Configure highly available data and real-time analytics to optimize performance, improve decision-making, and unlock new value.
- 125 Topics
- 116 Replies
Google Cloud is all about its customers.Read about: the New York Times shared how their data analytics team went from staying up until three in the morning trying to keep their legacy system running to relaxing while eating ice cream after their migration over to Google Cloud. why Verizon Media picked BigQuery for scale, performance, and cost. how the Golden State Warriors transform on-court data into a competitive advantage, pulling raw data from AWS into Google Cloud for fast analytics and much more on this article.Image Source: Official Google Cloud BlogI love these kind of stories. Success stories!Would you like to share your story as well?
Cloud Bigtable backups let you save a copy of a table's schema and data, then restore from the backup to a new table at a later time.In this tutorial, you'll learn how to create backups at regularly scheduled intervals (such as daily or weekly) using the Cloud Bigtable Scheduled Backups example.Image Source: Official Google Cloud BlogHave you used the Bigtable backup? Did you do it like this tutorial or did you do it another way?
Google Cloud and Databricks announced a new partnership to deliver Databricks at a global scale on Google Cloud.This partnership, which was announced in February, is fully available to the public from May the 4th (be with us!) 😀Enterprises can deploy or migrate Databricks Lakehouse to Google Cloud to combine the benefits of an open data cloud platform with greater analytics flexibility, unified infrastructure management, and optimized performance.Read it hereImage Source: Official Google Cloud BlogAwesome news, right?
Spotify began a migration to Google five years ago when Google's long-term commitment to cloud computing was something of a question.In a recent interview with Protocol, Tyson Singer, vice president of technology and platforms at Spotify, who oversees the technical infrastructure that serves Spotify's 356 million monthly active users, discussed the company's decision to marry its fortunes to Google Cloud, the pros and cons of using managed services and why "ML ops" is the next big thing on his radar.https://www.protocol.com/enterprise/spotify-google-cloud-platform They love BigQuery. What is your favorite Google Cloud technology?
Data Analysts 👉 Learn how to model, analyze, and visualize your data in less than 30 minutes. In this demo, Product Demonstration Manager, Leigha Jarett, will walk you through setting up a connection between your BigQuery data warehouse and Looker.Once connected Leigha will show how Looker auto-generates a data model, which you can immediately explore, customize, and reuse. From there, you’ll learn how to build reports, dashboards, bring data into your workflows via alerts, integrations, and more.Register
Today on the news are two articles for Japanese companies:7-Eleven Japan's built "Seven Central," a new platform for practical data use, to support the company’s future IT strategies and Digital Transformation initiatives. Learn how it leveraged #BigQuery and Apigee API management to support its data platform.https://cloud.google.com/blog/products/data-analytics/how-7-eleven-japan-built-its-new-data-platform Japan’s largest C2C marketplace, Mercari, allows 85+ million users to buy new and used items.Learn how Cloud Spanner helped the e-commerce giant launch a new mobile payment platform that is strong on scalability, availability, and performancehttps://cloud.google.com/blog/products/databases/mercari-chose-cloud-spanner-to-help-power-merpay How has Google Cloud helped your company? Share your story with us!
Do you love your database?Did you know that Cloud Spanner launched customer-managed encryption keys and Access Approval?Cloud Spanner is Google Cloud’s fully managed relational database that offers unlimited scale, high performance, strong consistency across regions and high availability (up to 99.999% availability SLA). In addition, enterprises trust Spanner because it provides security, transparency and complete data protection to its customers. To give enterprises greater control of how their data is secured, Spanner recently launched Customer-managed encryption keys (CMEK). CMEK enables customers to manage encryption keys in Cloud Key Management (KMS). Read the full blog posting here. Image from Google blog post
Have you used BigQuery’s new Geospatial capabilities? Have you exported them on Data Studio?Lak Lakshmanan, Data Analytics & AI @ Google Cloud, is showing how you can do it in his articleSource: @trolliYou can use BigQuery Sandbox (it’s free) and Data Studio (free product). Awesome, right?
When I was talking about BigQuery, I always had three people in mind: Felipe, Jordan and Lak.The first two are no longer in the team that works with BigQuery. But Lac is. And does an amazing job of writing articles, making videos that you can watch live or on-demand from Cloud OnAir events and, of course, training courses in Coursera and PluralSight.From last week I will have in mind another person. Our @antoine.castex, core team member of the France Community Group at C2C.His way of approaching BigQuery and explaining it with such simplicity is truly amazing. In his article, he has a very good transmission capability.It's a 7 minute investment to read. @Content.Sabina we must have him on the panel and talk. @JBranham maybe we can have a 10 minutes video from experts like himhttps://beautytmr.com/please-bigquery-can-you-accelerate-my-answers-and-be-cheaper-d642d2227c33 Source: Antoine Castex’s article on Beauty Tomorrow Publication, Medium
Hi Community, I wondering if someone have the experience implementing Data CI/CD pipelines from SalesForce and other DW flavors to BigQuery, managing versioning, deltas and dynamics pivoting tables, schema updates using GCP tools services (including Dataform). Thanks in advance
C2C is doing an event along with MediaAgility on How How MediaAgility is Partnering with Google Cloud and Looker to Help Businesses Build a BI Platform.You will get a chance to explore how MediaAgility supports analysis of critical KPIs—such as revenue growth, asset utilization, and overheads—when you attend the upcoming C2C Deep Dive with Shashi Ranjan, lead consultant and data architect. For companies relying on traditional ERP data, access restrictions and the need for manual interventions slow down analytics performance. Using Google Cloud and Looker, Ranjan and his team implemented a sustainable, centralized data and BI platform. Now, seamlessly integrated analytics are helping to identify new opportunities. RSVP here and make the most of this event.
