Data Streaming Strategy for 2025: What Industry Experts Recommend

Hybrid cloud, AI readiness, and scaling operations

2025 brings new challenges for data teams: hybrid cloud complexity, scaling demands, and AI readiness. We brought together Casey O'Shea (CTO at Atyeti) and Howard Holton (COO at GigaOm) to discuss practical strategies for navigating this environment.

Key insights from the conversation are below. The full podcast recording is at the end of this post.

Start small to accelerate data maturity

Large-scale, top-down data initiatives rarely work. Data leaders are shifting to smaller, targeted approaches that deliver value faster.

Targeting specific datasets or processes enables quicker wins and clearer ROI. This builds organizational buy-in.

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. Breaking down silos ensures all stakeholders share responsibility for data quality and strategic goals.

Tools require process and people

Modern tools address complex data challenges. But tools alone are not the solution. They must be paired with robust processes and skilled teams.

Effective tool adoption requires a clear focus on specific use cases. Start small and scale as teams grow comfortable.

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

Howard Holton, COO at GigaOm

For AI integration: use cases with limited bias and clear outcomes are ideal for early adoption. All AI applications require expert oversight to validate results.

Data quality is the foundation for AI

Without a strong governance framework, organizations build on unreliable or inconsistent data.

Key strategies:

• Metadata management: Track data ownership and flow for accountability.
• Standardized definitions: Align on consistent metrics to minimize confusion.
• Verification processes: Engage experts to validate data in high-stakes scenarios like 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 is a continuous process. It requires alignment across teams and consistent monitoring.

Phased modernization over disruption

Modernization is a priority for staying competitive. The speakers emphasized a phased approach: upgrade tools and processes focusing on the most impactful areas first.

Assess team readiness before adopting new tools. Ensure they have the skills and capacity. Encourage curiosity and innovation to foster 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

Prioritize initiatives that deliver measurable value. This achieves progress without overwhelming teams or systems.

The path forward

Focus on incremental improvements, leverage tools effectively, and foster collaboration. These strategies position businesses to thrive in 2025.

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

Watch the full podcast below for the complete discussion.