SESSION
Learn Practical Techniques for Applying Data Quality in the Lakehouse with Databricks (Repeat)
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Governance |
TECHNOLOGIES | Databricks Experience (DBX), Governance |
SKILL LEVEL | Beginner |
DURATION | 40 min |
This session is repeated.
Data quality has been a critical and common practice employed across industries for many years. At the core, data quality encompasses six dimensions, including consistency, accuracy, validity, completeness, timeliness, and uniqueness.
However, a significant challenge remains in streamlining these processes to prevent data management issues and enhance their utility for downstream analytics, data science, and machine learning. The session will delve into the six dimensions of data quality, detailing the specific techniques and features that enhance the Databricks Platform's functionality.
SESSION SPEAKERS
Lara Rachidi
/Solutions Architect
Databricks
Liping Huang
/Senior Solutions Architect
Databricks