Unlocking the Power of Data Normalization: An Interview with Derek Sewell from DataX.ai

In today's digital landscape, data plays a crucial role in determining business success, especially for manufacturers, distributors, and e-commerce companies. Managing, normalizing, and enhancing vast amounts of product data can be a daunting task, one that requires expertise in handling unstructured data. Derek Sewell, a strategic leader at DataX, recently joined a podcast with Matt to discuss DataX's approach to tackling these challenges. Below is a breakdown of the key insights from their conversation.

The Importance of Data in the Digital Age

As eCommerce continues to expand, businesses are increasingly challenged by the need to present their data in an organized, searchable, and unified manner. This issue is particularly prominent in the B2B space, where distributors and manufacturers often rely on various data sources that were never designed for seamless integration.

According to Derek Sewell, DataX specializes in solving these problems by focusing on the normalization and enhancement of unstructured data. This process involves creating a unified, structured dataset from disparate data sources, which can then be used for everything from product catalogs to customer-facing e-commerce platforms.

"Regardless of size, everyone has the same problem," Sewell said, highlighting that companies ranging from small mom-and-pop shops to Fortune 500 giants face data alignment challenges.

What is Data Normalization?

Data normalization is a process that ensures uniformity across data sets. This involves taking varied data inputs and standardizing them into a consistent format. For example, Sewell shared that a product’s country of origin might be listed as “USA,” “US,” or “United States” across different data sources. Data normalization consolidates these variations into a single, uniform entry.

Sewell also touched on the complexities that arise in fields like B2B eCommerce, where product data can be highly variable. “You might be dealing with something as simple as a bolt, but the data might include size, material, origin, and manufacturer — all of which need to be aligned,” he explained.

The Challenges of Data Enrichment

Beyond normalization, data enrichment involves filling in missing values or adding supplemental data to make product listings more complete. For instance, a product might lack a description or have outdated specifications. Data enrichment allows businesses to not only complete their datasets but also provide valuable information that can give them a competitive edge.

DataX takes a hybrid approach to these processes, leveraging AI while also incorporating human expertise. Sewell emphasized that this “human-in-the-loop” approach ensures the accuracy of the enriched data, preventing issues that might arise from over-reliance on AI-generated results.

Real-World Data Issues in E-commerce

Matt, from Harris Web Works, provided a real-world example from his agency, which helps businesses implement e-commerce solutions. He explained how distributors working in a brick-and-mortar environment might have product data based on informal knowledge — buyers would know a product by name or brand. However, when the time comes to upload product catalogs online, this fragmented knowledge becomes a problem. Manufacturers’ IDs, product descriptions, and attributes like size or material all need to be aligned across different manufacturers, creating a challenge for web developers and the businesses they serve.

Enter the PIM System

One of the emerging trends in B2B eCommerce is the use of Product Information Management (PIM) systems, which serve as central repositories for product data. Matt noted that companies are increasingly turning to PIM systems to handle their data, as relying on an ERP system can often lead to inefficiencies.

Sewell agreed, pointing out that data-heavy industries like manufacturing and distribution need robust systems that can handle large volumes of product data without bogging down their ERP systems. "When you have a product data set with millions of SKUs and hundreds of attributes, you're talking about millions of data points, and you don’t want that in your ERP," Sewell explained.

Leveraging AI for Better Data Management

DataX’s use of AI enables them to clean and normalize data much faster and more affordably than traditional methods, which often rely on brute force. However, Sewell is quick to warn that AI isn’t a silver bullet. “There’s a lot of hype that AI will solve every problem, but that’s not the case. The only successful way we’ve found to leverage AI is through a hybrid approach — AI helps process the data, but human experts validate it.”

The models are continually improving, and Sewell sees the future of AI in this field as evolving to process data even faster. But businesses should still be wary of over-relying on generative AI models like ChatGPT for mission-critical data tasks without human oversight. “Right now, mission-critical data isn’t processed without full manual review, and that’s something businesses are learning,” Sewell added.

The Future of Data Normalization and AI

Looking forward, Sewell envisions a world where data processing becomes faster and more accurate. AI will continue to play a significant role, but human oversight will remain essential for the foreseeable future.

In closing, Sewell emphasized DataX’s commitment to offering a no-risk engagement model, which allows businesses to test out their services with large free samples. This approach helps companies understand the value they’re receiving before committing to a full engagement, making DataX a trusted partner in solving data challenges for businesses of all sizes.

Conclusion

As the digital landscape continues to evolve, the ability to manage, normalize, and enrich data will be a key differentiator for businesses. With companies like DataX leading the way, businesses can unlock new efficiencies and ensure that their data is working for them — not the other way around.

If your business is struggling with data challenges, DataX offers a no-risk solution that could provide the competitive edge you’ve been looking for. Whether it's product data, invoicing, or HR data, DataX can help you streamline and enhance your data processes, paving the way for better business outcomes.