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Recce Blog

Updates, articles, and insights from the Recce team

  • Trace, Debug, Deliver: June Updates from Recce

    Discover what’s new at Recce. From powerful column-level lineage for tracing data impact to the new recce debug command for quick troubleshooting. Catch up on features, blog posts, and events.

  • Why High Quality Data Can Still Be Wrong

    Data quality is often used as a catch-all term for rating ‘good data’ but, in practice, data quality is more concerned with the structural integrity and completeness of data, rather than the correctness of the data. It’s possible for data to be of high quality, but fundamentally incorrect.

  • A Practical Guide to Generating a Time Spline (dim_dates) in dbt

    Learn how to replace slow-loading CSV seeds with a performant macro-based approach for managing your dim_dates table in dbt. This practical guide walks through creating a time spline using run-operation, helping your team speed up builds and version-control logic, not data.

  • When You Need More Than Just a Data Diff

    Discover why relying solely on data diffs can lead to noise, missed issues, and wasted resources. Learn how Recce emphasizes context, scoping, and human judgment to enhance data validation workflows.

  • Announcing Recce 1.0 with Cloud beta

    Recce gives data teams a faster, more reliable way to understand, review, and ship changes without all the guesswork or manual overhead.

  • Trust Issues: Rebuilt Stakeholder Confidence

    While investigating an issue initially raised by marketing, the Jaffle Shop data team discovered something bigger: revenue numbers were wrong, and had been for a while. Regaining confidence required transparency, context, and hours of manual effort: SQL tracing, ad-hoc queries, spreadsheet exports, and slow back-and-forth with stakeholders.Using Recce, the team can instead now investigate in under 10 minutes, show what changed, and align with business stakeholders in one shared view.

  • Meet Recce at Data Council

    Recce is attending DataCouncil 2025 in Oakland, CA. We want to connect and discuss data quality, impact analysis, and how to improve the data PR review process.

  • Recce Is Now SOC 2 Type 1 Compliant

    Recce has achieved SOC 2 Type 1 compliance, reinforcing our commitment to data security, confidentiality, and reliability—ensuring confidence in your data workflows.

  • Recce - Your data change management toolkit

    With Recce you’re able to validate your data modeling changes against a known-good baseline, comparing datasets before and after your modifications, in a risk-free environment. And there’s a diff for every occasion.

  • Support Self-Serve Data with Comprehensive PR Review

    dbt helps to apply software engineering (DevOps) best practices to data pipelines. With proper adoption and application of these practices as Dataops it is possible to support a self-serve data and analytics culture, while still maintaining data integrity through systematic data validation and PR review.

  • Explore data impact and data validations

    Recce's updated interface lets you stay on track while assessing and exploring data impact in your dbt project when making dbt data model changes, and performing dbt PR review.

  • The Ultimate PR Comment Template for data projects

    A PR comment template for dbt projects is essential for streamlining the pull request process, ensuring that both authors and reviewers are aligned on what changes have been made and how those changes have been validated.

  • Meet Recce at Coalesce 2024 and The Data Renegade Happy Hour

    Recce is attending Coalesce 2024 in Las Vegas to connect with the data community and discuss solutions for data quality, impact analysis, and improving the data PR review process. We are also co-hosting the Data Renegade Happy Hour, a fun networking event with data companies like Tobiko, Cube, Paradime.io, Datacoves, and Steep.

  • From DevOps to DataOps: A Fireside Chat

    Joined with industry experts CL Kao and Noel Gomez in a fireside chat exploring the evolution from DevOps to DataOps. Discover practical strategies for improving data productivity, reducing errors, and enhancing data quality. Learn how to apply software best practices to data management for more effective decision-making. Sign up for the full video recording to gain insights on modern DataOps workflows.

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