Data Quality

Data quality refers to the accuracy, completeness, consistency, and freshness of data. Dive into articles about the importance of maintaining high-quality data, common challenges, and methods to improve and measure data quality.
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Top Data Quality Articles

Most Recent Articles

Data Quality
How to automate your data quality checks
Get the rundown on automated data quality checks—including what they are, what to monitor, and how to set them up.
November 4, 2024
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8
min read
Data Quality
Data lineage: What is it and how to implement it
Data lineage is like a family tree for your data—showing you where it comes from, and how it's related to the rest of the data around it. Learn why data lineage is important and tips to implement it.
October 25, 2024
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6
min read
Data Quality
How Snowflake enabled data observability
Learn how Snowflake provided the technical foundation to turn scalable data observability from a dream into a reality.
August 22, 2024
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6
min read
Data Quality
How to manage tags for objects in Snowflake
Without a solid data management strategy, you're crossing your fingers and hoping that nothing goes wrong. Here's your first step toward a sound data governance strategy: using tags properly in Snowflake.
March 7, 2024
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6
min read
Data Quality
Three ways to track schema drift in Snowflake
Schema drift can result in missing or inconsistent data, undermining the accuracy of your Snowflake queries and reports if unaddressed. Here are 3 ways to track schema drift in Snowflake.
February 6, 2024
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6
min read
Data Quality
Machine Learning should be data-centric, not model-centric. Here’s why.
Until recently, ML model creation focused more on the architecture of the model itself, rather than the data feeding it. Here's why that's a problem.
January 12, 2024
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7
min read
Data Quality
How to maintain data integrity
Best practices for maintaining a few aspects of data integrity.
December 4, 2023
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6
min read
Data Quality
Data Quality Considerations for Data Stack Additions
Learn about common data quality mishaps when implementing new tools for your data stack.
August 17, 2023
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6
min read
Data Quality
What is Data Relevance? Definition, Examples, and Best Practices
Learn more about data relevance and how it can improve your data quality.
May 29, 2023
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5
min read
Data Quality
What is Data Security? Definition, Examples, and Best Practices
Learn more about how data security plays a role in your data quality practices.
May 29, 2023
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5
min read
Data Quality
What is Data Reliability? Definition, Examples, and Best Practices
Learn more about how data reliability plays a role in your data quality practices.
May 29, 2023
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5
min read
Data Quality
What is Data Usability? Definition, Examples, and Best Practices
Learn what data usability is and what role it has to play in improving data quality across your data stack.
May 29, 2023
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5
min read
Data Quality
What is Data Validity? Definition, Examples, and Best Practices
Learn more about how valid data can play a part in your data quality strategy.
May 29, 2023
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5
min read
Data Quality
What is Data Completeness? Definition, Examples, and Best Practices
Data completeness is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.
May 28, 2023
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2
min read
Data Quality
What Is Data Accuracy? Definition, Examples, and Best Practices
Data accuracy is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.
May 28, 2023
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3
min read
Data Quality
What is Data Freshness? Definition, Examples, and Best Practices
Data freshness is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.
May 28, 2023
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3
min read
Data Quality
What is Data Consistency? Definition, Examples, and Best Practices
Data consistency is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.
May 26, 2023
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2
min read
Data Quality
A Framework to Understand How Poor Data Quality Hurts Business Performance
How does data quality impact business performance? In the best case, poor data quality creates more work for your data team. In the worst case, it costs you time, frustrates stakeholders, jeopardizes revenue, and damages customer sentiment.
May 25, 2023
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6
min read
Data Quality
Data Monitoring v Data Observability
Learn more about how data quality tests, data monitoring, and data observability differ, while still improving data quality in their own ways.
May 25, 2023
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5
min read
Data Quality
Concepts and Practices to Ensure Data Quality
There are a multitude of potential data quality issues, and equally many ways to improve. This post describes two guidelines, three concepts, and four best practices to preserve trust in data.
May 24, 2023
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10
min read
Data Quality
Best Data Catalogs: An Evaluation Guide
