Remove Automation Remove Data Extraction Remove Data Ingestion
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ETL Process Explained: Essential Steps for Effective Data Management

Pickl AI

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. Introduction The ETL process is crucial in modern data management.

ETL 52
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Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning Blog

MongoDB Atlas offers automatic sharding, horizontal scalability, and flexible indexing for high-volume data ingestion. Among all, the native time series capabilities is a standout feature, making it ideal for a managing high volume of time-series data, such as business critical application data, telemetry, server logs and more.

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How the UNDP Independent Evaluation Office is using AWS AI/ML services to enhance the use of evaluation to support progress toward the Sustainable Development Goals

AWS Machine Learning Blog

Data ingestion and extraction Evaluation reports are prepared and submitted by UNDP program units across the globe—there is no standard report layout template or format. The data ingestion and extraction component ingests and extracts content from these unstructured documents.

ML 82
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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

Codify Operations for Efficiency and Reproducibility By performing operations as code and incorporating automated deployment methodologies, organizations can achieve scalable, repeatable, and consistent processes. Build and release optimization – This area emphasizes the implementation of standardized DevSecOps processes.

IDP 108
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Comparing Tools For Data Processing Pipelines

The MLOps Blog

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Data Transformation : Putting data in a standard format post cleaning and validation steps.

ETL 59
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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

SnapLogic , a leader in generative integration and automation, has introduced the industry’s first low-code generative AI development platform, Agent Creator , designed to democratize AI capabilities across all organizational levels. This post is cowritten with Greg Benson, Aaron Kesler and David Dellsperger from SnapLogic. Not anymore!