10 Best Practices for Modern Data Integration
Getting Data Fast and Getting It Right
Before big data and continuous data came along, data movement was pretty simple. And hand coding was often the most efficient way to build static, linear pipelines.
Today, the complexity of modern data integration means custom code quickly becomes a bottleneck to self-service, scaling, and optimization of cloud services. In fact, 66% of data experts think that this data complexity and friction can have a crippling impact on digital transformation.
Unlock the potential of advanced analytics, machine learning, and AI with the skills and people you have today by bringing speed, flexibility, and resiliency to your data pipelines. Deliver the data to those who need it quickly and accurately.
Download the 10 Best Practices to learn how to:
- Reduce schema specification to lower technical debt
- Handle data drift to manage the downstream impact of bad data
- Optimize legacy pipelines for cost and efficiency in the cloud
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