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Topics: Business Intelligence, Leadership, Strategy
How are Analytics Projects different from standard IT execution projects
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I am in Project Management since last 6 years managing Digital Transformation and BI projects. For the last 2 years I am managing Data Science projects. What I find is there is huge difference in the way Data Science projects need to be handled. And this is where the success / failure of the Data Science projects will lie in the next 2 years. I want to know from experts and peers on their experience and views. I do not want to start with listing what difference I feel, as that will lead to a focus on those points. Thank you all for participation.
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Its true each project has to be handled differently considering the domain and stakeholders of project. Documenting expectation of stakeholders of the project is the first step considering the above mentioned issues noted.
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I have managed that kind of projects too. The main point between Data Scientist and other professionals is the fact that Data Scientists are harder to find (even those days..), machine learning and bigdata tools still a little scary for the most of the companies... and because of all that some Data Scientists behavior like little "popstars" in the company. The best thing to do as PM (in my opinion) is learn how to deal with them and delivery the project
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There are no difference from project management perspective. The same with other type of project manager. What you have to decide is if you want to be a subject matter expert on a field or you want to be a project manager. Just to comment, I have lead both times of projects from the beginning of the concepts, I mean, before buzzwords like Data Analytics appears on the market (all this stuff is outside there from 1990 and before)
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Fully agree with Sergio. I do since quite some time SAP implementation projects with many of them having a big portion of BI scope content. From project management perspective no difference. Difference is within the work-package content or sprint content to execute the work.

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