Vaccine development became the top priority for the life sciences industry – delivering new vaccines at unprecedented speed and maneuvering large-scale production processes. Numerous factors helped accelerate the vaccine roll-out including prior research, genome sequencing, jumping the FDA approval queue and a plethora of testing volunteers. So now that we’ve experienced these advancements, how can the industry keep momentum to speed-up innovative solutions across healthcare?
A global leader in pharmaceuticals found themselves faced with a unique spin on a common challenge: Their biopharmaceutical division — responsible for producing vaccines and generating over $1 billion in annual sales — was struggling to turn raw data into trusted insights. Data underlies everything the global pharmaceutical company does, however, without data they can trust, they would be at risk of taking longer to get vaccines to market and incurring higher expenses along the way.
Greek philosopher Heraclitus wasn’t talking about the challenge of today’s enterprise IT landscape but the quote certainly fits. From the advent of the first digital computer in the 1940s to the emergence of first public cloud in 2004, the rate of change has only accelerated. In fact, over 60% of corporate data resides in the cloud in 2022, up from 50% last year.
BigQuery already offers highly flexible pricing models, such as the on-demand and flat-rate pricing for running queries, to meet the diverse needs of our users. Today, we’re excited to make it even easier for you to optimize BigQuery usage with new BigQuery slot recommendations powered by Active Assist, a part of Google Cloud’s AIOps solution that uses data, intelligence, and machine learning to reduce cloud complexity and administrative toil.
Sharing and exchanging data with other organizations is a critical element of any organization’s analytics strategy. In fact, BigQuery customers are already sharing data using our existing infrastructure, with over 4,500 customers swapping data across organizational boundaries. Creating seamless access to analytics workflows and insights has become that much easier with the introduction of Analytics Hub and surfacing datasets unique to Google.