Data pipelines are a critical element of any modern, data-driven organization. With the right tools in hand, data analysts can quickly build resilient data pipelines for your analytics infrastructure. From orchestration to monitoring, these tools can march your business towards advanced levels of automation, as well as improved transparency into how your pipeline functions along every step of its journey.

Welcome to the data movement movement. Use Fivetran and Hightouch to replace your existing iPaaS workflows and build warehouse-centric data pipelines.

A beginner’s guide to setting up ELT data pipelines.

Data integration is the process of combining data from different sources and formats to create a unified and consistent view of the data. This involves merging data from multiple databases, applications, and other sources into a single repository, and transforming and formatting data so that it can be easily accessed and analyzed. Data assets need quality controls to ensure they are valid and reliable as many teams within an organization leverages the same data for different purposes.

The data catalog is a critical step in the movement toward becoming a data-driven business. Here are 4 table-stakes questions to ask yourself to deliver reliable, trusted data.

Data pipeline tools help you create and manage pipelines that extract, transform and move data into a central location. Find out what the best tools are here.

When choosing to build or buy, consider whether the following challenges are worth the squeeze.

“Data pipeline” and “Extract, Transform, Load” (ETL) are common phrases encountered in just about every data integration. But what’s the difference?

From cost-effectiveness to what adds business value — what Autodesk considers critical when deciding whether to buy versus build data pipelines.

The five things you need to know about data observability in a data pipeline are: Becoming a data-driven organization is a vital goal for businesses of all sizes and industries—but this is easier said than done. Too many companies fail to attain the fundamental principle of data observability: knowing the existence and status of all the enterprise data at their fingertips.