Broadly, there are three structural options - centralized, decentralized, and hybrid.
Centralized Analytics
In traditional centralized models, specialized IT and analytics teams handle data management, modeling, and insight delivery to business stakeholders. The benefits include consistency, control, and oversight. However, this risks slow time-to-value and a lack of contextual insights.
Decentralized Self-Service Analytics
This democratized approach provides business teams direct access to data to generate their own tailored insights rapidly without IT bottlenecks. Benefits include faster decision velocity, localized analysis, and greater autonomy. But decentralization heightens risks around security, tools sprawl, and accuracy.
Balanced / Hybrid Model
An integrated model combines the strengths of both - with centralized data platforms, oversight, and advanced modeling complemented by decentralized self-service analytics capabilities for business teams within governed guardrails. The hybrid approach balances standardization with flexibility.
The Promise of Self-Service Analytics
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