article thumbnail

The Future of AI in the Enterprise

Jet Global

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

article thumbnail

Build an Amazon Redshift data warehouse using an Amazon DynamoDB single-table design

AWS Big Data

This approach comes with a heavy computational cost in terms of processing and distributing the data across multiple tables while ensuring the system is ACID-compliant at all times, which can negatively impact performance and scalability. This is inefficient from both a cost and performance perspective.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

The Future of AI in the Enterprise

Jet Global

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

article thumbnail

How to Build a Performant Data Warehouse in Redshift

Sisense

First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). This approach made sense during a time in which the cost of storage was high, so normalizing tables reduced the total footprint. So let’s dive in! OLTP vs OLAP.