You know Python is essential for a data engineer. Does anyone know how much one should learn to become a data engineer? When you're in an interview with a hiring manager, how can you effectively demonstrate your Python proficiency? Imagine knowing exactly how to build resilient and stable data pipelines (using any language). Knowing the foundational ideas for data processing will ensure you can quickly adapt to the ever-changing tools landscape. In this post, we will review the concepts you n...| www.startdataengineering.com
Data engineering project for beginners, using AWS Redshift, Apache Spark in AWS EMR, Postgres and orchestrated by Apache Airflow.| www.startdataengineering.com
Struggling to come up with a data engineering project idea? Overwhelmed by all the setup necessary to start building a data engineering project? Don't know where to get data for your side project? Then this post is for you. We will go over the key components, and help you understand what you need to design and build your data projects. We will do this using a sample end-to-end data engineering project.| www.startdataengineering.com
So you know how it can be overwhelming to choose the right tools for your data pipeline? What if you knew the core components involved in any data pipeline and can always pick the right tools for your data pipeline? Now you can! Use this framework to choose the best tool for your data pipeline.| www.startdataengineering.com
This post goes over what the ETL and ELT data pipeline paradigms are. It tries to address the inconsistency in naming conventions and how to understand what they really mean. Finally ends with a comparison of the 2 paradigms and how to use these concepts to build efficient and scalable data pipelines.| www.startdataengineering.com
Unsure how to load data into a data warehouse? Then this post is for you. In this post, we go over 4 key patterns to load data into a data warehouse. These patterns can help you build resilient and easy-to-use data pipelines. Level up as a data engineer and deliver usable data faster!| www.startdataengineering.com
Frustrated with handling data type conversion issues in python? Then this post is for you. In this post, we go over a reusable data type conversion pattern using Pydantic. We will also go over the caveats involved in using this library.| www.startdataengineering.com
Confused by all the tools and frameworks available to scale your data pipeline? Then this post is for you. In this post, we go over what scaling is, the different types of scaling, and how to choose scaling strategies for your data pipelines. By the end of this post, you will be able to come up with the correct scaling strategy for any data pipeline.| www.startdataengineering.com