Want to master data quality best practices? Join the upcoming hands-on workshop from GX. In this practical session, you'll learn how to: - Implement automated data testing - Catch issues before they impact your business - Build trust in your data pipelines Perfect for data engineers, analysts, and scientists at any experience level. Save your seat ?? https://lnkd.in/gr5gN-P3
关于我们
We're helping data teams have confidence in their data, no matter what. GX Cloud is our end-to-end platform for managing your data quality process. It delivers the intuitive experience of a fully managed SaaS solution while harnessing the power of the world's most popular data quality framework. With GX Cloud, data teams can work quickly, collaborate effectively, and always know what to expect from their data. GX Core is our open source Python offering, and the world's most popular data quality framework. It's a powerful, flexible data quality solution that empowers data teams to communicate better and take action effectively. At its heart are Expectations: verifiable assertions about your data that create clear and expressive data quality tests.
- 网站
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https://greatexpectations.io
Great Expectations的外部链接
- 所属行业
- 软件开发
- 规模
- 11-50 人
- 总部
- Remote
- 类型
- 私人持股
- 创立
- 2017
- 领域
- data science、data engineering、data pipelines、pipeline debt、data quality、data monitoring、MLOps、data observability 和AI
地点
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主要
获取路线
US，Remote
Great Expectations员工
动态
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If you’ve ever built a data pipeline, you’ve probably run into data quality issues. With a whole gallery of built-in data quality checks, you can seamlessly validate your data and ensure trust in your pipelines. Check out Matt Dixon's post for a helpful guide and the Expectation Gallery to get started. #dataquality #bigquery #datatrust
Great Expectations & BigQuery - DQ at scale. Chances are if you have written a data pipeline at any sort of scale you have run into data quality issues. Well, this is one way to combat these issues. I am a huge fan of Great Expectations and have written DQ suites on top of this package before. There is a whole gallery of standard checks now and it connects natively to #BigQuery! I recommend you give this package a try in your pipelines. I would love to hear your thoughts!?? As always, a helpful guide to get you going is?included below?for reference, along with a link to the?Expectation Gallery. Great Expectations & BigQuery --> https://lnkd.in/ey6yXX2i Expectation Gallery --> https://lnkd.in/erQadB8F Until next time… ? https://lnkd.in/endWQ-CG #GreatExpectations #BigQuery #GCP #DataQuality #DataEngineering
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Great news for data practitioners! If you're using Apache Airflow and Great Expectations, your workflows just got a whole lot smoother. The GX Airflow provider, maintained by Astronomer, is now available, making it easier than ever to integrate data quality checks directly into your DAGs. With GX Core 1.3.9, you can: ? Choose the right operator? ? Streamline your pipeline orchestration ? Ensure data quality at every step, without the hassle Check out the blog for all the details on how to get started https://lnkd.in/gfAtJKU6
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?? Happy St. Patrick’s Day! ?? No need to search for a pot of gold, we’ve got something even better! ??? The latest What's New in GX blog is here, packed with magically good updates you won’t want to miss. - New features to make your data quality workflows luckier than ever - Enhancements that’ll have you clapping like an Irish jig - GX Core highlights and more! Don’t rely on luck alone, check out what’s new and see how GX is making data quality your lucky charm. ?? Read the blog here: https://lnkd.in/dd6pszc3 #dataquality #GX # #whatsnew
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?? Spring Forward with GX! ?? Daylight saving time isn’t the only way to get ahead this season—it's the perfect moment to level up your data quality game! Join us for a hands-on GX Cloud workshop and start validating with confidence. ?? Secure your spot now https://lnkd.in/gr5gN-P3
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?? Taming Data Duplication for Better Decision-Making Data quality is everything. If you can’t trust your data, you can’t trust your decisions, and duplication is one of the biggest culprits eroding that trust. Join Nevin Tan, GX Senior Developer Advocate, on March 18th at 9 am PT/ 12 pm ET for a fast-paced, 25-minute session where he’ll break down: ? How data duplication happens (and why it’s so sneaky) ? How to detect duplicates within tables & rows ? How to collaborate effectively when duplication strikes Don’t let bad data derail good decisions. Sign up now and take control of your data quality https://lnkd.in/gV8e_SJ6
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No more guesswork: GX Cloud now auto-detects schema & volume changes, runs 24/7 monitoring, and flags issues instantly ?. Stay ahead of data issues with zero setup — just smarter, seamless anomaly detection. Try it now: https://lnkd.in/gK3DTj-x #dataquality #anomalydetection #GXCloud
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How unique is your data? Duplicate records, unexpected overlaps, and missing distinct values can derail your analytics and decision-making. But how do you systematically check for uniqueness at scale? Our blog explores why uniqueness matters in data quality and how to catch issues before they become problems. Don't let duplicates compromise your insights. Learn how GX's built-in uniqueness validators simplify enforcing data integrity across your entire pipeline. https://lnkd.in/gCdzruSz
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Want to see GX Cloud in action? ?? Don’t miss our last hands-on workshop of February! Learn how to streamline your data quality workflows, write Expectations, and gain real-time validation insights—all in just 30 minutes. Save your spot now! ?? https://lnkd.in/gr5gN-P3
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AI is only as good as the data it learns from. Garbage in, garbage out. Bad data isn't just an inconvenience—it can completely derail your AI projects. Yet most teams only discover quality issues after deployment. Costly mistake. Enter Great Expectations (GX): Your first line of defense against data problems. ? Catch data anomalies before they reach your models ? Automate distribution validation ? Implement smart training data guardrails Ready to level up your AI data quality? https://lnkd.in/gNjuYF59