automated data validation testing. (Also known as DVO). In a recent TechValidate survey, Informatica customers have told us that they:
- Reduce costs associated with data testing.
- Reduce time associated with data testing.
- Increase IT productivity.
- Increase the business trust in the data.
Customers tell us some of the biggest potential costs relate to damage control which occurs when something goes wrong with their data. The tale above, of our fortunate man and not so fortunate bank, can be one example. Bad data can hurt a company’s reputation and lead to untold losses in market-share and customer goodwill. In today’s highly regulated industries, such as healthcare and financial services, consequences of incorrect data can be severe. This can include heavy fines or worse.
Using automated data validation testing allows customers to save on ongoing testing costs and deliver reliable data. Just as important, it prevents pricey data errors, which require costly and time-consuming damage control. It is no wonder many of our customers tell us they are able to recoup their investment in less than 12 months!
TechValidate survey shows us that customers are using data validation testing in a number of common use cases including:
- Regression (Unit) testing
- Application migration or consolidation
- Software upgrades (Applications, databases, PowerCenter)
- Production reconciliation
One of the most beneficial use cases for data validation testing has been for application migration and consolidation. Many SAP migration projects undertaken by our customers have greatly benefited from automated data validation testing. Application migration or consolidation projects are typically large and risky. A Bloor Research study has shown 38% of data migration projects fail, incurring overages or are aborted altogether. According to a Harvard Business Review article, 1 in 6 large IT projects run 200% over budget. Poor data management is one of the leading pitfalls in these types of projects. However, according to Bloor Research, Informatica’ s data validation testing is a capability they have not seen elsewhere in the industry.
A particularly interesting example of above use case is in the case of M&A situation. The merged company is required to deliver ‘day-1 reporting’. However FTC regulations forbid the separate entities from seeing each other’s data prior to the merger. What a predicament! The automated nature of data validation testing, (Automatically deploying preconfigured rules on large data-sets) enables our customers to prepare for successful day-1 reporting under these harsh conditions.
And what about you? What are the costs to your business for potentially delivering incorrect, incomplete or missing data? To learn more about how you can provide the right data on time, every time, please visit www.datavalidation.me