Systems | Development | Analytics | API | Testing

Hybrid Data Delivery "Cloud Sources" Walkthrough

We have expanded our Hybrid Data Delivery service to load analytics ready data, from a number of cloud-based data sources, directly to snowflake - without the need for Qlik replicate. This initial update currently allows you to connect to data from over 20 cloud-based data sources such as Amazon Redshift, Google BigQuery, and Salesforce and land it directly to a Snowflake as a target on a scheduled basis, so it can be used with your analytics applications – offering a single solution for on-prem and cloud data movement and replication.

AstraZeneca: Building a finance data hub

At AstraZeneca, supporting funcstions like Finance are intensely data-driven. Recently, the data and IT team completely overhauled their data architecture to better serve the needs of the Finance team, they decided to build a Finance data hub. In this video, key project stakeholders explain why and how they build the data hub for the finance team (using Talend and AWS), and they detail how it's integrated with other data hubs at astraZeneca.

Why Can't we Advance Healthcare and Life Sciences this Fast all the time?

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?

Turning data into a life-saving asset

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.

A Real-Time Data Integration Fabric for Active Intelligence

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.

Introducing Active Assist recommendations for BigQuery capacity planning

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.

Enhance your analysis with new international Google Trends datasets in BigQuery

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.