Transforming data into insight

Data can be a source of strategic advantage for your enterprise, but only if you can unlock its full potential. The paradox is simple: more data creates more complexity, which reduces visibility and makes it challenging to deliver value at scale.

For the IBM Chief Data Office (CDO), extracting value from data is important. Data fuels IBM’s goal to become a more productive company, and central to this strategy is the integration of data from various sources into pipelines that deliver meaningful insights. A data pipeline is a sequence of operations that involve extracting, transforming and loading data from diverse sources into a data warehouse or lake—ensuring consistency and enabling analytics at scale.

With nearly 4,000 data pipelines to manage, the CDO team found the traditional approach cumbersome and time-intensive. Manually monitoring data pipelines and troubleshooting issues consumed a substantial amount of time and was prone to human error. “Managing pipeline health across our large volume of pipelines was a significant challenge, especially when teams are using different products,” explains Ashley Delport, senior engineering manager at the CDO. “We needed a solution that could continuously monitor data health, proactively identify and resolve issues such as missing data and notify our teams if service was going to be impacted.”

The team required a more efficient approach as they scaled data pipelines for business insights and AI use cases. They wanted an innovative solution; one that offered real-time visibility, automated monitoring and enhanced collaboration. Most importantly, the team needed to preserve the trust of the thousands of users who relied on the CDO for accurate, timely, high-quality data every day.

The CDO team chose IBM® watsonx.data® integration, a unified control plane that offers continuous data observability. The team began with a pilot focused on data from IBM’s merger and acquisition activities. The goal was to gain real-time visibility into pipeline performance.

 “The real-time monitoring and alerting capabilities have saved us time and effort. Specifically, we've seen an estimated 85% reduction in manual monitoring and troubleshooting in a pilot,” says Sheeba Prakash, senior technical staff member.

With the solution’s intuitive interface, the team could easily track pipeline health, identify bottlenecks and resolve issues quickly. Automated workflows and customizable dashboards measurably streamlined pipeline management. The solution freed up engineers to focus on accelerating data integration in acquisition scenarios.

After the successful pilot, the CDO team decided to expand their adoption of the data observability capability as a single source of truth for insights into the company’s overall data pipeline performance. “Data observability has elevated our operational excellence. It has made us more proactive instead of reactive to data pipeline issues,” adds Delport.