Data Quality: Cash Drain or Cash Gain?

Solving data quality problems requires investment, and it’s an investment no business can avoid. Poor data quality can lead to compliance issues, legal challenges and increased effort from all sides. Over time, as data (or the information derived from it) decays, inefficiency and inaccuracy becomes a serious issue that can hamper progress throughout the organisation. Customers also have higher expectations and feel more empowered to complain if they don’t feel their data is being handled correctly. According to a 2009 Gartner study, businesses estimated that they are losing an average of $8.2 million per year because of poor data quality. Five years on, we are storing, managing and relying on more data than ever before. It’s more important than ever to mitigate the risk of poor data quality by investing in solutions that work. Fearing Investment Thousands of businesses are now facing up to their responsibilities and investing in data quality software. They must also meet the costs associated with out […]
By |October 22nd, 2014|Blog, Data Quality|Comments Off

Data Quality Terms Defined

After 20 years developing data quality solutions, the team at DQ Global are very familiar with data quality terminology. However, many customers tell us that data quality terms can be confusing. What is the difference between enrichment and enhancement? And why do we cross match or automate in our quest for clean data? In this article, we’ll define some of the terminology we use on a daily basis to describe our data quality solutions. Deduplication and Cross Matching: What’s the Difference? ‘Deduplication’ and ‘cross matching’ are often used in the same sentence, particularly in reference to DQ Global’s Match software. But they are not the same thing: they complement each other. Our Match application is technically a deduplication tool in that it locates duplicate records in a database or an application. Match applies various methods to deal with those duplicates. It may suppress a duplicate record, merge it with another record, or flag it up for manual review. Cross matching is slightly different. In medicine, you will hear the term used to […]
By |October 14th, 2014|Blog, Data, Data Quality|Comments Off

Our 9 Ways Data Bureau Services Make Data Cleansing Easy

Data bureau services are data cleansing services that improve business datasets. These services cover all of the processes needed to make data fit for purpose: cleansing, deduplicating, matching and more. Regardless of how your data is used, cleansing is always at the centre of a data quality drive. With data bureau services, we can process data and enhance your data, applying our expert knowledge in data quality to ensure flawless outputs. Bureau Services or Data Quality Software? So how are bureau services different to data quality software? In short, the service and the product are aimed at slightly different customers. While some of our customers want to have full hands-on control of the way their data is cleansed, others use data bureau service as a more affordable and practical option. Depending on the size of your organisation and the size of your data warehouse, either option will work for you. Data quality software is still a great way to invest in long-term, […]
By |October 7th, 2014|Blog, Data Cleansing, Data Services|Comments Off

The Longer You Delay, the More the Data Decay

According to research, between 50 and 75 percent of the success of a B2B marketing campaign is down to the accuracy of the data available. Businesses also rely increasingly on Customer Relationship Management (CRM) systems – software that retains every lead, every sales opportunity and every contact record. But software is only as useful as the data it contains, and good quality, up to date information is the key. Businesses invest thousands of pounds in obtaining leads that allow them to generate profit. But what happens a year later, when it’s time to sell something new? This statistic from Target Margeting Mag, from a 2001 study, proves the scale of the problem: 70.8 percent of business people surveyed had at least one change to their contact record in 12 months. The breakdown of change was: Job or title change: 65.8 percent Phone number change: 42.9 percent Email address change: 37.3 percent Change of company name: 34.2 percent Move from one company to another: 29.6 percent Change of name: 3.8 percent Bear in mind that this […]
By |September 30th, 2014|Blog, Data, Data Quality|Comments Off

Is Open Data At Risk From Poor Data Quality?

Open data is a concept that’s new to many people in the UK. The idea is fairly straightforward. By opening up records used by the public sector, the British public can see how their data is being used. The idea was introduced by the coalition government in May 2010, but has yet to gain traction, and the British public have not yet had the opportunity to scrutinise government spending. In theory, open data should make the public sector more efficient and effective, and it should give British citizens more confidence in the way their tax money is being spent. Local governments are supposed to publish records for all spending over £500, and we should all be able to see figures on crime, civil servant salaries and government contracts. But in order to inspire confidence, people need to see two things. They must know that data is being published in the manner it should be published, and they need to know that data is accurate. According to the press, data quality is becoming a serious risk that could derail the open […]
By |September 16th, 2014|Blog, Data Quality|Comments Off

Is Customer Data Integration vital to business success?

