You wouldn't allow your children to get away with telling untruths to their family or friends, would you? And you certainly wouldn't let anyone else do so. But if you let data become and remain unclean, it will certainly be spouting nonsense to the rest of the company.

When British Gas was privatised at the end of 1986, the public was offered a limited number of shares per person. Unscrupulous individuals who saw the chance to earn a fast buck tried to fool the offering's auditors and get more than they should by using variations of their names and other personal details. For the first time, the artificial intelligence of fuzzy matching was used successfully to catch out the fraudsters. Now it has many more uses and is one of the common tools in master data management.

A report on a recent business survey found that, on average, out of every £6 spent out of their budget, departments wasted £1 because of poor data quality. Business people are aware that having clean data that gives accurate information helps them swim away from their competitors, but many still struggle to keep their heads above water rather than invest in data quality solutions.

It's no good doing things by halves if you want data quality. When you've done a data profiling exercise, you know where your data problems lie. That's half the exercise. Next you have to sort them out and deal with what might have a detrimental effect on the business. Change the metadata that doesn't match the data, and use data quality software to make sure the data is verified, complete and unique, with no duplicates.

Just as a horse has to be in tip top condition to win its race, so does your data need to be of really good quality to beat the competition. But managing the condition of your data is not as costly as maintaining a fit and healthy race horse. Data scrubbing - being able to remove duplicate records, maintain integrity and consistency - can all be achieved without having a massive weekly bill on top of an initial investment.

Is there anyone out there who doesn't want clean data? If so, you're in luck. Here is the definitive checklist of things NOT to do.

Like solving riddles? This one should be easy for any IT specialist familiar with this website. We are all about data quality, which comes from clean data; and clean data means fewer records because all the duplicates have been weeded out.

Would you put toxic fuel in your car and still expect it to take you wherever you want to go? It won't happen, will it? Toxic data is the same; a business running on toxic data simply can't perform.

So why keep on putting toxic data into the analysis engines and expect world beating results? It's not difficult to clean data before you use it. All you need are the right tools – a one off investment that could make all the difference.

Sometimes IT managers feel they could be losing the joust in trying to get the clean data message across. Everyone is so focused on their own aspects of winning the competitive edge, they don't see or understand that faulty tools could be undermining their efforts. Or if they do, it's why can't IT get it right for a change, or we've already invested in all these information systems, why do we need to spend even more money?

Big data is here, and it's getting bigger by the second. It is bringing significant challenges as well as opportunities. The horizons of master data management are changing at record speed.

How loyal are your customers? Do your senior managers know? Can you measure this? If your data gives you a single customer view you can see at a glance how much repeat business you are getting, and what is attracting the most loyal customers.

All businesses need to be able to adapt to market demand. Many astute business leaders seem to have an instinct for what is going to work well and what direction to take next. That's the way it appears to outsiders, but the truth is that their gut feel has most likely evolved from the accurate information from clean data available for them to study.

Sometimes, no matter how much hard work IT is putting in on data scrubbing andusing data quality software, you keep getting complaints that what's coming up in reports is not helpful. Unless everyone who touches data has a good understanding of how it is used to support the business activities, and how vital it is to get it right, things will continue to go wrong.

Got a direct mail campaign coming up? The marketers have prepared an excellent mailing with an eye-catching design, a tempting offer, a powerful call to action and prominent contact details. Everything is lined up to handle the responses and the business is holding its breath for an onslaught of interest.

But even with all this in hand, bad list preparation can virtually kill the campaign, waste the marketing budget and cause lasting damage to the reputation of the business. A bad mailing list that hasn't been checked by data cleansing software can even take you outside the law and result in costly fines.

A data matching project has uncovered more than 5,000 ineligible immigrants receiving benefits in the UK. Since the government undertook this exercise of using matching software on benefits, tax and border control data for the first time recently, it has released figures stating that that around 371,000 benefit claimants were non-UK nationals when they applied for a National Insurance number.

The Hidden Dangers of Defective Data

The surface dangers of bad data are obvious: it renders mailings a waste of time and money, can cause reputation damage and seriously interfere with customer relationships.

But there are other dangers lurking beneath the surface that could bite harshly into your bottom line and deliver false information that lures you into making business decisions that are financially damaging.