Low-Code, High Impact: Kickstart Your Data Analytics Journey with KNIME

Abstract: 

The success of data science teams heavily relies on their chosen tools. While algorithmic expertise and domain wisdom are vital, the success of a data science project depends on additional contingent factors linked to the tool, such as costs, ease and time of learning, rapid prototyping, robust debugging and testing, flexibility, effective support, automation and security.

In this talk, we’ll introduce you to KNIME Analytics Platform, the free and open-source data analytics software that relies on a low-code/no-code visual interface to enable professionals from any field to make sense of data. It features extensive data access & blending, wrangling, modeling and visualization capabilities, making it comprehensive and versatile for all stages of the data science life cycle.

KNIME’s free and open-source nature eliminates licensing and budget concerns, and favors smooth integration with other technologies and scripting languages. The platform’s visual GUI allows quick prototyping and easy implementation of analytics pipelines via drag-and-drop data operation blocks. Together, we’ll experience KNIME Analytics Platform in action and build a simple AI-driven application, leveraging the generative power of API-based and local LLMs.

Designed for simplicity, scalability and to address data science needs of any level of complexity, KNIME aims to drive open innovation and empower users with cutting-edge technologies in the evolving data tools landscape.

Bio: 

Roberto Cadili is a data scientist on the Evangelism team at KNIME. During his BSc. in Economics, he developed a genuine interest in statistics and data analysis. At the University of Konstanz, he pursued a MSc. in Social and Economic Data Science where he studied different machine learning algorithms and deep learning architectures with an emphasis on NLP and Computer Vision. As editor for Low Code for Data Science, he is helping the KNIME community shape successful data science stories, tutorials, and best practices that are worth sharing.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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