Configure highly available data and real-time analytics to optimize performance, improve decision-making, and unlock new value.
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Unlocking the potential of customer data to drive faster innovations in advanced analytics, AI and Machine Learning has been a core focus for Google Cloud. We're talking Infrastructure Modernization, Database Migration, Business Intelligence on Looker, Marketing Analytics, Predictive Analytics and more! How has data played an important role at your organization? What has been the number one pain point or challenge your organization has faced where data and analytics became a key solution? Is there a topic within Data and Analytics you'd like to learn more about? Let us know in the comments below» As the newly announced Google Cloud Data Analytics Partner of the Year, Quantiphi continues to leverage Google's best-in-class technology to help organizations across industries embark on a data-driven digital transformation journey on Google Cloud. Read more.
It is a fact that more and more traditional data warehouses are migrating to BigQuery.That’s why the BigQuery team wants to make our lives easier with these new user-friendly SQL features.These new capabilities come in three themes: Powerful Analytics Features, Flexible Columns, and Secure with SQL:Powerful Analytics FeaturesQUALIFY,PIVOT,UNPIVOT, Table function (Preview) Flexible Columns Parameterized Data Types (Preview) Flexible Data Type Casting and Formatting (GA) Change a column’s description (GA) Secure with SQL GRANT and REVOKE access to tables, datasets and views (GA) Review object privileges with INFORMATION_SCHEMA (Preview) So many new toys to play either on a live(?) project, a side project or for Free on BigQuery SandboxRead the article hereGoogle Cloud Blog
Google’s cloud data warehouse, BigQuery, has enabled organizations around the world to accelerate their digital transformation and empower their data analysts to unlock actionable insights from their data. Using BigQuery ML, data analysts are able to create sophisticated machine learning models with just SQL and uncover predictive insights from their data much faster.The AutoML Tables model type into the list of supported ML models within BigQuery ML and integrates directly and seamlessly with Vertex AI.Read the article hereGoogle Cloud Blog
Data Preparation takes a lot of time. It doesn’t matter if you are a beginner or an experienced data analyst. You are going to spend a lot of time on Data Wrangling.You have the option to use your Jupyter Notebook or you can use Dataprep by Trifacta. And you can do everything without writing a single line of code. Awesome, right?In this article, Priyanka has created cheat sheet with her drawings
BigQuery row-level security is now generally available, giving customers a way to control access to subsets of data in the same table for different groups of users. Row-level security (RLS) extends the principle of least privilege access and enables fine-grained access control policies in BigQuery tables. BigQuery currently supports access controls at the project-, dataset-, table- and column-level. Adding RLS to the portfolio of access controls now enables customers to filter and define access to specific rows in a table based on qualifying user conditions—providing much needed peace of mind for data professionals. Read more here: https://cloud.google.com/blog/products/data analytics/bigquery-provides-tighter-controls-over-data-access
Accessing data in real time enables your company to analyze, plan and improve continuously, so you can make better strategic decisions and reduce your overall risk.But any system can move only as fast as its slowest bottleneck.Read here how with Google Cloud’s Datastream, a serverless change data capture and replication service, and MongoDB Atlas, you can set up a real-time analytics pipeline that continually streams data from legacy relational data stores (like Oracle and MySQL) into MongoDB Atlas. Do you want to learn more about Datastream? Sign-up for our eventImage Source: Google Cloud Blog
Hello All,Great opportunity to learn the basics of BigQuery.Learn the basics of BigQuery, Google’s multicloud data warehouse, and get your questions answered live by experts in our no-cost June 18 training. This training will occur at both 9 am PT (Pacific Time) and 11:30 am SG (Singapore Time).shorturl.at/sS235
Most of the time people tend to do what their friends do.The same thing happens when you work with clients. I have heard the argument many times: "We will do it this way because my friend does the same with his company".They cannot understand that every company is a different case and they cannot understand the evolution of CS and Cloud technologies.In one of these cases, I had a client who looked at me as if I were a foreigner, an alien when I proposed to have an ELT solution for his company.Really glad to read this article from @antoine.castex and can’t wait for part 2!
