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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

By combining IBM’s advanced data and AI capabilities powered by Watsonx platform with AWS’s unparalleled cloud services, the partnership aims to create an ecosystem where businesses can seamlessly integrate AI into their operations.

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Remember when you began your career and the prospect of retirement was an event in the distant future? This may involve integrating different technologies, like cloud sources, on-premise databases, data warehouses and even spreadsheets. Add the predictive logic to the data model.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

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Dimensional modeling in Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

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How to Pinpoint Where Your Organization Wins (and Loses) with Data

CIO Business Intelligence

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. For data warehouses, it can be a wide column analytical table. Data and cloud strategy must align.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. Ingest 100s of TB of network event data per day .