Data is the lifeblood of an intelligent enterprise. Explore our data-related topics to learn more about how to become a data-driven business.
The field of exploration that focuses on getting computers to complete tasks we’d previously assumed only a human could do.
A data paradigm that focuses on collecting and rapidly making sense of large amounts of information from a wide variety of sources.
Continuous delivery for machine learning — CD4ML — takes software engineering approaches and applies them to the creation of machine learning applications.
A data lake is a repository — typically a large one — for storing data of many types.
Data mesh is an approach to data architecture where ownership of the data is distributed among cross-functional domain teams, who then provide data products to end users.
Data science combines methods, processes and technology to extract knowledge and insights from data to achieve some business purpose.
Deep learning is a branch of machine learning that uses multi-layered networks of computational nodes called neurons, creating an artificial neural network that mimics the way human brains process information.
A style of creating software that uses business events to trigger actions. Ideal for rapidly growing enterprises that need to respond quickly to changes.
Making AI solutions transparent and understandable — from the decisions they make, to the results they generate.
Apache Kafka is an open-source streaming platform frequently used by companies looking to develop innovative digital services that rely on large, real-time data sets.
Machine learning is a branch of artificial intelligence that uncovers patterns in large accumulations of data in order to make predictions and decisions.
A traditional approach to analyzing data that aims to create models from past behavior that can be used to make future predictions.