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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. With the proliferation of IoT devices and the abundance of data generated by them, it has become possible to collect real-time data on inventory levels, customer behavior, and other key metrics.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 77
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Perform upserts in a data lake using Amazon Athena and Apache Iceberg

AWS Big Data

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Factory.

Data Lake 116
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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. These upstream data sources constitute the data producer components.