Google’s research & data insights solution makes next-generation research accessible

In order to be successful, research needs to be replicable, so scientists can build on past work and insights. However, an article in Nature warned that as much as 50% of published drug development research could not be reproduced in subsequent trials. As a result, promising drug candidates sometimes led to disappointment, as well as wasted time and money, when key findings could not be replicated. The shift to cloud computing helps solve this problem because it allows researchers to use open-source tools that work across platforms. As demand for cloud computing rises, our customers have asked us for more ready-made solutions to assure reproducibility of results by their collaborators, regardless of the platform they are using. They asked for secure and effective collaboration tools as well as faster time-to-insight from any type of data.We listened. Google’s new research and data insights solution includes three sets of functionalities to address these key challenges. Each can be activated on demand and may be eligible for subscription pricing. “HPC in a box” offers abstract complexity to run high performance computing (HPC) workloads by automatically managing your cluster in the most effective manner. It integrates seamlessly with some of the industry’s most-used schedulers like Slurm and PBS. It makes it easier than ever to answer bigger questions faster by accessing Google’s fast, powerful hardware like TPUs and GPUs, all for one predictable flat fee for eligible workloads. Healthcare Innovation Hub provides healthcare-specific functionality to help ingest, aggregate, and de-identify any type of healthcare data in its original format. It unlocks cross-modality analysis and collaboration and empowers researchers with harmonization tools to overcome healthcare interoperability issues. Google Cloud Real-World Insights (formerly FDA MyStudies) accelerates and streamlines drug development and clinical trials to address urgent medical challenges with reproducible results.The solution enables researchers to ask new questions, get answers more quickly, and work more collaboratively–with no wait times or down times. Institutions can scale to more ambitious projects and generate actionable, real-time insights from any data source–all while staying within budget.Many top research centers have already found it faster and more cost effective to shift from downloading and storing data on their own servers to storing and analyzing data on Google Cloud. Here are some of the real-world projects already yielding breakthroughs:Clemson analyzed 8,500 hours of traffic camera feeds with 2.1M vCPUs in three hours to improve evacuation routes for disaster planning.The Colorado Center for Personalized Medicine saved $2.9M by building their Compass data warehouse on Google Cloud rather than on on-prem.The Broad Institute slashed costs of genomic sequencing by 90% with Google Cloud.Our partners, such as Atos, Burwood, Omnibond, Mavenwave, Quantiphi, and Deloitte, can help you first design and develop, then install and implement your own solution, including training. To assess your institution’s needs and develop a customized plan for your next-generation research solution with research and insights, contact our sales team.
Quelle: Google Cloud Platform

Amazon RDS unterstützt nun PostgreSQL 13 in den Regionen AWS GovCloud (USA)

Amazon RDS for PostgreSQL unterstützt jetzt die Hauptversion 13 in AWS GovCloud-Regionen (USA). PostgreSQL 13 bietet verbesserte Funktionalität und Leistung von neuen Funktionen und Verbesserungen wie Deduplizierung von B-Tree-Indexeinträgen, verbesserte Leistung für Abfragen, die partitionierte Tabellen verwenden, inkrementelle Sortierung zur Beschleunigung der Datensortierung und parallele Verarbeitung von Indizes mit dem VACUUM-Befehl, mehr Möglichkeiten zur Überwachung der Aktivitäten in einer PostgreSQL-Datenbank, neue Sicherheitsfunktionen und vieles mehr. Diese Version bietet auch Unterstützung für bool_plperl, wodurch das Schreiben von Perl-Prozeduren vereinfacht wird.
Quelle: aws.amazon.com

AWS gibt Data-Sink-Fähigkeit für die Glue-Konnektoren bekannt

AWS Glue ist ein serverloser Datenintegrationsservice, der das Auffinden, Aufbereiten und Kombinieren von Daten für Analysen, Machine Learning und die Anwendungsentwicklung vereinfacht. Mit den benutzerdefinierten Konnektoren von AWS Glue können Kunden ganz einfach Daten zwischen SaaS-Anwendungen, Cloud-übergreifenden Datenspeichern, AWS-Services, Data Warehouses, benutzerdefinierten Datenquellen und Amazon S3 übertragen. Heute geben wir die Verfügbarkeit einer Data-Sink-Funktion bekannt, die es Kunden ermöglicht, bidirektionale Konnektoren sowohl als Quelle als auch als Ziel zu verwenden. Die Data-Sink-Funktion für benutzerdefinierte AWS-Glue-Konnektoren wird auch in AWS Glue Studio unterstützt, sodass Benutzer ihre Datenpipelines ohne Code erstellen können.
Quelle: aws.amazon.com