Recently, the leading hub for Enterprise AI Dataiku made headlines by releasing a new, key upgrade to their software platform dubbed Dataiku 5. The new version will provide data teams with the necessary power to not only create but also deploy enterprise AI solutions widely.
What’s more, Dataiku 5 boasts full containerization features with both Kubernetes and Docker. Aside from that, it improves AutoML, welcomes deep learning to its supported libraries and brings in new all-inclusive documentation capabilities that enable globally, distributed data teams to create powerful apps more efficiently.
“In Dataiku 5 we are unlocking the ability for global teams to build even more powerful AI-driven services. We envision the future of AI application development as a global network of people within an organization, all of different backgrounds and skill levels, contributing to game-changing business applications. We’ve taken a major step towards that vision in our latest release,” said CEO of Dataiku Florian Douetteau.”
Dataiku 5 allows scalable Enterprise AI across an entity through introducing an array of new capabilities including:
Full Containerization with Kubernetes and Docker
‘Containerized’ environments refer to self-contained entities, which can be shifted to multiple servers and enable organizations to serve requests and load models in a few clicks. Dataiku 5 takes Docker coupled with the capabilities of containerization to Python & R recipes’ in-memory processing.
It also takes them to in-memory model scoring and training. For Dataiku to operate in-memory operations, it can now develop a Docker image comprising the code and the necessary packages or libraries as well as deploy it automatically to a Kubernetes group for computation elasticity.
Maritime containers were an incredible game-changer in shipping and have greatly shaped the world economy, as they form a global transportation network for goods. In the same case, virtual containers are quickly transforming the way we create and deploy apps in the Enterprise.
Comprehensive Documentation with Wikis and Group Discussions
With organizations continuing to develop additional AI-powered services, the inadequacy of documentation not only develops risks but also increases maintenance expenses.
Nevertheless, encouraging strong documentation, particularly in AI projects, facilitates the sustainable reusing of knowledge across projects in a bid to enable teams to build the necessary skills to become successful. With Dataiku 5, anybody can build, subscribe, comment and connect with subject matter professionals or teammates on their preferred topics of interest.
Visual Deep Learning with Keras and TensorFlow
Dataiku 5 ushers in Keras, which is a Python-written neural network library, to its family of supported open-source technologies and libraries. As such, users can now define the structure of their deep learning models, particularly from the Machine Learning GUI.
Enterprise AI is currently on track to transform business efficiencies and processes in the coming future. In this case, Dataiku 5 acts as the launching point whereby data teams can start developing powerful applications on one collaborative platform.
As of now, hundreds of organizations or companies, spanning from SMBs to Fortune 100’s among others, utilize Daitaku daily. Doing so allows their teams to create, deploy and oversee predictive data flows and create enterprise AI apps to solve an array of problems including predictive maintenance, churn, fraud and supply chain optimization among others.
Source Dataiku
