Visualizing Geospatial Data at Scale

There’s a pervasive perception held by many organizations that data governance or effective access management for data somehow reduces the ability to leverage and derive insight from information. This could not be further from the truth. Full control of data is necessary for both data protection and data leverage. In this webina

PrecisionProfile – a bioinformatics technology company – focuses on enabling oncologists and research scientists to rapidly analyze genomic profiles and create personalized treatment plans for cancer patients. Like most organizations, PrecisionProfile struggled with the most time-consuming part of every analytics exercise - combing, cleaning, and shaping data into actionable information. With self-service data preparation, they were able to design and develop a platform to accelerate data pipelines, enabling scientists to spend more time analyzing data and formulating how they can leverage it to save lives. View this webcast to learn: Empower researchers and oncologists to spend a fraction of their time restructuring data. Reduced cycle time of a genomic clinical study from 1-3 months to 2-8 hours.

The migration to cloud-based data architectures continues at a rapid pace, including databases and data management. Oracle databases are part of this trend, and during this webinar you will learn how to automate the provisioning and management of Oracle databases so that you can deliver an “as-a-service” experience with 1-click simplicity. Experts will walk you through the process of

Whether to take data ingestion cycles off the ETL tool and the Data Warehouse or to facilitate competitive Data Science and building algorithms in the organization, the Data Lake a place for unmodeled and vast data will be provisioned widely in 2019. Though it doesn’t have to be complicated, the Data Lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the Data Swamp, but not the Data Lake! The tool ecosystem is building up around the Data Lake and soon many will have a robust Lake and Data Warehouse. We will discuss policy to keep them straight, send “horses to courses,” and keep up users’ confidence in the Data Platforms.