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The systematic collection and transformation of data via the creation of tools and pipelines.
Cleaning PySpark DataFrames
Easy DataFrame cleaning techniques, ranging from dropping problematic rows to selecting important columns.
Learning Apache Spark with PySpark & Databricks
Get started with Apache Spark in part 1 of our series, where we leverage Databricks and PySpark.
Building an ETL Pipeline: From JIRA's REST API to SQL
Build a pipeline which extracts raw data from the JIRA's Cloud API, transforms it, and loads the data into a SQL database.
Working With GraphQL Fragments and Mutations
Make your GraphQL queries more dynamic with Fragments, plus get started with Mutations.
Building a Client For Your GraphQL API
Now that we have an understanding of GraphQL queries and API setup, it's time to get that data.
Writing Your First GraphQL Query
Begin to structure complex queries against your GraphQL API.
Welcome to SQL: Modifying Databases and Tables
Brush up on SQL fundamentals such as creating tables, schemas, and views.
Google BigQuery's Python SDK: Creating Tables Programmatically
Explore the benefits of Google BigQuery and use the Python SDK to programmatically create tables.
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