Analytics

Best Practices For Transferring Healthcare Data To Your Database

In the constantly changing healthcare environment, smooth data exchange is not just a luxury; it is a vital necessity. Integrating patient records from Electronic Health Records (EHRs), clinical data repositories, and other healthcare systems unlocks valuable insights, empowering providers to deliver personalized care, fuel groundbreaking research, and streamline operational efficiency.

Monitoring Cloudera DataFlow Deployments With Prometheus and Grafana

Cloudera DataFlow for the Public Cloud (CDF-PC) is a complete self-service streaming data capture and movement platform based on Apache NiFi. It allows developers to interactively design data flows in a drag and drop designer, which can be deployed as continuously running, auto-scaling flow deployments or event-driven serverless functions. CDF-PC comes with a monitoring dashboard out of the box for data flow health and performance monitoring.

Top 4 Data + AI Predictions for Telecommunications in 2024

The sheer breadth of data that telecommunications providers collect day-to-day is a huge advantage for the industry. Yet, many providers have been slower to adapt to a data-driven, hyperconnected world even as their services — including streaming, mobile payments and applications such as video conferencing — have driven innovation in nearly every other industry. The speed with which generative AI will change how we work, live, communicate and entertain ourselves is nearly unfathomable.

Ask Me Anything About Styling and White Labeling Yellowfin

Yellowfin makes it possible to combine action-based dashboards, automated data discovery, and data storytelling into a single, integrated, seamless platform — right in your user’s core workflow. Learn how to best to leverage these capabilities, starting with a walkthrough of the basics of white labeling Yellowfin along with some tips and tricks.

How HR Tech Company Sense Scaled their ML Operations using Iguazio

Sense is a talent engagement company whose platform improves the recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. The AI/Ml team is made up of ML engineers, data scientists and backend product engineers.