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Filling the data scientist gap, part 3: Challenges and solutions for the road ahead

Enabling domain experts to perform data science has obvious benefits to the business. However, this is not something that happens overnight. As organizations begin to put data analytics tools in the hands of their domain experts, challenges can arise, including showing the value of data analytics to those who are skeptical.

Being ready to address these challenges will keep projects moving forward, and keep the critics at bay. Learning curve for new technology Challenge: The pace of innovation in the data analytics space is very fast, and each new piece of technology has its own learning curve. In many cases, the original technology is developed by computer scientists, with the intended audience also being someone with very strong programming skills.

Source: embedded-computing.com
Author: Seth Deland

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