Requirements Gathering With Fewer Tears

Avoid time-consuming stakeholder back-and-forths with strategies that promote conciseness, accuracy and clarity.

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Data science instructors providing learners with clear, concise instructions for tasks, homework and projects are failing students.

Not because they’re spoon-feeding them information or coddling them.

But because you will almost never encounter this level of specificity and clarity (at least initially) when you begin your first data engineering job. To be clear, this is not the fault of management or a stakeholder.

A data engineering task is a business project at its core, so it takes careful, precise and detailed back-and-forth communication to not just execute the deliverable–but to find out what your stakeholder *really* wants.

Now, there are certainly exceptions to this formality. If you’ve been working closely with someone for years, they may be able to explain the concept of your task in 1 sentence.

As The Office’s Kevin Malone wisely said: “Why use many words when few words do trick?”

Unfortunately, your initial attempts at requirements gathering will likely take many, many words.