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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Enable advanced search capabilities for Amazon Keyspaces data by integrating with Amazon OpenSearch Service

AWS Big Data

Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

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Automate alerting and reporting for AWS Glue job resource usage

AWS Big Data

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

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Deep dive into the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

For more details on how to configure and schedule the log collector, refer to the yarn-log-collector GitHub repo. Transform the YARN job history logs from JSON to CSV After obtaining YARN logs, you run a YARN log organizer, yarn-log-organizer.py, which is a parser to transform JSON-based logs to CSV files.

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot Blog

The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against. This task may require complex joins, aggregations, filtering, window functions, and many other data transformations against extremely large-scale data sets.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

In this post, we discuss ways to modernize your legacy, on-premises, real-time analytics architecture to build serverless data analytics solutions on AWS using Amazon Managed Service for Apache Flink. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

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Stream VPC Flow Logs to Datadog via Amazon Kinesis Data Firehose

AWS Big Data

Kinesis Data Firehose is a fully managed service for delivering near-real-time streaming data to various destinations for storage and performing near-real-time analytics. You can perform analytics on VPC flow logs delivered from your VPC using the Kinesis Data Firehose integration with Datadog as a destination.