TOFU

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 Culture
Data Mesh vs. Data Fabric: Key Differences and Which to Choose in 2023
How to choose the right data architecture: Weighing the pros and cons of Data Mesh and Data Fabric.
May 25, 2023
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6
min read
Data Culture
Data modernization initiative: 4 tips to get you started
Your business is evolving, and so is business tech. Data modernization makes sure the tools you use to collect and analyze data keep up.
May 25, 2023
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5
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 Culture
What are Data Products?
Explore the evolving world of data products (or data as a product), their impact on decision-making, how they're integrated into businesses, and what the implications of this new phrase is.
May 24, 2023
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4
min read
Data Culture
5 Things to Know About Microsoft Fabric
Understanding Microsoft Fabric: From OneLake's unique data storage to flexible compute setups.
May 24, 2023
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5
min read
Data Culture
Data Mesh vs. Data Lake: Key Differences and Which to Choose in 2023
A detailed guide comparing Data Mesh and Data Lake architectures, and factors to consider when choosing.
May 24, 2023
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5
min read
Data Culture
The Future of Business Intelligence: 5 Transformative Shifts in the Data Landscape
Business intelligence is evolving, and it's happening right now. Discover the 5 transformative shifts set to redefine the future of BI.
May 23, 2023
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5
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 Culture
What are Data Product Managers?
Learn more about Data Product Managers, their origin, impact on businesses, and traits to develop to make it a career.
May 23, 2023
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5
min read
Data Culture
What is a Data Mesh? Definition, Examples, and Best Practices
Get an in-depth understanding of the Data Mesh architecture, its real-world applications, and the keys to its successful adoption.
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 Observability
Prioritizing Data Observability: Why Now?
Five important reasons for why you should consider making data quality a priority now, instead of waiting until it becomes an issue.
May 15, 2023
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5
min read
Data Culture
Decision Guide to Choosing a Data Integration Tool
How to make the right choice in a market bursting with options
May 15, 2023
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6
min read
Data Observability
The Origins, Purpose, and Practice of Data Observability
Data observability is an emerging technology that solves an age-old problem: understanding the state of data systems to increase awareness and trust.
May 15, 2023
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9
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 Observability
The Four Pillars of Data Observability
How much data do we need to reconstruct a useful picture of our data? That’s the question we attempt to answer in this article. The groupings of questions we need to answer in order to describe our data are the “pillars” that underlie data observability in 2023.
May 10, 2023
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5
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 Observability
Data Observability in 10 years
Predicting the future of data observability: 10 years from now, automation and generic metadata will be key in incident management and data management.
April 27, 2023
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7
min read
Data Observability
Data Observability Defined
Data observability is vital for ensuring high-quality data and informed decision-making. We cover its benefits, challenges, and how it impacts businesses.
April 20, 2023
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4
min read
Changelog
Fivetran Integration
Modern data teams have increasingly complex and powerful solutions for making sure their data is exactly where it needs to be, when it needs to be there, and in the correct format. ELT tools like Fivetran hold a goldmine of useful information, including hints about the potential root causes for data issues that might have started upstream.Metaplane now integrates with Fivetran, giving our joint users a richer view into the makeup and health of their whole data ecosystem.
February 22, 2023
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2
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
The Most Common Misconceptions About Data Observability
As the new kid on the block, data observability often goes misunderstood. In this blog post, we strive to correct the misconceptions we hear most frequently.
September 14, 2022
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6
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 Culture
11 Data Leaders Worth Following in 2023
From 'Tech Bros talk Data Scams' to 'Thoughtful Data Modeling', here are 11 data leaders making waves in 2023.
May 23, 2022
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6
min read
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