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AI-powered Cameras Help You Serve Your Pets Better. Learn How
Watch the video to learn how you can leverage Google Cloud platform and AI functions to build pet-detection cameras that can capture and send image-based alert messages on your phone to notify when your pets arrive or leave.
How Modern is Your Data Warehouse? Find Out With This Test
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As more and more businesses turn to advanced data analytics to help them make smarter decisions, run real-time analytics, and improve business operations, an increasing number are modernizing their data warehouses to make it all possible.
For many businesses, knowing how to modernize means understanding where their data warehouse sits on the spectrum between traditional and cutting edge.
To help, we collaborated with TDWI to offer the data warehouse maturity assessment. By answering a few questions on their current warehouse environment, businesses can get a customized report with helpful tips and recommendations.
A report card for your data warehouse
The data warehouse maturity assessment evaluates five different categories, assigning your business a rating for each that spans from “traditional warehouse” to “advanced/visionary.”
- Data diversity: How well does your warehouse support disparate data types, and does it provide users with a current and holistic view of data from a variety of internal and external sources?
- Infrastructure agility: How well does your warehouse support the various needs of your organization by allowing access from anywhere, ingesting data in real time, and separating storage from compute to enable independent scaling?
- Analytics support: How easy is it to adopt sophisticated analytical techniques at scale, such as machine learning, predictive analytics, deep learning, and IoT analytics?
- Collaboration and sharing: Can teams within your organization and beyond share information and work together quickly and easily using data from your warehouse, and is your data strategy aligned with your business goals?
- Security and governance: Are there tools and techniques in place to control data access, support data governance, and ensure compliance with data security standards?
In addition to the assessment you’ll also receive a detailed report with guidance and best practices that can help you determine your next steps in your modernization journey.
Getting started
Fill out a brief form to launch the survey, then take 15 minutes to answer a series of questions about the platforms, systems, and hardware you use to integrate, manage, and store business data for reporting and analytics. You’ll see your results right away.
Looking for a Cloud Data Warehouse? Find out Why Forrester Thinks Google BigQuery is a Leader
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We are thrilled to announce that Google has been named a Leader in The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report. For more than a decade, BigQuery, our petabyte-scale cloud data warehouse, has been in a class of its own. We’re excited to share this recognition and we want 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.
“Customers like Google’s frequency of data warehouse releases, business value, future proof architecture, high-end scale, geospatial capabilities, strong AI/ML capabilities, good security capabilities, and broad analytical use cases,” according to the Forrester report. Today’s data leaders require a data warehousing platform that provides both depth and breadth and with BigQuery, organizations are able to unlock deeper data science and machine learning capabilities while promoting data democratization and providing the highest levels of availability.
Google BigQuery: 5 out of 5!
Forrester gave Google BigQuery a score of 5 out of 5 across 19 different criteria, including:
Today, customers across the globe use BigQuery to run business critical analytics workloads to enable BI acceleration, IoT analytics, customer intelligence, AI/ML-based analytics, data science, data collaboration, and data services. Customers such as Verizon, Wayfair, HSBC, Twitter, AirAsia, KeyBank, The Home Depot, and Vodafone have anchored their digital transformation efforts on BigQuery—unlocking deeper insights for their people.
Customers use BigQuery across all industries, to solve issues like credit card fraud detection, predictive forecasting, anomaly detection, log analytics and many more. Forrester recognized this work and gave BigQuery a 5/5 score for supporting vertical and horizontal use cases.
More BigQuery advantages
Google is the first hyperscale provider to offer a multi cloud data analytics solution. With BigQuery Omni, customers can perform cross-cloud analytics with ease, and drive business outcomes they couldn’t achieve with the siloed approach offered by other vendors.
We designed BigQuery to be highly scalable and more open and interoperable so that customers can join data across SQL databases, traditional unstructured data lakes in object storage, and even spreadsheets using any analysis tool.
Recent innovations like BigQuery BI Engine lets us provide the best analytics experience by delivering sub-second query response times from any business intelligence tool, from Google’s Looker and Connected Sheets to Tableau, Microsoft Power BI, ThoughtSpot, and others. Our goal is to meet customers where they are rather than force them into a one-size-fits-all approach to data analysis.
With BigQuery, organizations gain both breadth and depth of capabilities to transform their analytics strategy. Forrester also gave BigQuery 5 out of 5 in:
Data-powered innovation
These advantages enable our customers to accelerate their digital transformation and reimagine their business through data-powered innovation. Google’s leadership across AI, analytics, and databases comes together in a single data cloud platform that provides everyone with the ability to get value out of their data faster.
We bring decades of research and innovation in AI to our customers through industry-leading AI solutions, that in turn helps our customers solve their biggest problems. Our support of open standards and APIs enables interoperability between a variety of services for ingestion, storage, processing and analytics across the data cloud platform. And finally, we believe our multi-layered security approach throughout the data stack ensures redundancy and reliability so that customers can have the peace of mind that their data is always protected.
We are honored to be a leader in this Forrester Wave™ and look forward to continuing to innovate and partner with you on your digital transformation journey.
Download the full Forrester Wave™ :Cloud Data Warehouse, Q1 2021 report. And check out these smart analytics reference patterns. To learn more about BigQuery, visit our website, and get started immediately with the free BigQuery Sandbox.
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Best Practices from Experts to Maximize BigQuery Performance (Featuring Twitter)
If you have made the decision to run your data analytics on BigQuery’s serverless platform, you are in good company.
Now, as you deploy complex workloads on your data, you want to be able to maximize the performance of all data operations from data loading to data analytics.
In this video Jagan Athreya, Product Manager, Google Cloud and Gary Steelman, Senior Software Engineer, Twitter discuss the best practices from speeding up your data ingest into BigQuery to learning the tips and tricks from the BigQuery engineering team to maximize query performance of your data warehouse.
The session is roughly divided into five areas:
- The architecture that enables the performance of BigQuery
- An example of a typical query
- How to write fast and efficient queries
- The best way to ingest data
- Twitter case study
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Modernizing your data warehouse is one way to keep up with evolving business requirements and harness new technology. For many companies, cloud data warehousing offers a fast, flexible, and cost-effective alternative to traditional on-premises solutions.
In a report sponsored by Google Cloud, TDWI examines the rise of cloud-based data warehouses and identifies associated opportunities, benefits, and best practices.
Featuring strategic advice from Google experts, it answers questions such as:
- What’s driving businesses to consider the cloud for their data warehousing strategy?
- What are the advantages of a cloud-native data warehouse?
- How can you coordinate data warehouse modernization with other modernization projects?
- What’s the first step in migrating your data warehouse to the cloud?
- How will cloud data warehousing affect your business’s security posture?
Download the complete report to learn more about cloud data warehousing and how it can help your business transform with the times — and prepare for the future.
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28:30 Minutes
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Data Leaders in 2021 and Beyond: How to Prepare
As technologies and workplace environments are quickly evolving, how people and businesses leverage data in their day-to-day workflow is also changing.
Data leaders are an emerging force navigating and charting pathways forward towards new horizons for how people and organizations experience data.
In this presentation, Pedro Arellano, Product Marketing Director, Looker, will cover three areas:
- Underline that the value of data within an organization is no longer up for debate. Everybody needs data, and everybody’s job has the potential to be improved with data.
- Three trends that will help put into context how we’ve arrived at this particular moment of such great potential for data.
- Why data leaders, almost regardless of their title, are now in a position to really influence the direction of organization like never before.
Learn what’s guiding the thinking of data leaders in 2021 and beyond.
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