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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

Financial services customers are using data from different sources that originate at different frequencies, which includes real time, batch, and archived datasets. Additionally, they need streaming architectures to handle growing trade volumes, market volatility, and regulatory demands. version cluster. version cluster.

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Top Five Financial KPIs for the Insurance Industry

Jet Global

In an unpredictable industry such as insurance , finance and accounting teams simply cannot ignore the importance of careful financial management. Smart accounting protects an insurer from changes in the competitive landscape, regulatory issues, internal shake-ups, and even history-making events like the COVID-19 pandemic. Loss Ratio.

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How a Discovery Data Warehouse, the next evolution of augmented analytics, accelerates treatments and delivers medicines safely to patients in need

Cloudera

However, as they continue finding treatments and understanding the progression of these cancers, they now also need to serve a much higher expectation on delivery to market. How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

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Business Intelligence vs Data Science vs Data Analytics

FineReport

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

Unlocking the value of data with in-depth advanced analytics, focusing on providing drill-through business insights. Providing a platform for fact-based and actionable management reporting, algorithmic forecasting and digital dashboarding. zettabytes of data. FOUNDATIONS OF A MODERN DATA DRIVEN ORGANISATION. Insurance.