Remove Internet of Things Remove Online Analytical Processing Remove Reference
article thumbnail

How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

article thumbnail

The Future of AI in the Enterprise

Jet Global

Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

For an example, refer to How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform. With its intuitive interface and automated conversion capabilities, the AWS SCT can significantly reduce the manual effort required during the migration process.

article thumbnail

The Future of AI in the Enterprise

Jet Global

Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.