Manufacturing companies are facing more pressure to use data-driven technologies like artificial intelligence (AI) to optimize their operations. A data mesh program can help with the implementation of AI.
A data mesh is an architectural principle for a distributed approach to data management that treats data as a product that can be managed and owned. In short, a data mesh democratizes data while improving quality, integration, business self-service and scalability.
Implementing AI at scale requires access to high-quality data that is properly integrated, governed and discoverable. Traditional data management architectures are often designed with centralized storage, processing and analysis. The main difference between data mesh and traditional architectures is the shift from a centralized to a decentralized approach to data management with a focus on empowering domain experts and collaboration.
Data mesh architecture can reduce costs, increase efficiency and productivity, and enable faster responses leading to innovation and a competitive advantage for businesses. Data mesh approaches must be adopted incrementally while companies still leverage existing investments in infrastructure and other tools.
Data meshes can also allow manufacturing companies to break down data silos, democratize data, improve data standardization, foster a culture of collaboration, and drive innovation. With a data mesh, manufacturing companies can accelerate their AI initiatives and improve the accuracy and efficiency of AI models. Adidas, JPMorgan, Michelin and Equinor are some of the big-name brands that have embraced data mesh architecture.
Organizations that implement data mesh architecture are looking to achieve the following Key Performance Indicators (KPIs):
Data can be used by manufacturing companies to optimize operations, deliver value to customers and stay competitive. Adopting data meshes with AI is crucial to achieving these goals. A data mesh can break down data silos, democratize data and foster collaboration providing manufacturers with a wide range of benefits, including predictive maintenance, quality control, enhanced supply chain optimization and sustainability efficiency. As a result, manufacturing companies can drive innovation, accelerate decision-making and ultimately gain a competitive edge in the industry.
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