In the rapidly evolving landscape of technology, companies are eager to
adopt the latest innovations, such as advanced AI applications like
ChatGPT. However, this enthusiasm often overshadows a crucial
underlying issue: the accumulation of data debt. As a Software Architect,
I've witnessed firsthand the ramifications of overlooking this critical aspect.
My talk will go into the intricate world of data debt, drawing parallels and
contrasts with the more commonly acknowledged concept of technical debt.
Data debt, although less visible, has a profound and far-reaching impact on
an organization's operational efficiency and strategic decision-making. It
arises from various factors, including inconsistent data management, lack
of comprehensive data strategies, and the rapid pace of technological
advancement outpacing data governance. This accumulation not only
hampers day-to-day operations but also poses significant challenges for
the adoption of new technologies.
Throughout the talk, I will share insights from my extensive experience in
the field, focusing on real-world scenarios and projects. I will discuss
strategies to identify, quantify, and manage data debt, emphasizing the
importance of a proactive approach to data management. The talk will also
explore how effective data governance can align with an organization's
evolving needs and goals, thereby turning potential liabilities into assets.