Times are tough – adversity is hitting our public sector and healthcare agencies from every angle. Budgets and resources are stretched beyond breaking point with many agencies facing multi-million real-term cuts. Combine this with an increase in complex demand, heightened public scrutiny and a continued expectation of improvement; something must change.
This month we released several new features in beta, including query scheduling, new BigQuery ML models and functions, and geospatial types and queries. We also released the ORC ingest format into GA. Let’s take a closer look at these features and what they might mean for you.
When we think of other products in Bugfender’s space, we don’t really think of competitors; we think of alternatives. Because, being honest, Bugfender doesn’t really have any direct competitors. That sounds like cheesy marketing, right? Yep, we get that. And we don’t say it to be arrogant. We say it because Bugfender was built to provide a unique service in our space. In fact it’s designed to serve the specific needs of our parent company, Mobile Jazz.
As we covered in our recent NLP blog, there are a lot of cool use cases for text / sentiment analysis. One recent instance we found really interesting came out of our May presentation at SeaTUG (Seattle Tableau User Group.)
We’ve recently experienced two fairly large system problems that have affected approximately 35% of our clients. The first issue took 50 minutes to resolve and the other approximately 10 hours. The root cause in both cases was the way we handled the provisioning of adhoc sandboxes on top of our SnowflakeDB (a few words about “how we started w/ them”).
How do you protect the stability of the work you’ve already done, while evangelizing experimentation, exploration and progress within your organization? The rapid evolution in business intelligence and analytics capabilities is both exhilarating and overwhelming.
Learn about:
BigQuery, Google Cloud’s serverless, highly scalable, low-cost, enterprise data warehouse, was designed to make data analysts productive. With no infrastructure to manage, customers can focus on analyzing data using familiar Standard SQL, while simplifying database administration and data operations. Large enterprises, mid-market growing organizations, and cloud native startups across the globe can use BigQuery to perform analytics at scale with equal ease.
