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BI Cubed: Data Lineage on OLAP Anyone?

Octopai

In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data. However, over time new technologies and tools developed to ease data reporting and analysis. Saving time and headaches with online analytical processing tool. Are you on top of your quality game?

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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.

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

AWS Big Data

ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. Unlike ingestion processes, data can be transformed as per business rules before loading. You can apply technical or business data quality rules and load raw data as well.

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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.

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