Chapter 4
Managing Change in Data Science
IN THIS CHAPTER
Exploring why change in data science is different
Approaching ways to manage change in data science
Listing things to avoid in change management
Utilizing various change techniques
Guiding steps to start your change journey
Investing in data science and a data-driven approach means understanding and dealing with the change that needs to happen. Although the inevitable data science transformation in society may not have fully arrived yet, organizations still need to get ready. The time for standing on the sidelines, waiting to see what other companies are doing, is over. The time to act is now.
Those companies best positioned to manage the needed change driven by data science in the next decade will be the ones that start preparing now. The day has come for companies to invest time in strategically building up an understanding of what is needed and capture the intent in a data science strategy — not just in one area or function, ...
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