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@@ -18,7 +18,7 @@ There are 4 main components of Deequ, and they are:
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## 🎉 Announcements 🎉
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-**NEW!!!**As of 06/19, 1.1.0rc0 of Python Deequ is published https://github.com/awslabs/python-deequ/releases/tag/v1.1.0rc0. We will bake for around 2 weeks. Any feedbacks are welcome through github issues.
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-**NEW!!!** 1.1.0 release of Python Deequ has been published to PYPI https://pypi.org/project/pydeequ/. This release brings many recency upgrades including support up to Spark 3.3.0! Any feedbacks are welcome through github issues.
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- With PyDeequ v0.1.8+, we now officially support Spark3 ! Just make sure you have an environment variable `SPARK_VERSION` to specify your Spark version!
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- We've release a blogpost on integrating PyDeequ onto AWS leveraging services such as AWS Glue, Athena, and SageMaker! Check it out: [Monitor data quality in your data lake using PyDeequ and AWS Glue](https://aws.amazon.com/blogs/big-data/monitor-data-quality-in-your-data-lake-using-pydeequ-and-aws-glue/).
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- Check out the [PyDeequ Release Announcement Blogpost](https://aws.amazon.com/blogs/big-data/testing-data-quality-at-scale-with-pydeequ/) with a tutorial walkthrough the Amazon Reviews dataset!
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