The data story behind sustainability
Together, digital maturity and connected data empower organizations to embed sustainability into engineering, manufacturing and supply chains
The biggest risk to your AI isn’t the model, it’s your data
How unreliable data undermines AI outcomes, and what you can do about it
More and more organizations are eager to start using AI. But look a little closer, and you’ll often find that it’s not the technology that causes AI models to fail. It’s the data they rely on.
You want to predict sales, plan more effectively, and stay ahead of the competition. The tools exist. The models too. And yet, the results often fall short. Why?
Because the quality of your data isn’t good enough.
In this article, we’ll look at why data quality is the foundation of any AI initiative, where things usually go wrong, and how a Data Quality Assessment can help prevent your AI project from failing before it even begins.
Rik Smink
AI consultant
Common pitfalls that derail your AI model
In a BI environment, you can work around a lot. You can clean things up in the model, apply filters, or add context manually. But AI doesn’t give you that flexibility. A model learns from the data exactly as it is. And if that data is incomplete, inconsistent, or unclear, your predictions will be just as unreliable.
Here are some of the issues we often come across during data quality assessments:
- Customer or supplier records with multiple spellings of the same name
- Incorrect or outdated address details
- Invalid email addresses
- Postal codes linked to the wrong country
- Duplicate product entries due to naming or categorization differences (for example, the same item listed under both "Accessories" and "Peripherals")
- Status fields filled with vague or inconsistent values
- Illogical combinations, like mixing up installation date and manufacturing year
- Production waste entries with missing reasons or unclear free-text explanations
Clean, reliable data isn’t just a nice-to-have. It’s the foundation for every AI project that actually delivers value.
How a Data Quality Assessment reveals what’s holding your AI back
A Data Quality Assessment doesn’t just scratch the surface. It takes a close, practical look at the state of your data and how it might affect your AI initiatives.
Some of the questions we explore:
- How many fields are empty, incorrectly filled in, or contain unrealistic outliers?
- Are there duplicate or conflicting records? How clear is the structure and hierarchy?
- Is data consistently classified, or are naming conventions all over the place?
- Are there irregular patterns or values that could confuse an AI model?
We pinpoint weak spots and offer concrete, actionable advice: what you can improve right now, what’s technically possible, and how to get your data—and your organization—ready for reliable AI.
The step most teams skip before starting with AI
As AI tools become easier to access, many organizations rush in without laying the groundwork. Data quality gets overlooked. The result? A model that behaves unpredictably and delivers unreliable output.
A Data Quality Assessment helps you avoid that. It gives you the clarity to make informed decisions, based on data you can actually trust.
AI starts with data. And that starts with taking control of its quality.
The future of SMEs in Industry 5.0
For SMEs, transitioning from Industry 4.0 to 5.0 presents both a challenge and an opportunity. As the initial costs of implementing Smart Factory systems become more manageable and new technologies enable greater flexibility, SMEs will be better positioned to adopt these innovations. At 9altitudes, we understand that the journey doesn’t end with Industry 4.0 - and we’re here to ensure that our clients are prepared for what’s next.
Our digital common thread connects the solutions and systems of today with the opportunities of tomorrow, integrating sustainability, human creativity, and advanced technology into a seamless manufacturing ecosystem.
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Digital business transformation is what we do. Making sure organizations are ready to deliver for the end customer of today and those of tomorrow. Thanks to our industry expertise, we are able to combine speed and quality into your digital transformation journey.