• Kickstart your data journey by implementing effective data quality checks to ensure accuracy and timeliness.
  • Monitor both upstream and downstream processes to manage potential data cascades in your data pipeline.
  • Utilize frameworks and alert systems like DQ and Slack to quickly identify and resolve data integrity issues.
  • Focus on nominal base checks to avoid alert fatigue and only respond to significant data discrepancies.
  • Adopt a phased approach to addressing data challenges, applying solutions as problems arise within your organization.