Hey @kazinahian
I completely understand your hesitation and appreciate your approach to seeking guidance! Embarking on a learning journey can be daunting, especially when financial considerations are involved. I'm happy to offer some advice on building a hands-on data pipeline with cost-effective options:
Platforms for Learning Data Pipelines:
- Databricks Community Edition: This is a fantastic starting point! It offers a limited runtime environment for exploring notebooks and running short jobs, perfect for learning the basics.
- A few other options could be - Google Colab, Kaggle Kernels, or Local Development
Building a Data Pipeline within Databricks Community Edition:
- Follow tutorials and sample notebooks: Databricks provides numerous resources to guide you through building your first data pipeline. Start with introductory tutorials and progress to more complex examples as you gain confidence. (https://docs.databricks.com/en/getting-started/data-pipeline-get-started.html)
- Utilize sample datasets: The platform offers free access to sample datasets, allowing you to practice without needing your own data.
- Focus on core concepts: While free resources might have limitations, they're excellent for learning fundamental data pipeline concepts like data ingestion, transformation, and loading.
Addressing Your Concerns:
- Azure Free Account: You can create a free Azure account with $200 credit, which should suffice for basic learning on their data services like Synapse Analytics or Databricks. However, monitor usage to avoid exceeding free limits.
- PRO TIP: Always shut off your running clusters/jobs remember it is a pay-per-use business so you'll only be charged if you use any of their services.
Leave a like if this helps, followups are appreciated.
Leave a like if this helps! Kudos,
Palash