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.
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.
Digital transformation. Everyone has their own ideas about what digital transformation means, so I decided to look up a few definitions.
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.
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.
