Data is everywhere and putting it to work is challenging
Today's enterprises run on dozens of applications: ERPs, procurement, HR and finance systems, and more. The data inside them is critical, but it's difficult to access and messy. If teams can land the data, it requires weeks or months of cleanup, normalizing and modeling before it's usable.
Difficult and complex data sources
Nested formats, undocumented fields, and custom configurations. The systems your company runs on, like SAP S/4HANA, Ariba, Coupa, Infor, Oracle and more, are the hardest to integrate.
Backlog of integration requests
New analytics and AI initiatives need additional data sources and access to datasets. Teams spend months slogging through the list and business projects are stalled.
Months of work before data is usable
Getting data into the warehouse is only the first step. Normalizing, relating, associating, and contextualizing work can stretch timelines to months, before anyone can run a single report.
Unpredictable pricing
You face row-based pricing, usage overages and data volume fees. As your data needs grow, so does an unpredictable bill, making it hard to plan, justify, or scale.
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