Category Archive: Data quality

Data quality

Data quality a priority for 2024

Despite the hype surrounding generative Artificial Intelligence (GenAI), I am finding in my industry reading that many industry analysts are predicting that data quality (one of my favourite topics) will remain a key priority for this year – especially when it comes to data management and governance.

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The uniqueness of modern data quality management

Last month I addressed how data quality is perceived by different specialists inside the organisation. This month, I turn the spotlight onto what makes modern data quality management different from traditional approaches. Edwin Walker’s Data Science Central article ‘Difference between modern and traditional data quality’ provides an excellent starting point.

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Data quality is in the eye of the beholder

The quality of the data we work with has a significant impact on the quality of the insights we can extrapolate for the business. Following on from my recent mini-series on the evolving data-related roles, it was interesting to come across Edwin Walker’s article on Data Science Central titled: ‘How do different personas in an …

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Examining the continually evolving data-related roles

In my quest to continuously learn more about data-related roles, I have recently come across two very interesting articles that suggest that data-related roles will be changing throughout the remainder of the year. These pieces share some great insight, and I couldn’t resist the opportunity to share my additional views and so in this, the …

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Understanding the causes and risks of data waste

In recent years, there has been a significant focus on individuals and organisations to reduce waste in support of global climate change and environmentally conscious efforts. In my blog post this month, I turn the spotlight on a different sort of waste. This is something which every business around the world struggles with – data …

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Understanding the essential KPIs for data and analytics

To be successful, any organisation must be able to measure what it manages. This is especially true when it comes to data – easily one of the most significant assets any digitally driven business has access to. I recently came across this Gartner report that examines the five data and analytics (D&A) KPIs that every …

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Can an organisation be data-centric without a CDO?

Regular readers of my blog will no doubt know that due to my immersion in the data-information-insights spectrum, I’ve been very interested in data centricity and the role of the Chief Data Officer (CDO) for some time. On reading a recent industry piece about the role of the CDO, a question that came to my …

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The importance of analytics in the data governance process

When it comes to data, one of the areas that really interests me is the connection between data analytics and data governance. There is obviously a lot of material available on how data governance can assist organisations achieve better data analytics outcomes, however, a paragraph focusing on analytics-enabled data governance in this Precisely.com article ‘The …

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Finding balance between data science and data engineering

Previously, I wrote about the two-tiered data lakehouse with an analytical sandbox and a curated data warehouse in the second layer – the one for productised BI and the other for data science work. I was therefore intrigued when coming across a Forbes article titled ‘Three Keys to a Harmonious Relationship between Data Science and …

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Finding value in the data lakehouse

As you may have gathered from my previous post, I have become very interested in cloud-based data lakehouses. It was therefore with a keen interest that I read the article ‘Five Effective Ways to Build a Robust Data Lake Architecture’ on Enterprise Talk. While initially I was hoping that the author was going to review …

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