LONDON, Dec. 18, 2024 /PRNewswire/ — By 2030, the manufacturing industry is projected to generate 4.4 zettabytes of data worldwide, according to forecasts by global technology intelligence firm ABI Research. This massive data stream, originating from IoT sensors, CNC systems, ERP platforms, automated identification readers, and MES systems, represents a transformative opportunity for enterprises to sustain competitiveness, drive innovation, and enable AI-driven solutions. However, many enterprises and digitalization providers lack the expertise to fully leverage this data, resulting in inefficiencies and revenue losses amounting to hundreds of millions of dollars annually.
“Generating a lot of data is one thing – being able to analyze and prepare this data for Large Language Models and AI algorithm training is another,” states Leo Gergs, Principal Analyst at ABI Research. “Data fabrics hold immense promise in transforming enterprise operations through seamless integration, enhanced governance, and automated data management. To unlock their full potential, it’s imperative to address a spectrum of challenges spanning technology, governance, operations, and organizational readiness.”
Integrating legacy systems, on-premises platforms, and cloud-native solutions into a cohesive data fabric is a major hurdle. Vendors like Databricks, IBM, and NetApp are developing platforms that unify these environments, enabling real-time data processing and seamless compatibility. Gergs explains, “The ability to bridge diverse systems is critical to unlocking the true value of data fabrics. Enterprises manage sensitive and regulated data that require strict compliance frameworks.”
Solutions like Informatica‘s Intelligent Data Management Cloud, Palantir Foundry, Cloudera‘s Data Platform, and AWS Industrial Data Fabric enable enterprises to enforce governance with automated lineage tracking, access control, and encryption. Data fabrics must ensure trust and compliance, particularly in sectors like healthcare, manufacturing, and government.
Traditional methods like manual ETL and siloed systems hinder scalability. Vendors such as Qlik, Denodo, Databricks, and Microsoft Fabric are addressing these bottlenecks by automating workflows, enhancing real-time analytics, and streamlining operations. According to Gergs, “Enterprises are looking to data fabrics for faster, smarter, and more efficient data handling. Balancing customization for unique enterprise needs with scalable solutions is essential. But in all of this, the right balance between customization and standardization is critical for widespread adoption and long-term success.”
To overcome these challenges, vendors must go beyond delivering technology, providing comprehensive integration support, education, and ongoing collaboration with enterprises. “The key to success is not just selling a product but enabling a partnership. Vendors must walk together with enterprises, guiding them through integration, building workforce capabilities, and ensuring long-term value. A proactive and supportive approach will transform obstacles into opportunities,” Gergs advises.
These findings are from ABI Research’s Overcoming Challenges in Bringing Data Fabrics to Industrial Enterprises report. This report is part of the company’s Hybrid Cloud & 5G Markets research service, which includes research, data, and ABI Insights.
About ABI Research
ABI Research is a global technology intelligence firm uniquely positioned at the intersection of technology solution providers and end-market companies. We serve as the bridge that seamlessly connects these two segments by providing exclusive research and expert guidance to drive successful technology implementations and deliver strategies proven to attract and retain customers.
ABI Research是一家全球性的技术情报公司，拥有得天独厚的优势，充当终端市场公司和技术解决方案提供商之间的桥梁，通过提供独家研究和专业性指导，推动成功的技术实施和提供经证明可吸引和留住客户的战略，无缝连接这两大主体。
For more information about ABI Research’s services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific, or visit www.abiresearch.com.
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SOURCE ABI Research
