Organizations must add data science and machine learning capabilities to their analytics and BI toolsets without creating redundancy and overlap. We show data and analytics leaders how to form a tool management strategy that fosters innovation, evolves analytics needs and enables economies of scale.
- Change How Your Organization Views Analytics, BI and DSML Tools by Managing Them as a Portfolio
- Conduct an Initial Assessment of the Life Cycle of Tools in Use
- Link Tools, Capabilities and Business Objectives With Analytics Blocks
- Balance Productivity and Innovation by Matching Analytics Blocks to Gartner’s Pace-Layered Application Model
- Define a Review Method for Tools, Based on Analytics Capability
- Form a Steering Committee, Share Results and Schedule Periodic Reviews
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