Google's Big Daddy Update: Big Changes to Google's Infrastructure & the SERPs
Google's Big Daddy was a major infrastructure update that began rolling out in December 2005 and had a big impact on the overall quality of SERPs.
How Salesforce and Google Cloud Platform are simplifying big data
See how Salesforce and Google are joining forces to simplify Big Data. Google Cloud Dataflow makes it easier than ever to process and enrich data, without ETL or data prep tools. Now you can push data directly to Wave Analytics and explore it on any device.
Choose your database on Google Cloud
In this GCP Sketchnote, I sketch a quick overview of Google Cloud Databases across relational, non-relational and in-memory databases.
You will learn to pick a database from based on your use case:
Cloud SQL, Cloud Spanner, Bigtable, Firestore, Memorystore and Bare Metal solution.
Playlist – https://bit.ly/3jA8Ylz
Spanner Blog – https://goo.gle/3zmQMnj
Bigtable Blog – https://goo.gle/2TV3hWY
Firestore Blog – https://goo.gle/3i1yQGX
GitHub Repo – https://github.com/priyankavergadia/GCPSketchnote
Visit my website to download the sketchnote image – https://thecloudgirl.dev/
Follow me on Twitter – https://twitter.com/pvergadia
Follow me on Instagram – https://www.instagram.com/pvergadia/
Follow me on LinkedIn – www.linkedin.com/in/priyankavergadia
#GCPSketchnote #GooogleCloud #gcp #sketchnote #database
GCP Course Overview & Agenda – Google Cloud Platform Big Data and Machine Learning Fundamentals #2
This video is part of an online course, Google Cloud Platform Big Data and Machine Learning Fundamentals from Google Cloud. Enroll today at https://www.coursera.org/learn/gcp-big-data-ml-fundamentals?utm_source=yt &utm_medium=social &utm_campaign=channel &utm_content=googlecloud to get access to the full course.
About this course:
This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
At the end of this course, participants will be able to:
• Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
• Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
• Employ BigQuery and Cloud Datalab to carry out interactive data analysis
• Choose between Cloud SQL, BigTable and Datastore
• Train and use a neural network using TensorFlow
• Choose between different data processing products on the Google Cloud Platform
Visit https://www.coursera.org/learn/gcp-big-data-ml-fundamentals?utm_source=yt &utm_medium=social &utm_campaign=channel &utm_content=googlecloud to learn more!
Specialization: https://www.coursera.org/specializations/gcp-data-machine-learning?utm_source=yt &utm_medium=social &utm_campaign=channel &utm_content=googlecloud
Keep in touch with Coursera!
How Customers Are Migrating Hadoop to Google Cloud Platform (Cloud Next ’19)
This session provides an overview of how customers are moving their on-premises Apache Hadoop clusters into Google Cloud Platform (GCP).
Key concepts discussed:
Best practices for running Hadoop distributions on GCP
Exploring opportunities for using Cloud Dataproc, GCP’s managed Hadoop and Spark service
Taking advantage of other GCP cloud-native solutions to handle streaming data, analytics, cold data storage, and machine learning
Build with Google Cloud → https://bit.ly/2TXBOOT
Next ’19 Data Analytics Sessions here → https://bit.ly/Next19DataAnalytics
Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions
Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform
Speaker(s): Christopher Crosbie, Blake DuBois
Session ID: DA105
product: Cloud – General; fullname: Christopher Crosbie, Blake DuBois; event: Google Cloud Next 2019;