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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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Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

While the organization of these layers has been refined over the years, the interoperability of the technologies, the myriad software, and orchestration of the systems make the management of these systems a challenge. A data-driven future powered by cloud data warehouse technologies. Cloud data warehouses.

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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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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions.

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. In the 2010s, columnar OLAP (C-OLAP) and in-memory OLAP (IM-OLAP) technologies gained prominence.

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Data Model Development Using Jinja

Sisense

Data warehouses provide a consolidated, multidimensional view of data along with online analytical processing ( OLAP ) tools. OLAP tools help in the interactive and effective processing of data in a multidimensional space. The benefits of DBT with Jinja. DBT + Sisense: A powerful combination.

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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). But a business could very well have a scenario where they need more compute power and higher concurrency to process a backlog of queries, but not necessarily more storage.