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What Is a Data Clean Room, and Do You Need One?
There’s a lot of talk in the market these days about data clean rooms, along with some confusion about what exactly a data clean room is and how it differs from data sharing methods. In this blog post, I’d like to shed some light on this topic.
How to build a self-service BI strategy
Think about the times you've wished you had more insight into your business data. Or all of the times you wished you could answer questions about your business performance without waiting for someone else to get back to you. Gone are the days when businesses rely solely on IT staff to provide reports and analytics. With self-service business intelligence (BI), users can create their own reports, dashboards, and data visualizations without relying on IT help.
Does Cost Reduction Play a Role in Digital Transformation?
Digital transformation. Everyone has their own ideas about what digital transformation means, so I decided to look up a few definitions.
Moving to Log Analytics for BigQuery export users
If you’ve already centralized your log analysis on BigQuery as your single pane of glass for logs & events…congratulations! With the introduction of Log Analytics (Public Preview), something great is now even better. It leverages BigQuery while also reducing your costs and accelerating your time to value with respect to exporting and analyzing your Google Cloud logs in BigQuery.
The Data Cloud & Public Sector With Deloitte
Welcome to Data Cloud Now, where we are dedicated to illustrating how the Data Cloud is pushing the possible forward, each and every day. In this episode we are exploring the impact it’s having within the public sector. Explore the impact the Data Cloud is having within the Public Sector with special guests Deloitte’s Monica McEwen & Frank Farrall along with Snowflake’s Jeff Frazier.
Following your local happiness gradient - Dr. Catherine Williams
This episode features an interview with Dr. Catherine Williams, Global Head of IQ at Qualtrics, an experience management software platform. Catherine has extensive background in data science and quantitative analytics. Prior to Qualtrics, Catherine served as Chief Data Scientist and Chief Data and Marketplace Officer at AppNexus and Xandr, which is part of AT&T. Catherine holds a Ph.D. in Mathematics from the University of Washington. She has also held postdoctoral fellowships at Stanford and Columbia Universities. On this episode, Catherine discusses growing a machine learning approach to unstructured data, using data to get to the “why” of customer behavior, and following your local happiness gradient.
Developing More Accurate and Complex Machine-Learning Models with Snowpark for Python
Sophos protects people online with a suite of cybersecurity products. Hear Konstantin Berlin, Head of Artificial Intelligence at Sophos, explain how the Snowflake Data Cloud helps Sophos increase the accuracy of their machine-learning models by allowing data scientists to process large and complex data sets independent of data engineers. Through Snowpark, data scientists can run Python scripts along with SQL without having to move data across environments, significantly increasing the pace of innovation.
3-Minute Recap: Unlocking the Value of Cloud Data and Analytics
DBTA recently hosted a roundtable webinar with four industry experts on “Unlocking the Value of Cloud Data and Analytics.” Moderated by Stephen Faig, Research Director, Unisphere Research and DBTA, the webinar featured presentations from Progress, Ahana, Reltio, and Unravel. You can see the full 1-hour webinar “Unlocking the Value of Cloud Data and Analytics” below. Here’s a quick recap of what each presentation covered.
Get Ready for the Next Generation of DataOps Observability
I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.