{"id":21717,"date":"2025-06-24T13:26:50","date_gmt":"2025-06-24T13:26:50","guid":{"rendered":"https:\/\/www.cleverrepublic.com\/?post_type=blog&p=21717"},"modified":"2025-10-15T16:44:35","modified_gmt":"2025-10-15T14:44:35","slug":"measuring-data-quality-of-a-data-product","status":"publish","type":"blog","link":"https:\/\/www.cleverrepublic.com\/nl\/resources\/blog\/measuring-data-quality-of-a-data-product\/","title":{"rendered":"Het meten van de datakwaliteit van een dataproduct."},"content":{"rendered":"
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Het meten van de datakwaliteit van een dataproduct.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Gone are the days when data sat quietly in spreadsheets. Today, it is stepping up as a Data Product, designed with purpose, owned with intent, and built to deliver value. Any BI tool, machine learning model, or even ESG reporting tools can be considered a Data Product. Organisations are shifting from viewing data as a byproduct to treating it as a strategic Data Product: with clear ownership, purpose, and measurable value.<\/span>\u00a0<\/span><\/p>

At Clever Republic, we believe that trustworthy data is at the heart of every successful Data Product. That\u2019s why, in this new blog series, we\u2019re diving into one of the most important, but often overlooked, aspect:\u00a0<\/span>measuring Data Quality of Data Products<\/span><\/b>.<\/span>\u00a0<\/span>But before we jump into real-life examples, let\u2019s start at the beginning.<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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What is a Data Product?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Depending on the organisation, a Data Product is generally defined as a reusable \u2018package\u2019 containing data which solves a specific business problem or answers a key business question. It includes not only the data itself, but also the necessary context about the data and how to access it. In this way, a Data Product contains data that is understandable, useable, and accessible for anyone.\u00a0<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Aspects of Data Products<\/span><\/b>\u00a0<\/span><\/h4>

Just like any product, a Data Product has a few critical aspects. It\u2019s up to the Data Product owner to keep them in top shape. A great Data Product has the following aspects:<\/span>\u00a0
<\/span>Trusted Data:<\/span><\/b>\u00a0A Data Product is only as good as the data behind it. If the Data Quality is poor, the outcomes will be too.\u00a0<\/span>\u00a0
<\/span>Easy Accessibility:<\/span><\/b>\u00a0Great Data Products are ready when users need them. Owners should make sure the right teams can easily find and use them.<\/span>\u00a0
<\/span>Secure and Compliant:<\/span><\/b>\u00a0Data Products must meet all security, governance, and compliance requirements: no exceptions.<\/span>\u00a0<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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What's coming next?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Over the next few blogs, we will walk you through real-world use cases of Data Products. We will show how to measure the Data Quality of Data Products by using\u00a0Data Quality tools<\/strong><\/a>, such as\u00a0SODA<\/a>\u00a0and\u00a0Collibra<\/a>. Each blog will include practical tips, real examples, and a peek into our approach of this at Clever Republic using our own Data Products made for our fictive company Groove.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFinancial Data Product \u2013 \u201cPension Payout\u201d\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h4>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tOur first Data Product focuses on financial operations and is called Pension Payout. It calculates the exact monthly pension payment for every employee at Groove. Accurate, timely, and complete data is critical. Without high Data Quality, payout errors can occur, leading to compliance risks and employee dissatisfaction. Pension Payout transforms raw payroll and HR data into trusted financial insights. It reduces manual effort, eliminates uncertainty, and ensures every euro is accounted for.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tESG Reporting Data Product \u2013 \u201cGreenhouse Gas Impact\u201d\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h4>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tOur second Data Product supports ESG and sustainability goals. Named Greenhouse Gas Impact, it enables organisations to track, analyse, and report Scope 1, 2, and 3 emissions in line with CSRD requirements. Low Data Quality turns ESG reporting into a compliance headache. Greenhouse Gas Impact solves this by automating data collection from logistics, utilities, and suppliers. It standardises emissions calculations and ensures audit readiness. The product uses Data Intelligence to establish full traceability, define ownership, and clarify terminology. This builds confidence across sustainability and compliance teams.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAI Model Data Product \u2013 \u201cCustomer Churn Prediction\u201d\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h4>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\t\t\tOur third Data Product uses artificial intelligence to help Groove retain customers. Customer Churn Predictor forecasts which users are likely to stop using the platform. The model analyses patterns like purchase behaviour, engagement, and support interactions to generate churn predictions. Without clean data, the model risks producing false alerts, wasting marketing budget, and damaging trust in AI. To avoid this, we embed strong Data Quality controls and AI Governance from the start. Every prediction is explainable and actionable. The insights empower marketing and customer success teams to create timely and personalised campaigns. These include exclusive offers and targeted re-engagement tactics.\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Final thoughts<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Treating data as a product is a necessity, but no Data Product can succeed without high Data Quality and strong governance. Whether you’re in finance, compliance, AI, or sustainability, ensuring trust in your data is the foundation for real business value. Follow along in our mini-blog series and discover how to build high-quality, high-impact Data Products per use case.<\/p>

Need help measuring or improving your Data Product\u2019s quality? Let\u2019s talk. At Clever Republic, we bring together strategy, governance, and technology to make your Data Products trusted and future-proof. Get in touch <\/strong><\/a>with us!<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Measuring Data Quality of a Data Product Gone are the days when data sat quietly in spreadsheets. Today, it is stepping up as a Data Product, designed with purpose, owned with intent, and built to deliver value. Any BI tool, machine learning model, or even ESG reporting tools can be considered a Data Product. Organisations…<\/p>","protected":false},"author":39,"featured_media":21568,"template":"","categories":[148],"class_list":["post-21717","blog","type-blog","status-publish","has-post-thumbnail","hentry","category-data_quality"],"yoast_head":"\nMeasuring Data Quality of a Data Product - Clever Republic<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.cleverrepublic.com\/nl\/blog\/\/resources\/blog\/measuring-data-quality-of-a-data-product\/\" \/>\n<meta property=\"og:locale\" content=\"nl_NL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Measuring Data Quality of a Data Product - Clever Republic\" \/>\n<meta property=\"og:description\" content=\"Measuring Data Quality of a Data Product Gone are the days when data sat quietly in spreadsheets. 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