Analytics

With the integration of BigQuery and Document AI, you can extract insights from document data and build new large language model (LLM) applications.

Vertex AI transcription models in BigQuery let you transcribe speech files and combine them with structured data to build analytics and AI use cases.

Effective management of Redshift costs is closely tied to data storage optimization. Choosing the right data types and implementing data compression are pivotal in reducing storage footprints and costs. Redshift’s columnar storage format enhances query performance, which in turn can lead to significant savings. For a more comprehensive approach, integrating tools like Anodot can provide advanced analytics and real-time visibility to further streamline storage efficiency and optimize costs.

Your company collects huge amounts of data about everything from customer transactions to supplier contracts to system performance. This valuable resource becomes even more valuable when you combine it with data about financial market and economic trends, consumer spending, regional demographics and other elements that provide broader context and insights for your business decisions.

The foundation of any successful AI initiative is a well-integrated and meticulously managed data platform.

How generative AI brings radical new capabilities to the world of AI and machine learning.