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Quality Is Not An Act, It Is A Habit

Ensuring the quality of your data isn't a one-time activity. With our help, you can adopt a rigorous approach to continuous data quality improvement that brings together people, processes and technology. Your data has never looked so good.

Rubbish In, Rubbish Out

We all know that the quality of our business decisions rests on the quality of our business data, and yet many organisations still struggle to apply effective Data Quality Management. Fortunately, we can help. Our holistic framework is built on tried and tested methods that address six key aspects of data quality.

© Thomas Leuthard

© Thomas Leuthard

1. Assessment & Planning – To target your data quality efforts, you need a clear picture of your current state. What are your baseline levels of data quality, where is the most pain being felt, and how is it impacting your business? Our Data Quality Framework answers these questions by combining a user-driven approach with sophisticated data profiling tools that collect quantitative evidence about the health of your data. The result is a data quality action plan that aligns with your true priorities.

© Jenny Downing

© Jenny Downing

2. Roles & Responsibilities – Data doesn't manage itself, so developing the right organisational components for managing data quality is one of the key contributors to success. Refined over many years, our Data Quality Framework allows us to define a set of roles and responsibilities that complement your structure and culture. Identifying the best individuals to fill those roles is equally important, so we'll go on to help you find and develop your in-house team of data champions.

© Thomas Leuthard

© Thomas Leuthard

3. Monitoring & Reporting – The routine monitoring of data quality levels is a fundamental aspect of Data Quality Management. However, when faced with the question of what to measure  the so-called "dimensions" of data quality – many organisations lack a structured approach. Thankfully, our Data Quality Framework removes the guesswork, helping you focus on the things that really matter. It's technology agnostic as well, so you're future-proofed against changes to your data quality toolset.

© Thomas Leuthard

© Thomas Leuthard

4. Improvement & Sustainability – Tackling  poor data quality isn't easy. You'll need every weapon at your disposal to win the battle against rogue data, so our Data Quality Framework combines reactive, proactive and preventative techniques to achieve continuous data quality improvement. Your data stewards will quickly appreciate the benefits of a multi-pronged approach that allows them to target their efforts more effectively than ever before.

© Thomas Leuthard

© Thomas Leuthard

5. Technology & Automation – The right tools can dramatically reduce the effort required to manage data quality. Our Data Quality Framework is designed around a number of functional capabilities, making it easy to "plug in" technology components to provide increased automation and scalability. And as independent trusted advisors at the forefront of Data Management you can rely on us to guide you through the technology maze, so your investment in data quality isn't left to chance.

© D. Sharon Pruitt

© D. Sharon Pruitt

6. Training & Education – Creating a culture where everyone understands the importance of data can make a huge difference to your data quality efforts. Our Data Quality Framework includes a number of educational components ranging from high-level briefings for senior management to an intensive two-day course aimed at those tasked with implementing your data quality capabilities. People may be the cause of many data quality issues, but if you educate them they'll also be your most effective weapon.

If you want to avoid being held back by the quality of your datacome and talk to us – you'll appreciate our no-nonsense approach. Data Quality Management is littered with myths and misconceptions so take a look at our top ten by downloading the free myth-buster below.