In another life, I taught the Book of Genesis to high school students, including The Tower of Babel excerpt. It struck me ironic that God’s wrath strikes down the tower, cofounds the universal language and scatters humans around the globe to teach King Nimrod a lesson in hubris; meanwhile, the boys in my class were texting their girlfriends across the country and playing video games with friends in Europe and Asia.
We launched BigQuery ML, an integrated part of Google Cloud’s BigQuery data warehouse, in 2018 as a SQL interface for training and using linear models. Many customers with a large amount of data in BigQuery started using BigQuery ML to remove the need for data ETL, since it brought ML directly to their stored data. Due to ease of explainability, linear models worked quite well for many of our customers.
Automation was already well on its way to becoming a ubiquitous investment in 2020, then the COVID-19 pandemic accelerated interest and adoption. Organizations started deploying Robotic Process Automation (RPA), Intelligent Document Processing (IDP), and other automation capabilities en masse, which interacted with mission-critical systems, legacy applications, and workers in both the front and back office.
Upgrading components of Cloudera Data Warehouse (CDW) is as easy as one decision and a few clicks. While the Database (DB) Catalog and Virtual Warehouses (VWs) need to be compatible, the CDW upgrade framework understands the interoperability constraints between them.
Historically, analytics has not always been a priority feature for software vendors. Many applications typically are built with analytics bolted-on later, as standalone tools. But the changing needs of today’s business users has accelerated the importance of providing in-built ways to monitor and explore their data while they use your software.
Last year, Gartner declared that on-premises databases are now legacy technology. Are we ready to say the same for analytics and BI?
Anyone can make a chart, but what’s the right chart? It’s a daily question for BI practitioners, and many of us have been using the highly acclaimed FT Visual Vocabulary to answer that question since its release in 2016.
While there are several different ways to measure the success of a site: one core metric is its traffic. Knowing how well your site performs compared to other sites is crucial in understanding how successful you have been in your efforts against competitors. This is possible if you know how much traffic your competitors are generating. Along with this, some competitor intelligence tools hand over the full list of keywords that bring traffic to a site.
