Explore the role of data virtualization in accelerating AI/ML projects through this 44-minute demonstration. Learn how data virtualization integrates data in real-time from various sources, providing data scientists with a powerful tool to streamline data acquisition and preparation. Discover the integration of popular data science tools like Spark, Python, Zeppelin, and Jupyter with the Denodo Platform for Data Virtualization. Gain insights into efficiently handling large data volumes and understand how data virtualization can significantly reduce project time spent on data-related tasks. Follow along as the demonstration covers topics such as data science workflow, data fabric architecture, data preparation, cleansing, transformation, and visualization, culminating in practical examples of statistics and machine learning applications.
The Role of Data Virtualization in AI-ML Projects - A Demonstration
Overview
Syllabus
Intro
The Data
Data Science Workflow
What is Data Virtualization
Data Fabric Architecture
The Idea
The Weather
Data Preparation
Data Source
Data Virtualization Platform
Data Virtualization Template
Base View
City By Data
Data Virtualization
Data Cleansing
Data Transformation
Filtering Data
Measuring Data
Simple Example
Inbuilt Functions
Joining Tables
Visualization
Data Visualization Example
Data Preparation Example
Statistics
Machine Learning
Data Visualization
Summary
Taught by
Open Data Science
