Data Intelligence for Financial Services | Databricks
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hevodata.com
What started as a hackathon prototype is now how Databricks infrastructure engineers debug thousands of OLTP databases at scale. The team built an AI agent platform that unifies metrics and logs into a single investigation flow, replacing manual debugging with guided reasoning. This has reduced debugging time by up to 90% and lowered the learning curve for new engineers. See how: https://www.databricks.com/blog/how-we-debug-1000s-databases-ai-databricks?utm_source=facebook&utm_medium=organic-soc
0:07
What started as a hackathon prototype is now how Databricks infrastructure engineers debug thousands of OLTP databases at scale. The team built an AI agent platform that unifies metrics and logs into a single investigation flow, replacing manual debugging with guided reasoning. This has reduced debugging time by up to 90% and lowered the learning curve for new engineers. See how: https://www.databricks.com/blog/how-we-debug-1000s-databases-ai-databricks?utm_source=facebook&utm_medium=organic-soc
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FacebookDatabricks
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FacebookDatabricks
The IDE for Data Engineering is everything you need to author and test data pipelines, directly inside the Databricks Workspace. The IDE is designed to improve productivity and debugging with features like dependency graphs, built-in data previews and execution insights. Now available in Public Preview for Lakeflow Spark Declarative Pipelines: https://www.databricks.com/blog/new-way-build-pipelines-databricks-introducing-ide-data-engineering?utm_source=facebook&utm_medium=organic-social | Databr
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The IDE for Data Engineering is everything you need to author and test data pipelines, directly inside the Databricks Workspace. The IDE is designed to improve productivity and debugging with features like dependency graphs, built-in data previews and execution insights. Now available in Public Preview for Lakeflow Spark Declarative Pipelines: https://www.databricks.com/blog/new-way-build-pipelines-databricks-introducing-ide-data-engineering?utm_source=facebook&utm_medium=organic-social | Databr
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FacebookDatabricks
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Nobody tells you this about becoming a data engineer: You think your job will be: writing SQL, building pipelines, coding all day Reality? It’s more like talking to business stakeholders who don’t really know what they want, figuring out what data product they actually need, translating vague ideas into real systems, building something… then changing it 3 times. On top of that:, fixing broken pipelines and issues (almost everyday), dealing with messy, inconsistent data, debugging systems instead
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