Episode 71 : Google Cloud Next 19

13/04/2019    news cloud conference bigdata googlecloud 

Le slack est ouvert !
http://bit.ly/invitebdh

Lancement d’Anthos
https://cloud.google.com/blog/topics/hybrid-cloud/new-platform-for-managing-applications-in-todays-multi-cloud-world

Cloud Run
https://cloud.google.com/blog/products/serverless/announcing-cloud-run-the-newest-member-of-our-serverless-compute-stack

Compute-optimized VM + Memory-optimized VM
https://cloud.google.com/blog/products/compute/introducing-compute-and-memory-optimized-vms-for-google-compute-engine

Confluent
https://www.confluent.io/blog/announcing-confluent-cloud-for-apache-kafka-native-service-on-google-cloud-platform

Moving from Cassandra to Auto-Scaling Bigtable at Spotify
https://www.youtube.com/watch?v=Hfd3VZOYXNU
https://labs.spotify.com/2018/12/18/bigtable-autoscaler-saving-money-and-time-using-managed-storage/

Bigquery BI Engine
https://cloud.google.com/bi-engine/docs/

BigQuery Storage API
https://cloud.google.com/bigquery/docs/reference/storage/

Bigquery Flat rate pricing
https://cloud.google.com/bigquery/pricing#flat_rate_pricing

Bigquery streaming insert
https://cloud.google.com/blog/products/gcp/life-of-a-bigquery-streaming-insert

Bigquery ML : Kmeans
https://medium.com/@lakshmanok/how-to-use-k-means-clustering-in-bigquery-ml-to-understand-and-describe-your-data-better-c972c6f5733b

Bigquery ML with TF models
https://towardsdatascience.com/how-to-do-batch-predictions-of-tensorflow-models-directly-in-bigquery-ffa843ebdba6

Auto ML Tables
https://cloud.google.com/automl-tables/

Cloud Data Fusion
https://cloud.google.com/data-fusion/

Data catalog
https://cloud.google.com/data-catalog/

Document Understanding AI
https://cloud.google.com/solutions/document-understanding/

DAY 1 recap
https://cloud.google.com/blog/topics/inside-google-cloud/next19-recap-day1

DAY 2 recap

Toutes les vidéos https://www.youtube.com/user/googlecloudplatform/videos


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Nuage de tags

bigdata france spark cassandra cloud interview hadoop nosql kafka news apache data data-science googlecloud timeseries aws bigquery machine_learning sql azure google ia warp10 datascience flink french influxdb r cloudera database datalake kubernetes mapr mongodb opensource ovhcloud privacy redis 2019 ai analytics beam data-engineering dataflow datageek dataiku datastax elastic faq gpu grafana java machine-learning noel nvidia oss ovh postgresql pulsar python snowflake storage streaming thematique timescale timescaledb 2017 actu amazon anniversaire anomaly-detection apachespark apple arm astro benchmark bi biais carbondata cdc clever-cloud clickhouse cncf cnil cockroach cockroachdb conference consul couchbase dash data-engineer data-platform databases databricks datalakehouse datapreparation datasearch dataviz devoxxfr direct distributed docker druid entreprise4.0 facebook fb flows foundationdb francais fundings futur gdpr git gke hbase helm hfactory ibm industrie influx influxdata intellij istio jupyter k8s kaggle kalman-filter kappa kata-container knative kotlin kubeflow log medusa memsql mesos messaging metrics microsoftazure modèle-relationnel modélisation mpp mysql netflix nlp notebook nsa object-storage olap opacus opensourcesoftware paas pinot pixley podcast postgres presto process prometheus prophet prospective pub-sub pytorch rancher rapport-gauvain redhat reinvent rgpd rust-vmm s3 salesforce scikit-learn servicediscovery servicemesh software souveraineté-numérique spanner stargate streams synapse tech test the-last-pickle timestream u-sql ubeeko uber vm voix warehouse warp-10 zeppelin

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À compter de l'épisode 104, le générique a été composé et réalisé par Maxence Lecointe

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