Adapting to Data Challenges in a Fast-Changing World

As the data landscape evolves, 2025 promises new challenges and opportunities for businesses. Organizations must refine their strategies to address hybrid cloud complexities, scale operations, and prepare for AI readiness. Our recent podcast, brought together experts from Conduktor, Atyeti, and GigaOm to explore practical strategies for navigating this rapidly changing environment.

Below, we’ve captured key insights from the conversation. For the full experience, don’t miss the podcast recording at the end of this post!

The Data Maturity Journey

As organizations strive for data maturity, the focus has shifted from large-scale, top-down initiatives to smaller, more targeted approaches. Instead of overhauling entire systems, data leaders are prioritizing incremental progress to deliver value faster.

Key Insight: Targeting specific datasets or processes enables quicker wins and clearer ROI, fostering organizational buy-in and alignment.

You don’t need to transform everything at once. Start small, measure your impact, and let the results build momentum.

Casey O’Shea— CTO at Atyeti

Collaboration remains central to achieving maturity. Breaking down silos and fostering alignment among teams ensures that all stakeholders share responsibility for improving data quality and achieving strategic goals.

The Role of Specialized Tools

Modern tools play a vital role in addressing the challenges of today’s complex data environments. However, the speakers stressed that tools alone are not the solution; they must be paired with robust processes and skilled teams.

Key Takeaway: Effective tool adoption requires a clear focus on specific use cases, starting small and scaling up as teams grow comfortable with new systems.

Tools can fill gaps, but they’re only as effective as the processes and people behind them.

Howard Holton— COO at GigaOm

Additionally, AI integration should be approached thoughtfully. Use cases with limited bias and clear outcomes are ideal for early adoption, but all AI applications require expert oversight to validate results.

Ensuring Data Quality for AI Readiness

High-quality data is the foundation of successful AI initiatives. Without a strong governance framework, organizations risk building on unreliable or inconsistent data.

Key Strategies for Data Quality:

• Metadata Management: Clearly track data ownership and flow to ensure accountability.

• Standardized Definitions: Align on consistent metrics to minimize confusion and enable reliable decision-making.

• Verification Processes: Engage experts to validate data in high-stakes scenarios, such as regulatory compliance.

AI is only as good as the data it learns from. If your foundation is shaky, your results will be too.

Quentin Packard— SVP of Sales at Conduktor

Governance isn’t just a checkbox—it’s a continuous process that requires alignment across teams and consistent monitoring to adapt to new challenges.

Modernizing the Tech Stack

Modernization is a key priority for organizations looking to stay competitive, but it’s not without its challenges. The speakers emphasized a phased approach to upgrading tools and processes, focusing on the most impactful areas first.

Actionable Advice: Start by assessing the readiness of your team. Ensure they have the skills and capacity to adopt new tools effectively. Encourage curiosity and innovation within your teams to foster a culture of continuous improvement.

Modernization doesn’t have to mean disruption. It’s about finding the balance between progress and practicality.

Casey O’Shea— CTO at Atyeti

By prioritizing initiatives that deliver measurable value, organizations can achieve meaningful progress without overwhelming their teams or systems.

Closing Thoughts: Preparing for a Data-Driven Future

The future of data is complex, but the strategies shared during our webinar highlight a path forward. By focusing on incremental improvements, leveraging specialized tools effectively, and fostering collaboration, businesses can position themselves to thrive in 2025 and beyond.

The path to data maturity isn’t a sprint; it’s a series of thoughtful steps that lead to lasting success.

Howard Holton— COO at GigaOm

For a deeper dive into these strategies, watch the full podcast below and hear directly from our experts.