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Explore The Power & Potential Of Professional Social Media Dashboards

datapine

Gathering data and information from one or multiple platforms and creating a comprehensive social media dashboard is equally important as creating the social content itself. Your Chance: Want to test a social media dashboard software for free? Benefit from professional social dashboards! We offer a 14-day trial.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics: Part 2

AWS Big Data

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. This post, walks through how to integrate AWS Glue job observability metrics with Grafana using Amazon Managed Grafana. Choose Administration.

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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

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Simplify Metrics on Apache Druid With Rill Data and Cloudera

Cloudera

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Deploying metrics shouldn’t be so hard. Cloudera Data Warehouse).

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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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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. In the following sections, we discuss these steps in more detail.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

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