Systems | Development | Analytics | API | Testing

Monitoring in BigQuery

Want to ensure that your BigQuery environment stays cost effective and secure? In this episode of BigQuery Spotlight, we’ll examine how monitoring your data warehouse can optimize costs, help you pinpoint which queries need to be optimized, and audit both data-sharing and access. Watch to learn how BigQuery gives you the flexibility to export any of these data sources back into your data warehouse for custom reporting.

The top 10 books every data and analytics leader must read

In the final episode of season two of The Data Chief podcast, we talk with authors of four must-read books for data and analytics leaders — two new and two time-tested. As you invest in your continuous learning, here is the full round up of the latest top books I recommend for today’s data and analytics leaders.

How Renault solved scaling and cost challenges on its Industrial Data platform using BigQuery and Dataflow

French multinational automotive manufacturer Renault Group has been investing in Industry 4.0 since the early days. A primary objective of this transformation has been to leverage manufacturing and industrial equipment data through a robust and scalable platform. Renault designed an industrial data acquisition layer and connected it to Google Cloud, using optimized big data products and services that together form Renault's Industrial Data Platform.

Speed the Path to Vastly More Data Insights With Pentaho 9.2 and DataOps

In our modern world, accelerating the process of extracting insights from data is a complex challenge. Exacerbating this task are colossal data volumes, the expansion and use of multiple cloud platforms, and the increasing demands for self-service in a way that maintains compliance. Enterprises attempting to tackle the problem encounter various forms of friction everywhere they turn.

The Journey to Processing PII in the Data Cloud

During the process of turning data into insights, the most compelling data often comes with an added responsibility—the need to protect the people whose lives are caught up in that data. Plenty of data sets include sensitive information, and it’s the duty of every organization, down to each individual, to ensure that sensitive information is handled appropriately.