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How to get started with dbt

Christophe Blefari

dbt Labs also develop dbt Cloud which is a cloud product that hosts and runs dbt Core projects. dbt was born out of the analysis that more and more companies were switching from on-premise Hadoop data infrastructure to cloud data warehouses. With the public clouds—e.g. The company has been founded in May 2016.

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Azure Cloud Practitioner Resume Example for 2023 + Templates

Knowledge Hut

If you are looking for an Azure Cloud job you are at the right place! In this article, I will share some tried and tested tips and tricks that you can use in your AWS cloud practitioner resume which might help you crack your dream job. Windows Azure, is Microsoft's public cloud computing platform.

Cloud 52
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Upgrade Journey: The Path from CDH to CDP Private Cloud

Cloudera

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Review the Upgrade document topic for the supported upgrade paths.

Cloud 131
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dbt Core, Snowflake, and GitHub Actions: pet project for Data Engineers

Towards Data Science

Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution. There are two ways to access dbt: dbt Cloud and dbt Core. dbt Cloud is a paid cloud-based version of the service and dbt Core is a python package providing all functionality you can use for free.

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ConsoleMe: A Central Control Plane for AWS Permissions and Access

Netflix Tech

We’re very excited to bring you ConsoleMe (pronounced: kuhn-soul-mee ), and its CLI utility, Weep (pun intended)! Motivation Growth in the cloud has exploded, and it is now easier than ever to create infrastructure on the fly. They are the one-stop-shop for cloud permissions and access. This happened for us at Netflix.

AWS 100
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Enforcing rules at scale with pre-commit-dbt

dbt Developer Hub

If we are using dbt Cloud, let’s jump to step 4 , where we will set up pre-commit-dbt as part of the CI process, otherwise, with dbt Core we can go to step 2. If not, we should really create a Python virtual environment ( more info here ) and activate it before installing pre-commit. We will cover this in step 4.

Python 52
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Building CI/CD with Airflow, GitLab and Terraform in GCP

Ripple Engineering

These are pretty standard DevOps requirements, and to achieve them, our team implemented a Continuous Integration Continuous Deployment (CI/CD) approach for our data applications in Google Cloud Platform (GCP). For more information about how to adjust the settings for the linters, see flake8-docs and isort-docs.