New BigQuery editions: flexibility and predictability for your data cloud
New BigQuery pricing editions and autoscaling let you choose the right price-performance for your workloads, and pay for only what you use.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Secure and privacy-centric sharing with data clean rooms in BigQuery
BigQuery data clean rooms can help organizations create and manage secure environments for privacy-centric data sharing, analysis, and collaboration.
ThoughtSpot for Google Cloud Platform
ThoughtSpot is partnering with Google Cloud to expand self-service analytics capabilities beyond the dashboards! Now you can use AI-powered search to query Google BigQuery in real-time, access the Looker semantic layer to obtain reliable and standardized data models, and close the productivity loop with ThoughtSpot plugins for Google Sheets, Connected Sheets, and Slides.
Telecom Data Cloud | Snowflake For Telecommunications
Telecommunications companies are under pressure to adapt and respond to changing customer preferences, market conditions, and industry regulations. The Telecom Data Cloud enables telecoms to leverage the full potential of data to help deliver exceptional customer experiences, power new revenue streams, and accelerate transformation, while also enabling the highest levels of data security, governance, and compliance. Join Snowflake customers, partners, and data providers already driving revenue and competitive advantages in the Data Cloud.
Setting up Google BigQuery as a data warehouse in minutes
In this tutorial, learn how to set up a new Google BigQuery cloud-based data warehouse account and extract data from all your data sources using Stitch in less than 3 minutes. Stitch partners with the most common data warehouses and data lakes to help move your data from sources like Shopify, MongoDB, LinkedIn Ads, Zapier, Hubspot, SendGrid, Google Analytics, and more. Google Analytics. Watch this step-by-step tutorial on how to set up Google BigQuery for data storage.
No Average Patient - Leveraging Data for Precision Healthcare
The evolution of healthcare has come a long way since local physicians made house calls and homespun remedies were formulated using items from the kitchen spice rack. Today’s healthcare is driven as much by the promise of emerging technologies centered on data processing and advanced analytics as by developing new and specialized drugs.
How Yellowfin Complements Tableau to Expand Analytics Use Cases
When it comes to analytics capability that caters to diverse data needs across the entire business, Yellowfin provides specific advantages compared to Tableau in several areas. Tableau users may find the platform can be complex, or lacking, in areas such as dashboard design, data governance, or flexibility. Thankfully, many have found Yellowfin to be a great alternative, and even complementary solution, to their analytic needs.
How Manufacturers Drive Profits with Connected Products
It’s been a decade since “connected” objects—commonly referred to as “the internet of things” (IoT)— reached broad audiences. Connected toothbrushes, sensors embedded in sneakers, and smart watches have started to change consumer behavior through a data-driven, gamified approach. Technology has rapidly evolved to handle large data volumes at high velocities and big data analytics. AI has become more democratized.
#shorts - Monitor Resource Consumption in the Qlik Cloud QMC
Administrators can monitor purchased and used amounts of different capacities in the Home pane in the Qlik Cloud Management Console. The pane gives you an overview of the consumption of user allocations, data capacity, reloads, and other capacity-based resources. It also shows a list of the capabilities that are enabled with your subscription and the limits on the capabilities.
Trusted Data: Alchemy For Misinformation
The best description of untrusted data I’ve ever heard is, “We all attend the QBR – Sales, Marketing, Finance – and present quarterly results, except the Sales reports and numbers don’t match Marketing numbers and neither match Finance reports. We argue about where the numbers came from, then after 45 minutes of digging for common ground, we chuck our shovels and abandon the call in disgust.” How would you go about fixing that situation?