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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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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. Finally, the dashboard’s user-friendly interface made survey data more accessible to a wider range of stakeholders.

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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

Here we take a look at Microsoft Azure’s essential analytics services, what they are used for, and how they come together to make a comprehensive stack for your analytics strategy in the cloud. Azure Data Factory. Azure Data Lake Analytics. Microsoft. Azure Analysis Services.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Big Data Hub

This is supported by automated lineage, governance and reproducibility of data, helping to ensure seamless operations and reliability.    IBM and AWS have partnered to accelerate customers’ cloud-based data modernization strategies. It enables secure data sharing for analytics and AI across your ecosystem.

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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

From detailed design to a beta release, Tricentis had customers expecting to consume data from a data lake specific to only their data, and all of the data that had been generated for over a decade. Data export As stated earlier, some customers want to get an export of their test data and create their data lake.