In Data We Trust

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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
What is Data Consistency? Definition and Examples
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.
September 27, 2022
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2
min read
The Ultimate Data Observability Playbook: Best Practices for Data Engineers
If you already know data observability would benefit your company, but don't how to evaluate, buy, and implement it, this blog post is for you.
September 21, 2022
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9
min read
What is Data Completeness? Definition and Examples
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.
September 19, 2022
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2
min read
Should You Buy, Borrow, or Build a Data Observability Tool?
If you're ready to adopt data observability but don't know which path to take, this post is for you. Discover the benefits, costs, and risks of building a tool from scratch, leveraging open-source software, and buying a commercial solution.
September 15, 2022
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6
min read
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
What Is Data Accuracy? Definition and Examples
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.
September 12, 2022
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3
min read
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
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.
September 7, 2022
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5
min read
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.
September 6, 2022
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8
min read
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.
August 17, 2022
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5
min read
Data Observability vs. Software Observability
Overview of the similarities and differences between the established field of Software Observability and the emerging category of Data Observability.
August 11, 2022
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12
min read
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.
August 11, 2022
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5
min read
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
Proxy and Practicality
Jason's post on AE roundup inspired so many ideas that they have overflowed into a post.
August 9, 2022
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5
min read
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.
August 4, 2022
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9
min read
A Framework to Understand How Low-Quality Data 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.
July 25, 2022
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4
min read
Announcing the First Snowflake-Native Data Observability Application
Snowflake debuted their native application framework at Summit 2022, which is poised to change how software is deployed on top of data. Metaplane has built the first data observability application that can be deployed directly within your Snowflake instance, for enhanced security and ease-of-adoption.
July 19, 2022
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3
min read
Introducing Snowflake Table and Column Usage Analytics
It’s easier than ever to ETL data, but harder than ever to understand who or what is using this data. Metaplane now monitors table and column level usage analytics for Snowflake customers so you can better understand how critical data is used, what should be tested, and how to prioritize data quality issues.
April 14, 2022
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4
min read
Announcing Warehouse To BI Tool Data Lineage
Learn about Metaplane's warehouse to BI tool data lineage visualization tool and how you can build data awareness, prevent downstream BI issues, and decrease data debt.
April 5, 2022
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3
min read
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
How to Maximize the Value of Your Metadata
Practical guide to using metadata effectively and assessing metadata-driven tools like discovery and observability offerings.
January 19, 2022
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10
min read
Decision Guide to Choosing a Data Integration Tool
How to make the right choice in a market bursting with options
December 13, 2021
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6
min read
How to Evaluate Data Observability Tools
A framework for data practitioners to evaluate data observability and quality monitoring tools.
December 9, 2021
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6
min read
How To Become A Great Data Analyst
Starting as a data analyst can be intimidating, but it doesn't have to be! Lucas Smith shares six steps you can take to become a great data analyst.
October 14, 2021
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15
min read
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.
September 24, 2021
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15
min read
How To Justify Investing in Data Observability
The four most common reasons for how data leaders justified an investment into data observability, spanning concrete to intangible (but still critical) reasons.
August 30, 2021
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6
min read
Inside Data with Ben Cohen @ SpotOn
We interview Ben Cohen, a seasoned data leader from Cars.com, Braintree, Cameo, and now SpotOn.
August 26, 2021
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6
min read
Announcing SOC 2 Type II Compliance
Security has been a priority from Day One, now affirmed with a SOC 2.
July 22, 2021
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2
min read
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.
July 20, 2021
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5
min read

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