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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. In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. The following diagram illustrates a sample architecture.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps. Query> Write an essay on DataOps.

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Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

When migrating Hadoop workloads to Amazon EMR , it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost.

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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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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

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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. Azure Data Explorer.

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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.