This month’s Google Open Source Live will highlight data pipelining in open cloud along with multiple sessions presented by Airflow team members and the community.Join this event to learn about Google contribution in Apache Airflow, Airflow autoscaling in Google Cloud Composer, as well as logging and monitoring in Airflow and Cloud Composer.https://opensourcelive.withgoogle.com/events/airflowday
Dataflow Prime is a new platform based on a serverless, no-ops, auto-tuning architecture that is easy to onboard, use, and operate.It brings unparalleled resource utilization and radical operational simplicity to big data processing. It is built on Dataflow and brings new user benefits with innovations in resource utilization and distributed diagnostics. The new capabilities in Dataflow significantly reduce the time spent on infrastructure sizing and tuning tasks, as well as time spent diagnosing data freshness problems. Dataflow Prime enables you to get more done with less in the following ways: Eliminate the time you spend sizing resource needs Optimize resource usage and save costs Increase your productivity Vertical Autoscaling Right Fitting Job Visualizer Managed Pipeline Smart Recommendations Sign up to receive updates
I just came across this new change data capture (CDC) service from Google that can really compete with Fivetran and similar 3rd party apps.Check it out here: Google Datastreamhttps://cloud.google.com/datastream/?hl=en_GB&_ga=2.132120585.-680420582.1613156617
Every company is on a journey to become more data-driven whether that’s providing great digital experiences to customers, or driving operational excellence through AI, or detecting hidden patterns in data to improve decision making. To help with this transformation, Google Cloud announced new products and services designed to fully unify your databases, analytics, and AI.Centrally manage, monitor, and govern your data across data lakes, data warehouses, and data marts, and make this data securely accessible to a variety of analytics and data science tools from a single view with Dataplex. Move and synchronize data between heterogeneous databases, storage, and applications reliably to support real-time analytics, database replication, and event-driven architectures with Datastream. Access and share valuable datasets and analytics assets across any organizational boundary with Analytics Hub. Speed up your rate of experimentation with AI projects and accelerate time to business value with
Sharing and exchanging data with other organizations is a critical element of a customer’s analytics strategy, but it’s hamstrung by unreliable data and processes, and only getting harder with security threats and privacy regulations on the rise. Furthermore, traditional data sharing techniques use batch data pipelines that are expensive to run, create late-arriving data, and can break with any changes to the source data. They also create multiple copies of data, which brings unnecessary costs and can bypass data governance processes. These techniques do not offer features for data monetization, such as managing subscriptions and entitlements. Altogether, these challenges mean that organizations are unable to realize the full potential of transforming their business with shared data.Analytics Hub is here to address these limitations. It’s a new fully managed service (in preview), that helps us unlock the value of data sharing, leading to new insights and increased business value.It bui
Datastream is a serverless change data capture (CDC) and replication service. It allows enterprises to synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency to support real-time analytics, database replication, and event-driven architectures.You can now easily and seamlessly deliver change streams from Oracle and MySQL databases into Google Cloud services such as BigQuery, Cloud SQL, Google Cloud Storage, and Cloud Spanner, saving time and resources and ensuring your data is accurate and up-to-date.Check out the Datastream documentation.Watch the Introducing Datastream videoYou can read more on these two articles: Unlock the power of change data capture and replication with new, serverless Datastream Using Datastream to unify data for machine learning and analytics Real-time Change Data Capture for data replication into BigQuery Migrate from Oracle to PostgreSQL with minimal downtime with Datastream
Google Cloud is partnering with industry leaders such as Accenture, Collibra, Confluent, Informatica, HCL, Starburst, NVIDIA, Trifacta, and others to build an open platform to power analytics at scale.Dataplex, an intelligent data fabric that provides a way to centrally manage, monitor, and govern your data across data lakes, data warehouses, and data marts, and make this data securely accessible to a variety of analytics and data science tools. You can read more hereWatch the recordingSign-up to request a preview Dataplex will be free to enterprises that are accepted into the preview program.
‘We have been in the business of organizing the world‘s information for a very long time,’ said Debanjan Saha, vice president and general manager of data analytics at Google Cloud (previously worked at AWS). ‘Data is in our DNA, and that’s what drives Google.’Read the full article: Why Google Cloud’s Data Analytics Tops The Competition: Debanjan Saha
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
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