In today’s economy, it is imperative to put the customer at the heart of the business; treating each customer as an individual to maximise lifetime value, coupled with the ability to personalise mailings or to send lifestyle information to the right person at the right time is vital to business success. When you consider that the average business never hears from more than 90% of its unhappy customers, the importance of putting the customer at the heart of the business becomes even more apparent. Customer Data Integration (CDI), or the process of consolidating and managing customer information from all available sources, if properly carried out, ensures that all relevant departments in the organisation have access to the most current and complete view of customer information. Most companies have customer data, possibly in disparate database containers which makes it difficult to manage effectively, resulting in out of date and conflicting customer data.  Although most companies believe having an integrated view of customer data is critical, only a very small percentage of companies actually manage to achieve this. The inability to consolidate […]
By |September 10th, 2014|Blog, Data Management, Data Quality|Comments Off

Is There Such a Thing as Too Much Data?

We live in an age where all businesses are generating data, and harvesting data at the same time. The flow of information, and the speed that it is created, have led to the age of Big Data – where massive amounts of ones and zeros are created, transmitted and stored. Every day, another huge chunk of data is broadcast for the consumption of anyone who wants to access it. The Internet of Things (IoT) is one big contributor to data generation. Machines are increasingly being equipped with sensors and can report back their state continuously, across the factory or across the globe. Thousands of these sensors can be remotely monitored, making traditional machinery more connected, and more visible to the managers who have invested in it. And data is being harvested at incredible speed. Most websites are hooked up to Google Analytics, Google’s website statistics package; this retains data for at least 25 months (although some users report seeing older data) on every website it monitors. Google also collects […]
By |September 2nd, 2014|Blog, Data|Comments Off

I was a duplicate Record!

As a point of contact for Recruitment agencies at our company, I regularly receive telephone calls from them promoting their services. This week I received a telephone call from a large online recruitment agency. As the caller started “his script” it felt very familiar and I very quickly realised that I had received the very same telephone call from this company a week ago. I listened politely to what he had to say and then I explained to him that we did not require his services at the moment and pointed out to him that I had been called last week by someone from his company. He assured me that from my records I was last called in June. I was 100% certain that I received a call from this agency last week. He finally admitted (quietly) that there was probably a duplicate record of me on their system! This situation was embarrassing for the caller and an interruption and annoyance to me. Last week, as a company we also received a letter from a large supplier informing us that they were changing their system […]
By |August 26th, 2014|Blog, Data, Data Quality|Comments Off

7 Stops on the Route to Data Quality

The road to quality data can seem like a long, difficult journey. But it’s one that every business eventually needs to make. As data ages, the business becomes less efficient; it’s not possible to maintain operational efficiency if you can’t make robust decisions. Like many tasks, data quality is best viewed as a long-term concern, and something that will be tackled in controlled phases. We’ve split the journey into seven distinct parts. Each one is a stop you’ll make on the way.   1. Get Out Of the Pit When tackling a data quality problem, taking the first step is often the most important part of the process. With a long, difficult challenge ahead, it can be surprisingly difficult to get the wheels in motion. To make progress with any problem, we have to recognise it and stop denying its existence. Own up. The organisation has a data quality problem; it’s not impossible to fix. Most – perhaps all – businesses will eventually find themselves in […]

Improve Data Quality by Playing as a Team

Data warehouses are key to the way modern businesses make decisions. The data warehouse is the hub of business intelligence. A data warehouse is essentially a repository where data is stored, organised, categorised and integrated into various systems. Data warehouses receive data from many sources. According to industry research, 95 per cent of Fortune 500 companies use data warehousing, or are planning to develop a data warehouse. However, potential failure rates are high – between 50 per cent and 90 per cent. Understanding failure is key in preventing negative outcomes. Why Data Quality Matters According to the International Journal of Latest Trends in Computing, there are 20 factors affecting the success off data warehousing projects. Reasons include poor data quality, the failure of management to recognise the benefits of data warehousing, and a knowledge gap between researchers and practitioners that prevents meaningful progress. Ted Friedman, one of Gartner’s key analysts, said “Consistency and accuracy of data is critical to success with business intelligence, […]