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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.

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

AWS Big Data

Data inbound This section consists of components to process and load the data from multiple sources into data repositories. ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. However, it’s not mandatory to use the same technologies.

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

AWS Big Data

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI). The data warehouse is highly business critical with minimal allowable downtime.

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.