The Analytics Lifecycle Toolkit
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Analytics involves more than just assembling a group of data scientists and analysts. Analytics leaders must be concerned with a sphere of activities to achieve their business goals. Organizational capabilities must include five key elements, each of which comprise the Analytics Lifecycle.
The Analytics Lifecycle Toolkit: A Practical Guide for Effective Analytics Capability by Gregory S. Nelson, Wiley ©2018
The Analytics Lifecycle Toolkit, by Gregory S. Nelson
These five best practice areas are used throughout the design, development, and delivery of analytics products. While not every analytics project (problem, project, product) will exercise each of these areas in the same manner, they provide a framework for ensuring that analytics projects deliver value and the effort appropriate to their outcome.
This chapter covers:
- An introduction to the Analytics Lifecycle.
- The various goals of analytics.
- Four types of analytics deliverables.
- The elements of design thinking.
“This book condenses a lot of deep thinking on the wide field of analytics strategy. Analytics is not easy – there are no quickie AI/BI/ML shortcuts to understanding your data, your business, your processes. You have to build a diverse team of talent. You have to respect the hazards of “fishing expeditions” that may need false-discovery-rate adjustments. You should consider designed experiments to get the true behavior of a process, something that observational data may hint at, but not provide complete understanding. There are dimensions of data wrangling, feature engineering, and data sense-making that all call for different skills. But with deep investment in analytics comes deep insight into processes and tremendous opportunity for improvements. This book puts analytics in the context of a strategic business system, with all its dimensions.”
John Sall, Co-Founder and Executive Vice President, SAS
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