22-25 April 2026 
SQLBits 2024
Get Rid of Your Data Quality Problems
Dive into data quality essentials with HEDDA.IO! Discover seamless integration across platforms and real-world scenarios addressing accuracy, completeness, and standards. Empower your data engineering with practical insights to overcome common challenges. Unlock HEDDA.IO's potential and elevate your practices!
In the ever-evolving landscape of data engineering, ensuring impeccable data quality is paramount for informed decision-making and analytics. In this session we delve into the practical integration of HEDDA.IO, a versatile data quality solution designed to tackle diverse challenges.
This session will provide a hands-on exploration of how HEDDA.IO seamlessly integrates into various processes across platforms, including Azure Data Factory, Azure Databricks, Azure Synapse, Microsoft Fabric, and custom applications. We will guide you through real-world scenarios, showcasing how HEDDA.IO effectively addresses common data quality issues. Whether you are dealing with accuracy concerns, completeness challenges, or adherence to standards, this session offers insights and demonstrations to empower you in overcoming your data quality hurdles.
Join us to unlock the potential of HEDDA.IO and elevate your data engineering practices to new heights.
This session will provide a hands-on exploration of how HEDDA.IO seamlessly integrates into various processes across platforms, including Azure Data Factory, Azure Databricks, Azure Synapse, Microsoft Fabric, and custom applications. We will guide you through real-world scenarios, showcasing how HEDDA.IO effectively addresses common data quality issues. Whether you are dealing with accuracy concerns, completeness challenges, or adherence to standards, this session offers insights and demonstrations to empower you in overcoming your data quality hurdles.
Join us to unlock the potential of HEDDA.IO and elevate your data engineering practices to new heights.
Speakers
Oliver Engels's previous sessions
Get Rid of Your Data Quality Problems
Dive into data quality essentials with HEDDA.IO! Discover seamless integration across platforms and real-world scenarios addressing accuracy, completeness, and standards. Empower your data engineering with practical insights to overcome common challenges. Unlock HEDDA.IO's potential and elevate your practices!
Data Testing with HEDDA.IO
Explore the pivotal role of data testing in ensuring accuracy, completeness, and reliability in data engineering. Learn how HEDDA.IO, a versatile data quality tool, seamlessly integrates into diverse environments such as Azure Data Factory, Azure Databricks, Azure Synapse, Microsoft Fabric, and custom applications. This session provides practical insights into HEDDA.IO's application within a lake house concept or event-driven architecture. Through informative discussions and hands-on demonstrations, discover how HEDDA.IO enhances data testing processes, empowering data engineers to rectify errors and anomalies, ensuring robust and reliable data for downstream analytics and decision-making.
Tillmann Eitelberg
decompose.io
Tillmann Eitelberg's previous sessions
Get Rid of Your Data Quality Problems
Dive into data quality essentials with HEDDA.IO! Discover seamless integration across platforms and real-world scenarios addressing accuracy, completeness, and standards. Empower your data engineering with practical insights to overcome common challenges. Unlock HEDDA.IO's potential and elevate your practices!
Data Testing with HEDDA.IO
Explore the pivotal role of data testing in ensuring accuracy, completeness, and reliability in data engineering. Learn how HEDDA.IO, a versatile data quality tool, seamlessly integrates into diverse environments such as Azure Data Factory, Azure Databricks, Azure Synapse, Microsoft Fabric, and custom applications. This session provides practical insights into HEDDA.IO's application within a lake house concept or event-driven architecture. Through informative discussions and hands-on demonstrations, discover how HEDDA.IO enhances data testing processes, empowering data engineers to rectify errors and anomalies, ensuring robust and reliable data for downstream analytics and decision-making.