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.

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.

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.

Martin Doyle is a Data Quality Improvement Evangelist and the CEO of DQ Global, which is a UK-based data quality software and services vendor providing data cleansing, international address and email verification, data deduplication, and data matching solutions for Customer Relationship Management, Single Customer View, and Master Data Management. DQ Global has worked with over 500 businesses worldwide on a variety of projects, providing their clients with improved data quality, making their data fit for business use, and enabling them to trust their data and make decisions based on a foundation of fact.

Listen to the full interview here:

http://www.ocdqblog.com/home/the-johari-window-of-data-quality.html

Good content is data which is fit for purpose.  It should be:

As we move into 2012, businesses that capitalise on their data, create single customers views and master their enterprise data will have a distinct advantage over their competition. They will survive and thrive, whilst those who don’t will be at a severe disadvantage and could become extinct.

In an ideal world we would have a universal product naming convention.  In practice this rarely happens and it's possible for different users in the same organisation to give different names to the same product.

Alongside our exemplary service and value for money DQ Global's primary unique selling points (USP's) are founded in our technology and data quality improvement processes. It's what we do and the way we do it that makes us different.

Data Deduplication is the removal of unwanted records from a file or database; cross matching is the process of comparing one database against another to identify relationships which lead to accurate data integration/migration and construction of a single customer view.

According to a Gartner Group report, bad data is the main reason that CRM projects fail; poor data quality compromises an organisation's investment in CRM and undermines customer relationships. So perhaps bureau offerings are not working?

Well, the first problem is the definition of "Single Customer View" (SCV). In my opinion an active SCV certainly shouldn't be considered a service, it's a capability underpinned and delivered by technology.

A true SCV should be dynamic, so as any piece of data changes anywhere the business can see all data linked to the single customer instance they are interested in.

What bureau appear to be selling is simply a deduped and merged file, which they are now labeling a single customer view; this is not a living and breathing representation of the data. It's more akin to a company's audited accounts which are only true at one specific point in time.

Furthermore, this typically only delivers name and address data, leaving important linked transactional data, product information, contact history etc. out of the equation.

Technical Support Engineer

Job Description

DQ Global is a leading provider of Data and Information Quality improvement software products to over 500 companies worldwide.

We are looking for a versatile IT generalist to manage a varied set of tasks that encompass the following:

• Sales and customer support for existing and future software applications.
• Bureau work requiring database application development and data processing.
• Customer training and product presentations.
• Documentation of products and training
• Data Curation and Digital Asset Management
• Software testing for new DQ 360 product
• Product evangelist and guru

This role will have many customer facing elements so candidate must be comfortable interacting with clients often in a pressurised environment.

Desired Skills & Experience

An appreciation of data quality issues and solutions would be highly advantageous. The applicant must be able to demonstrate the following technical skills:

• Infrastructure support – Windows Small Business Server & network
• Good general Database technology knowledge with Administration skills
• Must be expert with SQL Server 2005 / 2008 / R2 and SQL SSIS
• Windows 7 domain administration including Exchange and Microsoft CRM
• Good up to date T-SQL skills
• Working knowledge of JavaScript
• PowerShell scripting would be advantageous
• Good working knowledge of MS Access & MS Excel
• Any VB 6 or .NET development skills would be welcome

The applicant must be capable of working under pressure and must have the ability to learn new skills on a regular basis. Recruiting

Company Description

We work with organisations who care about data quality, companies who want to recover the 5% to 10% of revenue unnecessarily wasted which could otherwise be going directly to the bottom line.

Our clients typically want to obtain a Single Customer View or benefit from a Master Data Management capability.

Uncorrected data defects lead to wasted time and money as well as bad decisions; all of which directly impact the bottom line, which could otherwise be bolstered by 10% or more.

Our products and services identify and rectify and prevent data defects. They allow organisations to finally trust their data and make decisions based on a foundation of fact.

Additional Information

Type: Full-time,   Experience: Mid-Senior level,   Compensation: Dependant on skills and experience