AI News, Lead your own data science projects with the 3 Ps

Lead your own data science projects with the 3 Ps

There's a lot of literature on learning the technical aspect of data science: statistics, machine learning, data munging, big data.

But what about when you are ready to spread your wings and lead a project yourself or embark on a project independently?

Here you need a different sort of storytelling - the type that communicates why you are working on a project, what the value is, and what you have accomplished.

Pair the 3 Vs of big data with the 3 Ps of model development to increase the success rate of your project.

Compare this to many classroom settings and entry-level positions that detail every last minutiae of work. This is equivalent to color-by-number coloring books.

At some point in your drawing career you graduate from this detailed instruction and move to coloring books without numbers.

As your career advances, your success will be contingent on transforming blank sheets of paper into something valuable, ie identifying opportunities from data.

If you don't know what you are solving nor who benefits, you most certainly will fail as your project becomes indistinguishable from entertainment.

As you work through the problem definition, you may find that there are numerous people who benefit, each with a slightly different problem that can be solved by the same model or analysis.

That may be true, but as you advance in your career, you will be expected to not only lead initiatives but drive new ones.

Documenting your process in advance will clarify your thinking and make it easier for your collaborators to understand and review your approach.

Despite data science being a team sport, it's important for practitioners to be able to work on tasks and projects independently.

Using the 3Ps method described above will help you crystallize your thinking and improve your communication with others.

Mastering this technique may even reduce the number of dead ends you encounter, quickening the journey to completion.

Brian Lee Yung Rowe is an Adjunct Professor at the CUNY MS Data Analytics program and also the founder of Pez.AI, a chat-based data analysis and computing platform with a conversational AI interface.

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