Data catalogs are being adopted to improve data quality and help analytics and data engineering teams better understand what's available to use. Read on if you're currently evaluating data catalogs!
May 24, 2023
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5
min read
Data Quality
Benefits of Data Lineage for Better Data Quality
Learn how you can use data lineage, provided by data observability tools, to improve data quality across your modern data stack.
May 24, 2023
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5
min read
Data Quality
Data Quality Metrics for Data Warehouses (or: KPIs for KPIs)
A framework of data quality metrics, a shortlist of metrics, and a process for identifying which metrics your team should use.
May 22, 2023
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15
min read
Data Quality
How to Use Machine Learning for Robust Data Quality Checks
Learn how machine learning can help make your data quality checks more robust, empowering data and analytics engineers to make reliable and accurate data-driven decisions
May 16, 2023
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6
min read
Data Quality
The Definitive Guide to Snowflake Data Lineage
Learn how to extract and use data lineage in Snowflake to optimize your data pipelines and improve data engineering workflows.
May 15, 2023
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15
min read
Data Quality
Stay Fresh: Two Ways to Track Update Times for Snowflake Tables and Views
Discover how to ensure your data is fresh and up-to-date in Snowflake with two essential tools: the MAX function and the LAST_ALTERED column.
May 14, 2023
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3
min read
Data Quality
Stay Fresh: Four Ways to Track Update Times for BigQuery Tables and Views
Master Data Freshness in Google BigQuery: Keep your insights up-to-date and your decisions data-driven with our guide to monitoring table and view updates in BigQuery.
May 14, 2023
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4
min read
Data Quality
Three Ways to Retrieve Row Counts in Redshift Tables and Views
Understand your data better in Amazon Redshift with accurate row counts. Discover how using COUNT functions and system statistics can optimize your data management.
May 12, 2023
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5
min read
Data Quality
Three Ways to Retrieve Row Counts for Snowflake Tables and Views
Explore various methods to obtain row counts in Snowflake, from simple SQL queries to leveraging table statistics, for performance optimization and data analysis.
May 12, 2023
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4
min read
Data Quality
Four Efficient Techniques to Retrieve Row Counts in BigQuery Tables and Views
A comprehensive guide on retrieving row counts in tables and views for Google BigQuery. We detail practical methods, discuss their trade-offs, and provide useful code snippets.
May 12, 2023
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4
min read
Data Quality
How to Set Up Data Quality Tests
Data engineers use unit testing for data quality today, but quality assurance needs more. In this post, we offer best practices for robust data quality standards.
May 10, 2023
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4
min read
Data Quality
The Root Causes of Data Quality Issues
Understand 5 common sources of data quality issues: input errors, infrastructure failures, incorrect transformations, invalid assumptions, and ontological misalignment. Learn to combat these with smart strategies to turn data into your strongest asset.
May 3, 2023
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7
min read
Data Quality
Data Quality Fundamentals: What It Is, Why It Matters, and How You Can Improve It 
Data quality has a massive impact on the success of an organization. In this blog post, we highlight what it is, why it matters, what challenges it presents, and key practices for maintaining high data quality standards.
October 5, 2022
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7
min read
Data Quality
A 6-Step Process for Managing Data Quality Incidents
Need to streamline your data quality issue management process? In this blog post, we take inspiration from site reliability engineering to craft a six-step process for handling your data incidents.
September 30, 2022
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9
min read
Data Quality
The Importance of Data Quality for PLG Companies
Product-led companies are fundamentally data-driven. Data about the product, customers, and users facilitates every part of the PLG business and the product behind it. Given the central role of data, problems with data quality can have massive impacts on revenue, customer sentiment, team efficiency, and strategy and forecasting.
August 10, 2022
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7
min read
Data Quality
5 Common Data Quality Challenges (and How to Solve Them)
From getting to know hundreds of data teams, we've discovered that the most common data quality challenges result from both human and machine errors. Here are the top five problems we've encountered.
May 25, 2022
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5
min read
Data Quality
Data Quality Begins and Ends Outside of the Analytics Team
The people traditionally most concerned with data quality are naturally the people debugging data issues themselves, being analytics teams. Conversations around data quality have been focused around data pipeline tests and anomaly detection. What about ensuring data quality both upstream and downstream of analytics workflows?
March 22, 2022
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5
min read
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