data quality

Announcements
Announcing Snowflake’s Investment in Metaplane
We’re excited to announce that Snowflake has invested in Metaplane. Here’s how this strengthened partnership will scale us both to new heights.
May 15, 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
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
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 Observability
What Data Observability Is, What It’s Not, and Why it Matters
Data observability is arguably the hottest concept in the data space today, but few have a clear sense of what it means. This blog post offers a definition of data observability, differentiates it from related concepts, and emphasizes why it's important.
May 24, 2023
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8
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
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 Culture
Data Reliability Engineering: A Guide to Ensuring Data Quality in the Modern Data Stack
Read this post to understand if you should formally assign or hire a member of your team to focus on data reliability.
May 23, 2023
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4
min read
Data Culture
Stale Data Leads to Bad Business Decisions
Using stale data for decision-making can have dire consequences. In this blog post, we explore the risks and emphasize the significance of accurate data.
May 23, 2023
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4
min read
Data Culture
Data Contracts: Bridging the Gap Between Business and Data
Discover the significance of data contracts as a bridge between business and data in our blog post. Uncover their definition, key elements, benefits, and effective implementation tips.
May 23, 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
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
Changelog
Introducing Partition Monitors: find data quality issues in segments of your data
Easily monitor specific data segments with Metaplane's new partition monitors to identify root causes of data quality issues in seconds.
February 9, 2023
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4
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 Observability
6 Signs You Need a Data Observability Tool
As data observability tools grow in popularity, many data leaders are asking themselves, “Does my team need one?” In this blog post, we share six signs you need one and three signs you don't.
September 8, 2022
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5
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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