Published: 21 May 2024
Managing self-service analytics is often a struggle for many organizations. To prevent SSA from becoming a defective operating model, data and analytics leaders should reevaluate their approach while keeping measurable business outcomes, potential self-service users and adequate governance top of mind.
Self-service analytics (SSA) initiatives across decentralized teams often devolve into siloed analytics that are rarely tracked through measurable metrics or alignment with business outcomes.
Business users are underprepared to leverage SSA, even with generative AI (GenAI)-enabled natural language interactions, due to insufficient data literacy training and inadequate focus on the analytical capabilities that user personas need.
According to the 2023 Gartner Analytics and AI Adoption Survey, solving risk and governance issues is the top challenge for SSA developers. Without adequate guardrails, these initiatives result in duplication of dashboards, reports and metrics that ultimately leads to data distrust and diminished business
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