Enterprise data environments are becoming increasingly complex. Data is spread across various distributed environments, while demand for trusted, timely data for analytics and AI continues to grow.
Traditional data pipelines are struggling to keep pace. Fragmented tooling, brittle integrations, data quality issues, and pipeline failures create bottlenecks, increase operational overhead, and undermine trust in data.
DBTA held a webinar, Modern Data Pipelines: Integration, Automation and Trust, with Raji Narayanan, vice president, data integration and product management at CData and Cameron Leblanc, senior technology evangelist at CData, who discussed how organizations are building more automated, reliable, and trusted data pipelines.
According to Narayanan and Leblanc, who cited McKinsey, “8 in 10 enterprises cite data limitations as their #1 barrier to scaling AI.”
Most enterprise teams have the ambition, but the pipeline is where trust breaks down, the pair said.
The teams that win with AI are not the ones with the most models. They are the ones with the most reliable data.
Data pipelines are no longer a back-office function. They are AI infrastructure, as critical as compute and networking.
AI-ready data means three things: freshness, trusted format, and reliability through auditable pipelines.
The moment a pipeline breaks mid-run, a model loses its grounding. Every inference downstream runs on stale data.
Narayanan and Leblanc said, CData Sync was built for this, offering: continuous, governed, production-grade data movement at enterprise scale.
CData Sync provides easy to use, real-time modern data pipelines. Other features and capabilities include:
- Enterprise-grade connectors with unmatched speed and depth
- Deploy anywhere: on-prem, private cloud, and hybrid
- High-availability and node clustering across
- Sync deployments CDC for real-time synchronization: no full table scans, no batch windows
- Transform data using custom SQL or dbt data modeling
- Predictable, scalable pricing based on connections, not rows
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.