Best Practices in Data Science: Ten Keys to Operational Success and Business Value

Data science is unique among new technologies in its promise for delivering greatly increased profits at near zero additional cost or organizational change. It is a fundamentally required technology for companies seeking to undergo a digital transformation. Yet most companies are struggling with how to make data science safe and productive. They have the desire and often the knowledge to make data science operational but lack best practices and guidance for selecting product features that can make it a reality.

In this research, we investigate why data science is so powerful but underutilized in business. We then review the issues involved in its complexity and the dangers that arise when it is used incorrectly. Eight high priority best practices and product features are then detailed that will make data science part of daily business operations.

This report will provide guidelines for evaluating and improving data science practices within large organizations. It will also provide details about necessary product capabilities that customers can use to make well-informed product selections.

Readers Will Learn:

The barriers preventing companies from realizing the full potential of data science
What operationalizing data science means and why it is critical for success
Eight best practices and product features for operationalizing data science across the enterprise
How to build organizational support and multi-disciplinary teams for implementation
How to construct a business plan to optimize the return on investment from data science

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