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GCP vs AWS Data Warehousing and Analytics: Which Service to Pick?
Data warehousing on AWS and Google Cloud a comprehensive comparison
Utilizing ClickHouse to Reduce Costs from Your BigQuery and Looker Usage Part 1
Reduce your Looker and BigQuery Costs by Utilizing Clickhouse to “cache” your data
Transitioning from BigQuery Flat-Rate Commitments: A Guide to Editions & On-Demand
How to smoothly transition your expiring BigQuery flat-rate commitments to a different pricing plan, and keep your usage optimized afterward.
Leverage Malloy and Looker for a Unified, Future-Proof Data Warehouse
SQL has downsides that limits collaboration around analyzing complex datasets. Here's how Malloy addresses SQL's faults to help you operate at scale.
BigQuery Editions and What You Need to Know
Comprehensive Guide to the Changes on BigQuery Compute from BigQuery Editions Announcement
BigQuery — keep fresh data while avoiding large-scale mutations
Avoid merge or join and use deduplication and clone in large dataset updates
The BigQuery Autoscaling Public Preview Rundown (DoiT Edition)
Author’s note: Google announced on March 29, 2023 that they are rolling out a completely new billing model for BigQuery that includes, and…
Identifying your costliest BigQuery queries
In an edited excerpt from a series on optimizing BigQuery costs and performance, we explore how to identify the queries in your environment that are incurring the most costs.
Avoiding eight common BigQuery query mistakes
If you want to speed up your query processing and reduce the costs involved, you should avoid these eight common mistakes.
BigQuery Optimizations (Part 2)
Primer on BigQuery Cost and Performance Optimizations
Prepare to take control of your BigQuery costs
BigQuery is a versatile data warehouse that helps you turn big data into valuable insights – but you can run up costs fast. In the first of a series of detailed guides, we show you how to use it efficiently.