Remove Business Objectives Remove Interactive Remove OLAP
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The Future of AI in the Enterprise

Jet Global

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

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AI vs. BI for Business, What Do You Need?

Jet Global

To successfully interact with the physical world, these devices must be able to observe the world through different types of sensors and perform actions based on those observations. In each of these applications, the differentiator is that machines aren’t simply reacting to data and providing a prescriptive output.

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

AWS Big Data

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. It enables you to create interactive dashboards, visualizations, and advanced analytics with ML insights.

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Goodbye Oracle Discoverer, Hello Next-Generation Reporting

Jet Global

It’s also important to consider your business objectives, both inside and outside finance. Interactive dashboards that provide reports with a rich variety of visualization tools. Challenge Business Requirements. However, be prepared to challenge your team’s perceived business requirements. But does OBIEE stack up?

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The Future of AI in the Enterprise

Jet Global

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

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

AWS Big Data

The data warehouse is highly business critical with minimal allowable downtime. A successful migration can be accomplished through proactive planning, continuous monitoring, and performance fine-tuning, thereby aligning with and delivering on business objectives.