MOSTLY AI: How to create synthetic time series data?

If you want to learn how to generate synthetic time series data, this video is for you. Join Nick Jewell, MOSTLY AI's Product Marketer as he walks us through MOSTLY AI's synthetic data platform to create privacy-safe, accurate versions of time series data describing complex events.

You'll gain practical insights and techniques that can be applied in various data science projects dealing with behavioral and event data. Here's what you'll learn:

➡️ Understanding Synthetic Time Series Data: Get to know the basics and importance of synthetic data in today's data-driven world.
➡️ Modeling and Generating Synthetic Data: Learn how to model purchasing behaviors using real transactional event data.
➡️ Data Preparation and Loading: Explore ways to prepare and upload data into MOSTLY AI's synthetic data generation platform.
➡️ Data Relationship Analysis: Understand how to analyze and connect different datasets for comprehensive insights.
➡️ Configuring Synthetic Data Generation: Discover the settings and parameters to effectively generate synthetic time series data.
➡️ Quality Assurance and Validation: Learn how to conduct thorough quality checks and validate your synthetic data using Python.
➡️ Practical Applications: Understand the real-world applications of synthetic time series data in analytics and machine learning.

Key Moments:

00:00 Introduction to Synthetic Time Series Data
00:12 Modeling Purchasing Behavior
01:07 Loading Data into MOSTLY AI's Synthetic Data Platform
02:08 Analyzing Data Relationships
03:01 Configuring Data Connections
03:54 Synthetic Data Generation Settings
04:55 Creating Synthetic Time Series Dataset
05:35 Previewing Generated Synthetic Data
06:01 Quality Assurance Report Analysis
07:00 Data Validation with Python Code
08:40 Comprehensive Analysis of Synthetic Data