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What is Data Accuracy? Definition, Examples and KPIs

Monte Carlo

Even if data is accurate within individual records, inconsistencies or discrepancies across different sources or datasets can reduce its overall quality. Inconsistencies may arise due to variations in data formats, coding schemes, or definitions used by different systems or data providers.

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Announcing Nickel 1.0

Tweag

To minimize the risk of misconfigurations, Nickel features (opt-in) static typing and contracts, a powerful and extensible data validation framework. A REPL nickel repl , a markdown documentation generator nickel doc and a nickel query command to retrieve metadata, types and contracts from code.

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What is Data Completeness? Definition, Examples, and KPIs

Monte Carlo

The same is true with data. If all the information in a data set is accurate and precise, but key values or tables are missing, your analysis won’t be effective. That’s where the definition of data completeness comes in. Be sure to use random sampling to select representative subsets of your data.

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Data Quality Score: The next chapter of data quality at Airbnb

Airbnb Tech

To fully enable this incentivization approach, we believed it would be paramount to introduce the concept of a data quality score directly tied to data assets. We identified the following objectives for the score: Evolve our understanding of data quality beyond a simple binary definition (certified vs uncertified).

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8 Data Quality Monitoring Techniques & Metrics to Watch

Databand.ai

Data Quality Rules Data quality rules are predefined criteria that your data must meet to ensure its accuracy, completeness, consistency, and reliability. These rules are essential for maintaining high-quality data and can be enforced using data validation, transformation, or cleansing processes.

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9 Ways to Improve Your Dataplex Auto Data Quality Scans

Monte Carlo

With Dataplex, teams get lineage and visibility into their data management no matter where it’s housed, centralizing the security, governance, search and discovery across potentially distributed systems. Dataplex works with your metadata. The SQL expression should evaluate to true (pass) or false (fail) per row.

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97 things every data engineer should know

Grouparoo

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. For example, grouping the ones about metadata, discoverability, and column naming might have made a lot of sense.