Purpose-built to be fast, secure, reliable and beautiful, Award Force is perfect for anyone who wants to create an unparalleled experience for entrants, judges and program managers.
We support our clients with a global support team whose sole purpose is to give peace of mind and help clients focus on making their awards the best they can be.
Award Force is used for: awards management; staff excellence / employee recognition; grant application management; accelerator program intake; incubator program intake; venture or seed capital funding application management; contest management; fellowship application management; higher education entrance; scholarship applications; journal article / paper abstract submission management; student portfolio assessment.
Good decisions: Good evaluation leads to good decisions and good outcomes. Entry/application evaluators will love how fast and smooth it is to evaluate applications with Award Force.
Save time, save money: Free up your time to focus on making your program the best it can be thanks to reduced admin and support effort.
Grow your program: Increase the volume and quality of your entries/applications, and earn more revenue with features designed for outstanding results.
Judges are happy: Attract and retain high-calibre judges that love how fast and smooth it is to judge with Award Force.
Peace-of-mind: Boost confidence and discard stress, you'll be in good company using our reliable and secure system that performs under pressure.
Visibility + control: Deliver the right outcomes time-after-time with flexible configuration options and management tools at your fingertips.
You look good: Distinguish your awards with a friendly, intuitive system in a beautiful design that's a joy to use.
Based on our record, Apache Airflow seems to be more popular. It has been mentiond 66 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / 10 days ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 3 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 7 months ago
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 7 months ago
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 8 months ago
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