Analytics

MLRun Functions DEMO: Python Jupyter (Open-Source Data Science Orchestration + Experiment Tracking)

MLRun is a generic and convenient mechanism for #data scientists and software developers to build, run, and monitor #machinelearning (ML) tasks and pipelines on a scalable cluster while automatically tracking executed code, metadata, inputs, and outputs. On-Premise or Barebone/Metal - including Edge AI / Analytics Customers include NetApp, Quadient, Payoneer (and many more).

Auto-TLS in Cloudera Data Platform Data Center

Wire encryption protects data in motion, and Transport Layer Security (TLS) is the most widely used security protocol for wire encryption. TLS provides authentication, privacy and data integrity between applications communicating over a network by encrypting the packets transmitted between endpoints. Users interact with Hadoop clusters via browser or command line tools, while applications use REST APIs or Thrift.

Git-based CI / CD for Machine Learning & MLOps

For decades, machine learning engineers have struggled to manage and automate ML pipelines in order to speed up model deployment in real business applications. Similar to how software developers leverage DevOps to increase efficiency and speed up release velocity, MLOps streamlines the ML development lifecycle by delivering automation, enabling collaboration across ML teams and improving the quality of ML models in production while addressing business requirements.

Using Your Existing API to Become a Snowflake Data Marketplace Provider, Part 1

Many data providers who participate in Snowflake Data Marketplace are already using Snowflake Cloud Data Platform as their primary data store, and they can share secure slices of their data via Global Snowflake, Snowflake’s global data sharing feature, with any other Snowflake consumer regardless of which cloud or Snowflake region each is using. But other potential data providers, especially data enrichment companies, are not yet using Snowflake themselves.

How Yellowfin is working with Health iPASS to help medical practices survive

In this Webinar, Health iPASS, a leader in medical practice management software, discusses how they are using Yellowfin to provide business insights to medical practices. These insights allow clients to optimize their patient collections and hold their front desk teams accountable for collecting information and capturing card on file. In an era where medical practices are struggling because of COVID-19, Health iPASS has used Yellowfin to create a set of products to help these practices adapt their workflow and build for the future.

How to use data to change behaviors

The government's COVID-19 response is a good example of failed leadership from a data perspective. While government officials have access to a huge amount of data to help them make decisions they’ve fundamentally failed to use it to take people on a journey. There’s a huge lesson that businesses can learn from this on how to use data to change behaviors. What we’ve seen is governments responding to the outbreak at a very simplistic level.

How to use data to change behaviors

The government's response to COVID-19 is a good example of failed leadership from a data perspective. While government officials have access to a huge amount of data to help them make decisions, they’ve fundamentally failed to use that data to take people on a journey. There’s a huge lesson that businesses can learn from this on how to use data to change behaviors.