
dbt Projects Integration in Databricks Workflows
In this video, Olya from Databricks reviews how to automate dbt tasks, integrate project into larger workflows, and monitor dbt transformation.
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dbt Core and the Lakehouse
From Databricks‘ YouTube channel Previously, Olya walked through how the dbt-Databricks adapter enables Data Analysts to build, test, and deploy data models on Delta Lake. Additionally, Databricks can also connect to open-source dbt Core to run dbt Core projects as a task in a Databricks job. This allows you to automate your dbt tasks, include […]
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AWS Glue 5th Anniversary Developer Retrospective | Amazon Web Services
AWS Glue serverless ETL and Data integration service celebrates its 5th anniversary. Watch this video to meet the engineers who built Glue from the ground-up, and hear their vision for Glue’s future.
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Azure Synapse Full Course
- Frank
- December 6, 2021
- Azure
- Azure Data lake
- Azure Synapse
- Azure Synapse Analytics
- azure synapse analytics tutorial
- Big Data analytics
- Cloud
- Data flows
- Data Science
- Data Warehousing
- ETL
- intro to azure synapse analytics
- Learn with the nerds
- Microsoft
- mitchell pearson
- Power BI integration
- SQL Pools
- Synapse notebooks
- Training
Azure Synapse Analytics (ASA) is changing the way we work with data services in Azure. The ASA workspace combines the core technologies required for data warehousing, Big Data Analytics and Data Science. In this Learn with the Nerds event, Mitchell Pearson will teach you how you can use Synapse Analytics to solve the paradox of […]
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Data Science and Predictive Analytics with Azure Synapse
Discover new Azure Synapse features to integrate predictive analytics capabilities into your organization—using both code-free and code-first options for AI/ML.
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How Databricks Leverages Auto Loader to Ingest Millions of Files an Hour
- Frank
- August 31, 2021
- Databricks
- ETL
Continuously and incrementally ingesting data as it arrives in cloud storage has become a common workflow in our customers’ ETL pipelines. However, managing this workflow is rife with challenges, such as scalable and efficient file discovery, schema inference and evolution, and fault tolerance with exactly-once guarantees. Auto Loader is a new Structured Streaming source in […]
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Empowering Zillow’s Developers with Self-Service ETL
Databricks shows how their tech empowers Zillow’s developers via self-service ETL. These tools abstract away the orchestration, deployment, and Apache Spark processing implementation from their respective users. In this talk, Zillow engineers discuss two internal platforms they created to address the specific needs of two distinct user groups: data analysts and data producers. Each platform […]
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The Modern Data Warehouse in Azure – Data Processing
In this video, Chris Seferlis continues discussing the Modern Data Platform in Azure with Part 3: Data Processing. Tools Discusssed: Azure Data Factory Data Flows – https://docs.microsoft.com/en-us/azure/data-factory/concepts-data-flow-overview Azure Databricks – https://azure.microsoft.com/en-us/services/databricks/ Azure HDInsight – https://azure.microsoft.com/en-us/services/hdinsight/ Azure Marketplace – https://azuremarketplace.microsoft.com/en-us/marketplace/
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How to Build a Cloud Data Platform with Databricks Part 2 – ETL Processing
Learn how to use Apache Spark and Delta Lake on Databricks to perform ETL processing, manage late arriving data, and repair corrupted data. Companies look to support both business analytics and machine learning initiatives within their organization, but often face challenges with complex operations, proprietary technologies, and unreliable data.
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