Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence (AI) based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. However, machine learning is not just for predictive analytics. It can also be embedded within tools to automate data management development and optimize execution. This interesting information came to us from TDWI in their article, “Machine Learning that Automates Data Management Tasks and Processes.”
Modern tools can catalog and categorize data automatically via machine learning algorithms and models as well as via old-school business rules and application logic. Machine learning algorithms and other tool logic can recognize and catalog data sources and structures that are of particular domains. This helps users who will browse or search the catalog for domains of high interest, such as the customer, product, and financial domains. With big data, Internet of Things (IoT), and other new sources that are notoriously devoid of metadata, a modern DM tool with ML embedded can parse data and deduce credible metadata.
The list of uses for machine learning is expanding as the high value is being realized by many.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.