Google Cloud Big Data and Machine Learning Blog
Innovation in data processing and machine learning technology
New Google Data Studio features give analysts quicker and broader access to data
Over the past six months we launched over 25 new features in Google Data Studio, now we're adding new features so you can access your data even faster.
Performing prediction with TensorFlow object detection models on Google Cloud Machine Learning Engine
Learn how to export a trained object detection model into the SaveModel format then how to deploy to Cloud Machine Learning Engine and perform prediction.
How to crunch your business data from Sheets in BigQuery
Google BigQuery can query Google Sheets just like any other table, allowing new collaborations and quicker insights.
The canonical new book about stream processing
We speak with Tyler Akidau, one of the authors of the O’Reilly Media book Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
From data to insights: Preview a new Google Cloud training course for SQL analytics
Get a preview of our new course From Data to Insights with Google Cloud Platform, which includes hands-on exercises using BigQuery and Google Data Studio.
Guide to using Google BigQuery on Microsoft PowerShell
Learn how to use PowerShell cmdlets that script to BigQuery commands straight from the PowerShell environment.
Analyzing errors in Cloud Dataflow with Stackdriver Error Reporting
Learn how you can use Stackdriver Error Reporting to monitor and debug your Cloud Dataflow jobs
Guide to common Cloud Dataflow use-case patterns, Part 2
Part 2 in our open-ended series that documents the most common patterns we've seen across production Cloud Dataflow deployments.
How Aucnet leveraged TensorFlow to transform their IT engineers into machine learning engineers
Learn how Aucnet uses deep learning to build a real-time car image recognition system powered by Tensorflow.
Easier integration with Apache Spark and Hadoop via Google Cloud Dataproc Job IDs and Labels
Learn best practices for using Google Cloud Dataproc Job IDs and Labels to integrate your apps with Apache Spark and Hadoop.
Hyperparameter tuning in Cloud Machine Learning Engine using Bayesian Optimization
Learn about HyperTune, hyperparameter tuning as a service, in Cloud Machine Learning Engine.
When art meets big data: Analyzing 200,000 items from The Met collection in BigQuery
This new public dataset allows you to build a custom machine-learning model, create an app for sorting and visualizing the images, and more.
Traveloka’s journey to stream analytics on Google Cloud Platform
Travel technology company Traveloka talks about migrating its streaming data processing pipeline to a multi-cloud solution including GCP data analytics.
How WePay uses stream analytics for real-time fraud detection using GCP and Apache Kafka
Learn how WePay built a new stream analytics pipeline for real-time fraud detection using Apache Kafka and Google Cloud Platform.
Life of a Cloud Dataflow service-based shuffle
Learn the practical impact of Google Cloud Dataflow's Shuffle on data pipelines using the Opinion Analysis project as an example.
Running external libraries with Cloud Dataflow for grid-computing workloads
Learn how Cloud Dataflow used in conjunction with other GCP services can unlock parallel workloads.
Cloud Dataproc is now even faster and easier to use for running Apache Spark and Apache Hadoop
Learn about Cloud Dataproc 1.2, which includes software component updates, environment configuration changes and YARN changes.
New hands-on labs for scientific data processing on Google Cloud Platform
Try out 7 labs which can teach scientists how to use Google Cloud products and services to support their professional goals.
Google Cloud Platform for Data Scientists: Using R with Google BigQuery, Part 2 (storing and retrieving data frames)
Learn how to create an R data frame and stash it in BigQuery using bigrquery.
Moving Thumbtack’s data infrastructure to Google Cloud Platform
Learn how Thumbtack ramped up GCP usage from a few BigQuery tables to include all of its data infrastructure, a move resulting in big productivity gains.
How to aggregate data for BigQuery using Apache Airflow
Users of Google BigQuery, the cloud-native data warehouse service from GCP, have access to an ever-expanding range of public datasets for exploration.
After Lambda: Exactly-once processing in Cloud Dataflow, Part 3 (sources and sinks)
The series concludes with a description of how exactly-once processing in Cloud Dataflow is supported by sources and sinks.
Counting uniques faster in BigQuery with HyperLogLog++
Learn how BigQuery uses HyperLogLog++, Google’s internal implementation of the HyperLogLog algorithm for cardinality estimation.
Get on track to becoming a Google Certified Professional Data Engineer
Get tips on preparing for the exam to become a Google Certified Data Engineer. Show prospective employers you have the skills to build and scale on GCP.
Cloud Machine Learning Perception services updates: Cloud Video Intelligence enters beta and Cloud Vision gets new features
Cloud Video Intelligence beta is now open to all. Now Google Cloud Platform users can use Cloud Video Intelligence API to understand their video content.
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