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Building Your Human Benchmark with Ontotext Metadata Studio

Ontotext

To be able to annotate the specified content consistently and unambiguously, these experts usually follow a set of specific conventions, which are referred to as “annotation guidelines”. This measures the consistency of annotations when more than one person is involved in the process.

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Run Trino queries 2.7 times faster with Amazon EMR 6.15.0

AWS Big Data

Benchmark setup In our testing, we used the 3 TB dataset stored in Amazon S3 in compressed Parquet format and metadata for databases and tables is stored in the AWS Glue Data Catalog. The following graph shows performance improvements measured by the total query runtime (in seconds) for the benchmark queries. With Amazon EMR 6.10.0

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

AWS Big Data

The second streaming data source constitutes metadata information about the call center organization and agents that gets refreshed throughout the day. For the template and setup information, refer to Test Your Streaming Data Solution with the New Amazon Kinesis Data Generator. We use two datasets in this post.

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The Future of Data Lineage and the Role of Metadata

Alation

Active metadata will play a critical role in automating such updates as they arise. This has been the dominant approach for nearly 50 years, and in my opinion, was born out of the work of Thomas McCabe in the 1970’s to measure the complexity of Cobol programs. Why Focus on Lineage? Support for all technologies.

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Deploy Amazon QuickSight dashboards to monitor AWS Glue ETL job metrics and set alarms

AWS Big Data

Although we don’t cover optimizing your jobs for costs in this post, you can refer to Monitor and optimize cost on AWS Glue for Apache Spark to learn how to fine-tune your AWS Glue jobs for performance, efficiency ,and cost-optimization. Refer to Managing user access inside Amazon QuickSight to find your existing QuickSight users.

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Do I Need a Data Catalog?

erwin

Data catalogs combine physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals in certain circumstances. You also can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

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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

5) How Do You Measure Data Quality? In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. How Do You Measure Data Quality? Table of Contents. 2) Why Do You Need DQM?