Artificial intelligence (AI) continues to gain ground as a core business competency. Machine learning or deep learning algorithms promise to revolutionize business models and processes, restructure work forces, and transform data infrastructures. This will enhance process efficiency and improve decision-making throughout the enterprise. That is a lot of promises. DATAVERSITY brought this interesting topic to us in their article, “Data Architecture and Artificial Intelligence: How Do They Work Together?”
In machine learning, data teaches and shapes the algorithm in a specific way without any programming. This means that data preparation for machine learning pipelines can be challenging if the data architectures have not been refined enough to interoperate with the underlying analytic platforms. An organization can only take advantage of this volume of data from many different sources if a sound data architecture is in place across the organization. With AI-powered analytics systems, business users can be empowered to engage in just-in-time analytics and business intelligence activities.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
