3 Lines Of Python To Create Timezone-Aware Pipelines
Building time-sensitive data pipelines is a challenge; luckily, there is a way to build localized pipelines with 3 lines of Python.
Building time-sensitive data pipelines is a challenge; luckily, there is a way to build localized pipelines with 3 lines of Python.
Avoid GCP 401 errors — and security concerns — by passing project credentials into your Docker image the right way.
Leverage the Python Google Cloud Storage and BigQuery APIs to bulk download, transform and upload CSV files in < 1 minute.
Either afraid or stuck in old habits, new engineers fail to ask important probing questions; how devs can think critically.
How to use Python to read multi-page PDFs, transform unstructured data and SQL to format the final result in BigQuery.
Set up a virtual environment, install Python & pip and run Python scripts in a Google Cloud Compute Engine virtual machine.
Distinguishing between Google Cloud Platform and a typical API’s authentication process emphasizes the need for secure credential storage.
Leverage BigQuery SQL table metadata to deduplicate, partition and delete data — all using only one word.
Covering GitHub versioning, CI/CD pipeline development and scheduling jobs within Google Cloud Platform.
A risk-averse approach to “flipping the switch” from test tables to production tables featuring a subtle BigQuery SQL function.
How data engineers can set realistic development expectations and respond to impatient stakeholders.
Convert PDFs to CSVs in an unusual–but practical–use case of real-life data engineering problem-solving.