Swipe Insight Swipe Insight Logo
Axel Thevenot

Axel Thevenot

Open source LinkedIn

France

2 Swipes

About

Axel is a seasoned cloud solutions architect with extensive experience in designing and implementing scalable cloud infrastructures. He specializes in Google Cloud Platform and has a strong background in DevOps practices. Axel is passionate about leveraging cloud technologies to drive business transformation and efficiency. He is committed to continuous learning and staying updated with the latest industry trends.

Top Topics

Achievements

Coming Soon 🤞

Swipes

BigQuery Introduces Code-Free Workflow Tool for Streamlined Data Management Trending ️‍🔥

BigQuery Introduces Code-Free Workflow Tool for Streamlined Data Management

5 months ago

BigQuery

Google has unveiled BigQuery Workflows, a new code-free orchestration tool for BigQuery, now in preview. It simplifies data pipeline management with a visual interface, built-in scheduling, centralized monitoring, flexibility, and cost-effectiveness. Users can create sequences of code assets like notebooks and SQL queries. Limitations include creating new assets within the workflow, no access grants for specific workflows, and availability only in Google Cloud.

Top-Notch Google Ads Audit Tool

Top-Notch Google Ads Audit Tool

Featured

Effortlessly audit your Google Ads account with Marketing Auditor. Perform 200+ automated checks to uncover optimization opportunities and save over 10 hours per audit. Generate white-label reports in minutes with 50+ pages of actionable insights. Customize your reports with professional themes or your own branding, and export them in editable formats like PowerPoint or Google Slides. This tool is the ultimate solution for efficient and impactful Google Ads audits.

BigQuery Increases Maximum Partitions Per Table from 4000 to 10000

BigQuery Increases Maximum Partitions Per Table from 4000 to 10000

9 months ago

BigQuery

Now, the maximum number of partitions by table in BigQuery has increased from 4000 to 10000. Partitioned tables are divided into segments called partitions. Specifying a partition column allows you to run queries over those partitions to scan only the relevant data, improving performance and reducing costs. BigQuery supports three types of partitions: Integer Range Partitioning, Time-Unit Column Partitioning, and Ingestion Time Partitioning.