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A Complete Guide To Finding The Product Metrics That Matter

datapine

1) What Are Product Metrics? 2) Types Of Product Metrics. 3) Product Metrics Examples You Can Use. 4) Product Metrics Framework. The right product performance metrics will give you invaluable insights into its health, strength and weaknesses, potential issues or bottlenecks, and let you improve it greatly.

Metrics 141
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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

AWS Big Data

Today we are pleased to announce a new class of Amazon CloudWatch metrics reported with your pipelines built on top of AWS Glue for Apache Spark jobs. The new metrics provide aggregate and fine-grained insights into the health and operations of your job runs and the data being processed. workerUtilization showed 1.0

Metrics 102
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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

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. Data quality refers to the assessment of the information you have, relative to its purpose and its ability to serve that purpose.

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

AWS Big Data

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. It provides insights and metrics related to the performance and effectiveness of data quality processes. We can analyze the data quality score and metrics using Athena SQL queries.

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Unbundling the Graph in GraphRAG

O'Reilly on Data

While RAG leverages nearest neighbor metrics based on the relative similarity of texts, graphs allow for better recall of less intuitive connections. For example, a mention of “NLP” might refer to natural language processing in one context or neural linguistic programming in another. Do LLMs Really Adapt to Domains?

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The Race For Data Quality in a Medallion Architecture

DataKitchen

For instance, records may be cleaned up to create unique, non-duplicated transaction logs, master customer records, and cross-reference tables. Similarly, downstream business metrics in the Gold layer may appear skewed due to missing segments, which can impact high-stakes decisions.

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Build a pseudonymization service on AWS to protect sensitive data: Part 2

AWS Big Data

For an overview of how to build an ACID compliant data lake using Iceberg, refer to Build a high-performance, ACID compliant, evolving data lake using Apache Iceberg on Amazon EMR. In the following examples, we analyze three important Lambda metrics for the pseudonymization service: Invocations , ConcurrentExecutions , and Duration.

Metrics 101