Big data, big problems: The hidden costs of bad data

In today's data-driven world, organizations are collecting massive amounts of data, often operating under the assumption that more data equals better insights. This talk challenges this assumption by exploring the hidden costs and consequences of poor data quality, using real-world examples from building management systems and IoT sensors.

Through practical examples from indoor climate monitoring, we'll examine how seemingly minor issues like sensor calibration errors, missing data points, and conflicting readings can cascade into significant problems - from wasted energy and unnecessary maintenance visits to flawed machine learning models and incorrect business decisions.

Attendees will learn how to:
Identify common data quality issues in their systems

Understand the real cost implications of poor data quality

Implement practical strategies for data validation and quality assurance

Develop effective data collection and maintenance protocols

The presentation will feature case studies from building management systems, demonstrating how issues with temperature, humidity, and CO2 sensors can impact building operations and decision-making. We'll explore how conflicting data between different sensor types (like smart thermostats and window sensors) can create confusion and lead to suboptimal automation decisions.

Whether you're managing building systems, developing IoT solutions, or working with any kind of sensor data, this talk will provide you with practical insights and strategies for ensuring your data collection efforts truly support your objectives rather than undermining them.

Speaker: Marin Holi

Organizer: Finn Gustafsson, IDA IT

Participation free of charge for members of IDA IT and DANSK IT

Refreshments: Coffee / tea and sandwich / soft drinks.