GRAPH GURUS EPISODE 10 - Analyzing temporal data with a native parallel graph database
Recorded February 27, 2019
This is the 10th episode that continues TigerGraph's Graph Guru series, a free educational webinar series for developers and data scientists.
A temporal data set is a series of data points indexed, listed or graphed in time order. Many applications deal with such data: those that feature financial transactions with associated timestamps, inventories that continually change over time, and other processes involving logs and events coming in 24 hours seven days a week. Being able to analyze data across a particular period of time - whether its volume or size of payment transactions, the cost of care for a specific health condition, machine logs or security events is useful for multiple use cases across banking, insurance, healthcare, government, telecom, and other industries.
This Graph Gurus episode walks through the TigerGraph Developer Edition, demonstrating how to build a time series analysis solution. In this episode, we:
- Share various use cases for temporal data analysis across industries.
- Present a graph solution to perform temporal data analysis using GSQL.
- Review a real-life business use case to see the temporal data analysis by TigerGraph and GSQL in action.
Emma Liu, Product Manager
Huiting Su, Software Engineer