New enhancements to Data Studio, including support for choropleth maps of BigQuery GEOGRAPHY polygons, so you can easily visualize BigQuery GIS data in a Google Maps-based interface.Ready to try it out for yourself? Check out this step-by-step walkthrough of visualizing BigQuery polygons in Data Studio. Explore the BigQuery Public Datasets or try it with your own data. If your geospatial data isn’t already in BigQuery, you might want to learn more about BigQuery GIS or loading geospatial data into BigQuery using FME.https://cloud.google.com/blog/products/data-analytics/geospatial-insights-bigquery-gis-and-data-studio-choroplethGoogle Cloud BlogI have used BigQuery and Data Studio a lot of times. But I have never used BigQuey GIS. It is quit tempting to start fooling around on the weekend! What do you think?
Ready to take your surveying to the next level and build an experience management data warehouse?From Google Forms to Google Cloud Platform. Your XM data warehouse will leverage three main technologies: Cloud Dataprep by Trifacta, BigQuery, and Data Studio or Looker.Get started today by visiting Codelab, digging into the technical guide, or checking out this video walkthrough.You can access all of Google Cloud patterns on their Smart Analytics Reference Patterns page.https://cloud.google.com/blog/products/data-analytics/creating-an-experience-management-data-warehouse-with-survey-responsesby NBC
Major League Baseball migrates to Google Cloud to develop a unified data plane across its complex operations to drive fan engagement and increase operational efficiency. Just so everybody knows (we have a global audience), Major League Baseball, which is North America’s oldest and most-attended professional sports league, consists of 30 member teams in the United States and Canada. It is America’s “Past time” and almost everyone loves baseball. So check this out: “The fundamental goal is fan engagement—to bring baseball to millions of fans and introduce new technology that allows for personalized recommendations and a social viewing experience, where when something happens on the field and you get excited about it, you can share it with other fans. These are the things that really motivate us and Google Cloud has been a great partner in building products that embody those values.” —Jason Gaedtke, CTO (former), MLBYou can read the full article here. Is this interesting for you? Wou
Did you see the announcement today? Google has been named a Leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report. For more than a decade, BigQuery, Google’s petabyte-scale cloud data warehouse, has been in a class of its own. Google wants to thank our strong community of customers and partners for voicing their opinion. “We believe this report validates the alignment of our strategy with our customers’ analytics needs.”Are you using BigQuery in your work, or do you plan to?Would you like to continue discussions on this thread? Should we invite the author of the blog to do a session for interactive Q&A? (Hint: I know him.) Let us know.
@OttoSchell welcome to C2C! I’m curious, when you, as the expert, don’t know the answer who do you go to or where do you turn? Feel free to @ people and/or invite others to the community and conversation or share resources that would be helpful to the entire group. Look forward to hearing your responses!
Google Cloud’s databases and analytics products such as BigQuery, Dataflow, Pub/Sub and Firestore brought Theta Labs unlimited scale and performance, allowing them to: Analyze streaming viewership data for real-time for analytics Forecast how many concurrent users to support during livestream events Predict reputation scores for thousands of edge nodes and address bad actors or underperformance Create the listener/subscriber for the topic the ETL pipeline publishes and ingest into BigQuery tables running fast queries Isn’t it an inspiring work? What do you think?
Today, I read this article about Looker: https://cloud.google.com/blog/topics/training-certifications/how-to-use-looker-on-google-cloud-for-data-governanceThe truth is that I haven’t used it, yet. Instead, I have worked with Dataprep for cleaning data and Data Studio for dashboards.Has anyone used it? Let me know what you think about this. And also, if anyone has used Looker and Dataprep to compare them, this would be even better!
5 days , 21 hours of free training to improve your data processing skills through flexible hands-on training and practical tips provided by expertseam from concept to common use cases and best practices.5 days, 21 hours to bring your skills to the next level to make your daily job more productive. To learn best practices that can help you solve your more advanced/large scale data processing applications, or to improve performance and reduce costs of your Apache Beam pipelines, or simply ask questions to a team of Apache Beam experts.The free training webinars sponsored by the open source community including Google Cloud could be of value to you and team. Key topics include:The Data Processing ecosystem and distributed processing the Beam way Advanced distributed data processing Scaling and productionalizing your Beam pipelines Strategies for performance and cost optimization Best practices for debugging Beam pipelinesRegister now 👉 https://beamcollege.dev/
C2C member, speaker, and France group leader, @guillaume blaquiere wrote this on Medium and I thought it’d be a great article to share for Tips and Best Practices curation. Here’s Guillaume’s intro to the post:Cloud components are useful and powerful. However, they are all disconnected from the others and when you want to deploy a full pipeline, you need to glue them. You can achieve this with PubSub and Cloud Functions.However, it quickly becomes a spaghetti design with a lot of topics and functions. Having a centralized place to see, manage and configure your pipeline workflow could be great! You can read the full article and Guillaume’s tips here: https://medium.com/google-cloud/parallel-executions-with-google-workflows-3a16f8fee0eb
Login to the community
Social LoginLogin With Your C2C Credentials
Enter your username or e-mail address. We'll send you an e-mail with instructions to reset your password.