Overview
One of our clients in the online education industry provides courses across multiple categories to 20 million customers nationwide. With a focus on student outcomes, data reveals patterns in learning effectiveness and course completion, allowing to continuously improve course quality and maintain a prime market position.
In 2024, a period of rapid business expansion revealed gaps in data operations and collaboration, between the Data Engineering and Business Intelligence teams. Learn how our client increased operational coverage, decreased development timelines, and reduce time to insights with CloudEQS Managed Data Operation Services.
The Problem – Aligning people, processes and data pipelines to critical metrics
The Business Intelligence (BI) team supports the performance marketing, financial planning and acquisition of business units as well as providing internal auditing on compliance and regulatory requirements. The gap was two fold:
- Organization structure: Data Engineering & BI teams reporting to separate leaders.
- Process: Translating the business requirements into technical plans to make data readily accessible for timely business decisions.
Operating in a data-hungry organization, the Data Engineering team needed to provide timely data to the BI team.
Many of the teams that we serve are in our reporting environment every single day. If they launch a new campaign, they want to use critical metrics to make fast decisions. It’s amazing, but it places a lot of expectation on us to spin up and integrate new datasets very quickly and that is a challenge in a lean team.
– VP of Business Intelligence
Key challenges included:
- Development bottlenecks – slow delivery times creating an accumulating queue of unresolved requests.
- Inability to scale – data operations due to limited internal resources and budget constraints.
- Delayed response – time-zone gaps, system failures, and one-person support coverge.
- Inefficiencies – handling of new data sources during acquisitions.
- Alignment – misaligned priorities between teams causing project delays.
Coping with system failures and keeping up with day-to-day work was proving to be too much. We needed more coverage from a time-zone perspective and more system knowledge. But securing budget to grow the team from within was not possible.
– CTO
The Solution – CloudEQS Managed Data Operations Support
Sharing technical knowledge through documentation, playbooks, and industry best practices, the CloudEQS Data Operations as a Service offering extended the data team’s capacity and established a scalable operation in 3 key pillars:
- Production handover – CloudEQS team owning and monitoring production environments
- Department handover – CloudEQS team owning Data Engineering
- Consolidated leadership – Data Engineering & BI reporting under 1 leader
By realigning the organization, our client has created an outsourced Data Engineering function with the skills, systems, and processes that allow the BI team to focus on the business requirements and delivering strategic business outcomes.
CloudEQS observed and documented on the job to formulate playbooks for primary and data mart schemas that we can apply for future mergers.
– VP of Business Intelligence
The Results
The CloudEQS Data Ops team bridged time-zones, alleviating pressure on in-house data engineers, and synchronized the data in time for the US team to begin their work.
Specific results included:
- Stabilized Production within 2 weeks
- Reduced ticket backlog
- Quicker delivery of data with aligned SLAs
- Faster time to insights
It only took two weeks for us to see light at the end of the tunnel where the CloudEQS team stabilized production. By the eighth week, the CloudEQS team had full data engineering ownership.
– VP of Business Intelligence
Conclusion
This project showcases the value of the CloudEQS Data Ops as a Service offering. Our client was able to transform its data operations, bridge gaps between teams, and handover production support. Resulting in a scalable operational model to drive strategic initiatives.
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