Data Quality Scalability: Creating a Vision for Growth

How are you planning to grow data quality within your organisation? What is your strategy for scaling an enterprise data quality capability?

How are you planning to grow data quality within your organisation? What is your strategy for scaling an enterprise data quality capability?

Data Quality Scalability: Creating a Vision for Growth

by Dylan Jones, Editor

Are you creating a data quality capability that can scale? This article explores why building a data quality vision that can grow is one of the most critical skills a data quality leader possesses.


One of the benefits of running Data Quality Pro and interviewing so many experts on a weekly basis is that you start to unearth some common patterns to success that run through all data quality initiatives.

Whilst every project and programme is unique there are some key takeaways that are well worth applying as principles in future engagements.

A recurring theme in successful initiatives that we’ve featured revolves around how data quality leaders plan for the scalability of their vision.

I’ve witnessed many projects fail to create any real impact in their organisation despite having well-funded and proficient data quality teams. In other organisations I’ve witnessed very small teams have a much wider impact.

So what is the difference?

At some point data quality leaders have to recognise that their team alone cannot deliver an enterprise data quality solution, they have to build scale into their vision for data quality.

There are various resourcing tactics for data quality management but the idea that one central team can deliver a data quality service to the entire organisation is unsustainable based on the interviews I’ve undertaken. What appears to work most effectively is the ability to “federate” localised pockets of expertise that all follow a common set of processes and procedures.

Of course you still need a central team to help train and mentor leaders and data quality field workers. Central repositories for data dictionaries, data quality rules and business glossaries are also vital as are central reporting infrastructures so that data quality can be monitored across the entire organisation. However, at some point data quality leaders need to factor scale into their ambitions.

I’ve witnessed data quality leaders leveraging customer resources, business process analysts, outsourced teams and partners – whatever they can use to gain traction and scale beyond their own limited resources. My first team consisted solely of low-paid, part-time data entry workers and they soon gelled as a crack team of data quality analysts. In recent months we’ve heard from experts who have successfully delivered Enterprise Data Quality initiatives by building for growth and re-using components, technology and design patterns.

There really are no limits to who you can leverage to build out your data quality vision but you need to plan for scale because at some point your own team can’t take your vision to the next level. You have to let go and let the wider organisation develop capabilities that align to your own goals but ultimately find their own way forward.

What is your vision for growth? How are you planning to scale your data quality capability to the next level? Welcome your views.

Image credit: Photobotos (creative commons)


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