At OWOX BI, we empower marketers and data analysts with advanced tools for streamlined marketing analytics and data transformation. We are thrilled to announce a significant enhancement in our Transformation product — the introduction of Operation Run Lite.
Simplified Data Processing for Greater Flexibility
Numerous companies have embraced OWOX BI Transformations to effortlessly incorporate analytics-ready data into their reports. Recognizing the diverse needs of our users, we understand that variations in report types and data volumes exist. For some organizations, assuming full responsibility for data processing costs in the Google Cloud Platform (GCP) is more convenient.
In response to this, we have introduced Operation Run Lite as a new Consumption Unit in the Transformation product. The premise is straightforward — each run of a distinct Operation in a Transformation is counted as 1 Operation Run Lite, irrespective of the processed data volume. Detailed examples of these calculations can be found on this page.
Operation Run Lite differs from the regular Operation Run in that it is executed on behalf of the customer's GCP project. This delineation offers users greater flexibility in managing their data processing costs within their own GCP environment.
You can control the Operation Run Lite count for each Operation in the same place on the screen:
How to Optimize Your OWOX BI Transformation Experience
If you are eager to leverage OWOX BI Transformation, receive analytics-ready data for marketing reports, and independently oversee and cover all data processing costs in the Google Cloud Platform, simply reach out to your dedicated OWOX manager to discuss and modify the terms of your contract.
Should you have any inquiries or require assistance regarding Consumption Units in the Transformation product, our support team is here to help. Reach out to us at bi@owox.com, and we'll be happy to guide you through any questions or concerns.
Thank you for choosing OWOX BI, and we look forward to continuing to support your data analytics journey.
Happy analyzing!
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