The Business Case for a Multi-Persona Data Science Platform

A single, accessible data science platform empowers all users to leverage insights from the data in their work

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What it Does

A data science platform enables users with varying levels of expertise to utilize data science, bridging the gap between technical and business competencies. It empowers everyone in the organization to perform predictive analysis and obtain data-driven business insights.

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  • Halve decision-making time by leveraging data science-driven insights across the organization.
  • Achieve labor cost reductions of 20% to 30% by enabling business stakeholders to perform analysis previously done only by data scientists.
  • Increase top-line revenue by 5% to 15%, in a sales use case, through broader adoption of data science across the organization, due to more intelligent and timely decision making.
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Moderate: With data scientists and engineers in short supply, accessible data science platforms empower business users to benefit from these tools. Adoption of multi-persona data science platforms is strategically important to business success.

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Risk Level

Moderate: As with all analytics-related initiatives, data security and protection vulnerabilities pose risks. Poor model transparency, inadequate training and change management, and deployment struggles with business user-created solutions are risks.

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30/60/90 Plan

  • 30 days: Identify use cases and resources, plan a roadmap, and identify data to be used. Prioritize use cases on impact and feasibility based on availability of required data.
  • 60 days: Set business goals and evaluate solutions before adopting a platform.
  • 90 days: Deliver initial proof-of-concept and then scale across use cases. Monitor and optimize ML models.
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Time to Value

Initial value of integrating a multi-persona data science platform can be realized within three to six months. Further value will accrue at the one- and two-year milestones.

What Is a Multi-Persona Data Science Platform?

A multi-persona data science platform provides automation and a visual approach to data science for business users while also allowing coding-based approaches for advanced professionals. “Multi-persona” refers to the ability for team members with different skill sets and expertise to collaborate within a unitary data science platform to build solutions together.

In the past, data science and knowledge extraction from data required extensive technical knowledge, but with the help of multi-persona data science platforms, automation can fill in for many technical skills. This automation enables non-technical users to mine large amounts of data to aid decision-making and operational efficiency, providing opportunities for competitive advantage. Technical users can nevertheless leverage multi-persona data science platforms at levels more advanced than they are accustomed.

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