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"Extract, transform, load" (ETL) is at the center of every application of data, from business intelligence to
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Build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and Kafka Key Features Develop modern da
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Learn to build scalable and reliable data ecosystems using Data Mesh, Databricks Spark, and Kafka. Key Features Develop
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Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project
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Develop production-ready ETL pipelines by leveraging Python libraries and deploying them for suitable use cases Key Fea
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Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. T
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Proactive strategies for ensuring data accuracy and addressing broken data pipelines
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All cloud architects need to know how to build data platforms—the key to enabling businesses with data and delivering en
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Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and mo
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