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Your portal to the latest insights, resources and guidance, in the field of Data Quality, Data Governance and MDM.
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The Data Quality Pro Blog
Latest insights from our expert blog…
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In this post, we share a short video that gives you and your team some simple rules to follow for achieving greater traction, particularly amongst your senior management.
Did you know that over on LinkedIn we have a popular group called the Data Quality and Data Governance Professionals Forum?
With over 7,500 members, 100’s of topics discussed, and many years of excellent community engagement - it will give you a headstart on some of those thorny data quality or data governance questions you’ve been wrestling with.
Why not check out some of the most popular discussions below, or submit your own question into the group?
Managing change is critical to a data quality project. You need to take the organisation with you and above all, this means getting the business onside.
How do you create a library of data quality rules that can be shared for the common good of your organisation. Read on to find out…
Initiatives like BCBS239 are a great starting point for making Data Governance operational and getting some core processes 'baked in' to the organisation. In this post, I interview Taher Borsadwala, to learn more about his experience of implementing and operationalising BCBS239.
Understanding how data flows around your business to deliver value to your internal and external customers is critical to effective data quality management. In this article we take a look at some simple techniques required to deliver effective information chain management.
Data Quality Scorecards are one of the most vital resources for guiding your team and motivating your project sponsors towards the goal of data quality management.
But how do you go about creating a data quality scorecard and what are some of the key points to consider?
Here are 23 pointers to set you in the right direction.
In this article you will learn how to create a data quality business case that convinces sponsors of the benefits of your data quality efforts and the value of supporting your approach.
In this article, data governance expert Mirjam Visscher provides details of how to improve your business definitions using a Definition Quality Indicator process.
Without a clear definition, you will struggle to communicate the benefit and value that your initiatives bring. Use this guide as a compendium of ideas to formulate your own company definition for the meaning of Data Governance.
This article explores why building a data quality vision that can grow is one of the most critical skills a data quality leader possesses.
To help you kick-start your data quality initiative we’ve highlighted some existing data quality frameworks and data quality methodologies that are available both online and offline.
Creating a Data Quality KPI (Key Performance Indicator) is a critcal step in measuring, monitoring and controlling the impact of poor quality data in any organisation.
In this post, we respond to a request for help from one of our community members struggling to create Data Quality KPI’s:
A poorly designed data model can cause major data quality issues when the final information system is launched. In the second part of his expert modelling series, John Owens provides another detailed tutorial that explains the core techniques of effective data structure modelling as found in his Integrated Modelling Method (IMM).
Our aim with this tutorial series is to help our readers learn some of the key modelling skills that are typically required for data quality improvement.
What is a data quality policy and what are the key sections?
Who should create it and how is it executed?
There are many questions posed when creating a data quality policy for your organisation. Use this article as a guide to getting started and creating a data quality policy that is right for your organisation.
If you’re working as a data analyst perhaps it’s time to shift your focus to data quality analyst roles to help increase your career potential? If that’s something you’ve considered then the next question you’ll pose is what additional skills will I need? Fortunately you’ll find that many of your data analyst skills are exactly what companies are searching for in a data quality analyst.
Master Data Management (MDM) has rapidly become one of the most in-demand skills within the data management industry.
One of the core skills that practitioners require to deliver MDM is the ability to construct and manage a variety of data and functional models.
John Owens provides Business Systems Modelling advice from his Integrated Modelling Method
In this interview, highly experienced Data Quality author and practitioner, Laura Sebastian-Coleman, provides a detailed account of her experiences in launching and growing a Data Quality Centre of Excellence (CoE) in a large organisation.
How do you get started with identifying the true causes of Data Quality Root-Cause issues?
This article examines 10 techniques that are proven to help you get to the heart of your data quality issues and move from a reactive to proactive and longer-term defect elimination.
In this paper, Sundara and Sankara provide a practical guide for implementing data quality as a service via a cloud based architecture.
Easily one of the single biggest causes of data defects in any organisation is poor quality information entered at the start of the information chain via data entry interfaces.
This article provides some simple, practical and cheap techniques to dramatically improve the data quality of human entered information.
With her extensive experience in leading Data Quality and Governance initiatives in different domains, Purvi Ramchandani describes ten situations when Data Quality and Data Governance initiatives have a higher probability of failure.
What should a Data Governance Manager do in their first 6 months?
Find out how to plan your DG activities with Nicola Askham, ‘The Data Governance Coach’
During this webinar recording, experienced Data Quality practitioner James Phare of UK based Data to Value demonstrates how a Lean approach leveraging Data Prototyping can be used to simultaneously address Data Quality issues whilst progressing wider project requirements.
In this video tutorial by Dylan Jones, editor of Data Quality Pro, we learn of an effective data quality assessment strategy that was able to create high impact ‘data quality stories’ often within one day.
Data Profiling vs Data Quality Assessment - what’s the difference?
A common problem we see in data management circles is the confusion around what is meant by data profiling as opposed to data quality assessment.
How do you create traction with data governance and data quality when your organisation is wary of these initiatives due to past historical projects that didn’t live up to expectations?
How do you prevent poor levels of supplier data quality impacting your organisation?
The answer? Through the adoption of a Data Quality Firewall and ongoing Data Quality SLA process.
This post creates a blueprint for creating your own Data Quality Firewall and ensuring your data quality SLA provides certified, high quality data throughout your organisation.