Building a Strong Data Foundation for Enterprise AI

From predictive analytics and machine learning to generative AI, data is the lifeblood that fuels the development and efficacy of AI systems. At the same time, data-related issues remain a key obstacle across the training, deployment, scaling, and return on investment of initiatives at many enterprises. These issues include the availability and quality of data, the volume and speed at which data needs to be processed, as well as the protection of data.

Ultimately, AI depends and thrives on large, diverse data sets. To succeed, enterprises need fast access to data across different data stores, clouds, locations, and vendors. Equally important, enterprises must have effective safeguards in place to ensure that clean, highquality data is being used in a manner that does not create privacy and compliance risks. A strong data foundation for AI must balance these requirements.

Download this special report for key considerations and best practices.

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