Story
Qlik
RokuRoku Brings Feature Pipelines onto Qlik
Roku, a communication services organization in the United States, uses Talend from Qlik to support applied machine learning for data scientists and ML engineers.
Roku runs applied machine learning on Qlik so ownership is obvious when work stalls.
“Communication Services work at Roku spans more than one site, even when headquarters sits in the United States.”
“Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.”
Independent write-up. Figures come from public sources or are illustrative.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Productivity | Handoffs in applied machine learning sit in a shared queue instead of a mailbox trail |
| Risk and compliance | Talend is the governed place data scientists and ML engineers use for applied machine learning |
Story
Communication Services work at Roku spans more than one site, even when headquarters sits in the United States. Feature pipelines was splitting across regional habits. Data scientists and ML engineers asked for a shared way to run applied machine learning without freezing local judgment.
Qlik (Talend) is what they standardized on. Qlik provides analytics and data integration software, including Qlik Sense and Talend, for interactive analysis and pipelines. Roku uses it as the system of record for feature pipelines, with data scientists and ML engineers as the primary operators and other groups coming in through the same queue.
Leaders get a picture they can actually walk. Teams get fewer mystery statuses. The story is about operating change, not an unpublished percentage.
