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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 364
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Cloud Data Warehouse Migration 101: Expert Tips

Alation

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. And what must organizations overcome to succeed at cloud data warehousing ?

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Implement historical record lookup and Slowly Changing Dimensions Type-2 using Apache Iceberg

AWS Big Data

In todays data-driven world, tracking and analyzing changes over time has become essential. As organizations process vast amounts of data, maintaining an accurate historical record is crucial. History management in data systems is fundamental for compliance, business intelligence, data quality, and time-based analysis.

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How Gupshup built their multi-tenant messaging analytics platform on Amazon Redshift

AWS Big Data

Objective Gupshup wanted to build a messaging analytics platform that provided: Build a platform to get detailed insights, data, and reports about WhatsApp/SMS campaigns and track the success of every text message sent by the end customers. Additionally, extract, load, and transform (ELT) data processing is sped up and made easier.

Analytics 119
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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. In addition, organizations rely on an increasingly diverse array of digital systems, data fragmentation has become a significant challenge.

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How Cloudinary transformed their petabyte scale streaming data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. However, throughout history, data services have held dominion over their customers’ data.

Data Lake 126
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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

Data is at the center of every application, process, and business decision. Customers across industries are becoming more data driven and looking to increase revenue, reduce cost, and optimize their business operations by implementing near real time analytics on transactional data, thereby enhancing agility.