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How DeNA Co., Ltd. accelerated anonymized data quality tests up to 100 times faster using Amazon Redshift Serverless and dbt

AWS Big Data

This blog was co-authored by DeNA Co., Among these, the healthcare & medical business handles particularly sensitive data. Conduct data quality tests on anonymized data in compliance with data policies Conduct data quality tests to quickly identify and address data quality issues, maintaining high-quality data at all times.

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What is a DataOps Engineer?

DataKitchen

DataOps establishes a process hub that automates data production and analytics development workflows so that the data team is more efficient, innovative and less prone to error. In this blog, we’ll explore the role of the DataOps Engineer in driving the data organization to higher levels of productivity. Create tests.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Your Chance: Want to test a professional logistics analytics software? Use our 14-days free trial today & transform your supply chain! Your Chance: Want to test a professional logistics analytics software? Use our 14-days free trial today & transform your supply chain! Now’s the time to strike.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments.

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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

Also known as data validation, integrity refers to the structural testing of data to ensure that the data complies with procedures. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate.

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Navigating the Chaos of Unruly Data: Solutions for Data Teams

DataKitchen

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

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DataOps Observability: Taming the Chaos (part 1)

DataKitchen

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

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