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How to blast through silo mentality to create a culture of experimentation - WiderFunnel Blog

@machinelearnbot

Is your experimentation program experiencing push-back from other departments? Marketers and designers who own the brand? Product owners who've spent months developing a new feature? The reality is that experimentation programs often lose steam because they are operating within a silo. Problems arise when people outside of the optimization team don't understand the why behind experimentation. When test goals aren't aligned with other teams' KPIs. Optimization champions can struggle to scale their experimentation programs from department initiatives to an organizational strategy. Because to scale, you need buy-in.


Live Webinar: Feature Store as a Data Foundation for ML

#artificialintelligence

With many organizations evolving their ML projects from experimentation to production, massive amounts of time are wasted on feature definition and extraction. Robust feature engineering and management, enabled in and by a Feature Store, are key missing parts of the ML stack. With them, businesses can innovate faster and drive ML processes at scale. Join Provectus and Amazon Web Services (AWS) for a live webinar to learn why a Feature Store is a foundational component of data infrastructure. At the webinar, we will look into the specifics of building a scalable Feature Store with a data mesh pattern, and discuss how to achieve consistency between real-time and training features, to improve reproducibility with time-traveling for data.


Optimizely updates its Full Stack platform with new data tools, enterprise integrations

ZDNet

San Francisco-based web experimentation company Optimizely is releasing a new version of its flagship platform that includes a new user interface, new data and analytics offerings, and integrations with AWS and Salesforce. Optimizely's core product is Web Experimentation, which enables non-technical staff to conduct A/B testing on the company's website using Optimizely's visual editor. Meantime, Optimizely's Full Stack product enables developers to experiment deeper into the tech stack to test things like search ranking algorithms or mobile app functionality. A/B testing has been a notable space of the software market as customers look to develop digital channels and improve experiences. Optimizely allows for quick A/B testing that can speed up software and code delivery.


Shifting Left on Development @CloudExpo #CloudNative #AI #SDN #DevOps

#artificialintelligence

As applications become more complex and codebases grow, companies are forced to implement more comprehensive quality safeguards which slow the rate at which they can deliver new software. At the same time, the companies that prevail in this winner-take-all economy are those that can accelerate software delivery while providing a high caliber of quality. High-velocity engineering teams are applying not only continuous delivery processes, but also lessons in experimentation from established leaders like Amazon, Netflix, and Facebook. These companies have made experimentation a foundation for their release processes, allowing them to try out major feature releases and redesigns within smaller groups before making them broadly available. In his session at 21st Cloud Expo, Brian Lucas, Senior Staff Engineer at Optimizely, discussed key practices that developers can use to maximize the effectiveness of continuous delivery, quality, and experimentation programs.


Shifting Left on Development @CloudExpo #CloudNative #AI #SDN #DevOps

#artificialintelligence

As applications become more complex and codebases grow, companies are forced to implement more comprehensive quality safeguards which slow the rate at which they can deliver new software. At the same time, the companies that prevail in this winner-take-all economy are those that can accelerate software delivery while providing a high caliber of quality. High-velocity engineering teams are applying not only continuous delivery processes, but also lessons in experimentation from established leaders like Amazon, Netflix, and Facebook. These companies have made experimentation a foundation for their release processes, allowing them to try out major feature releases and redesigns within smaller groups before making them broadly available. In his session at 21st Cloud Expo, Brian Lucas, Senior Staff Engineer at Optimizely, discussed key practices that developers can use to maximize the effectiveness of continuous delivery, quality, and experimentation programs.