How much business know-how do you really need?
How much business know-how do you really need?
It depends on this...
When people think of data roles, they assume we’re talking about tech roles 💻. And we are, BUT, as you know, business acumen is also crucial to one’s success in the data field!
So, let’s take a look at some of the primary data roles, the level of biz acumen needed, and how they support the business in generating greater profit…
👨🏻💻Business Analyst 👩🏿💻
Biz acumen requirement = High ⬆️
Business Analysts are closely linked to traditional business roles (i.e. business managers and executives).
Analysts play an important role in cross-collaboration between teams by leveraging their existing knowledge and communication skills.
They use existing data to analyze processes, systems, organizational units, and overall problems in order to formulate effective business solutions.
Despite being closely involved in both business and technology, they are firmly rooted in the business world.
👩🏼💻 Data Product Managers & Project Managers 🧑🏽💻
Biz acumen requirement = High ⬆️
The role of the project manager is to manage and support the implementation of data.
In contrast, data product managers serve as mini-CEOs for the company's data products.
Their role is to ensure that projects or products are delivered on time and accurately, and it is these products and projects that drive profit gains.
Both roles are part of the business side 💼, but they also work directly with the technology 🖥️ side of things.
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🧑🏿💻 Data Scientists & Analysts 👩🏻💻
Biz acumen requirement = Medium ➡️
Although both are on the technology side of the business, data scientists and analysts are closer to the business than engineers and software developers.
By executing the requirements outlined by data projects or product managers, they assist companies in generating increased profits.
While both roles involve data implementation, analysts focus more on business consulting than strictly data science.
A data scientist or a data analyst needs some business acumen, but not in the same way that a data project manager, product manager, or business analyst does.
👨🏼💻 Machine Learning Engineer & Data Engineer 👩🏽💻
Biz acumen requirement = Low ⬇️
People in these roles are almost all purely technical data implementers.
So, when it comes to business acumen, not a huge amount is needed for things like developing decision engines or building data systems.
The aspects of your product or project that deal with requirements gathering or consulting are generally handed to you by a data project manager, data product manager, or business analyst.
But, even with this low bar for business acumen, data and ML engineers must still produce documentation to support their products.
[Image source: Data Science for Dummies Ed.3]
The above images will help give you a better understanding of how all of these primary roles work together to generate greater profit for the business.
If you have the tech skills and are worried you don’t have the business know-how needed to succeed in any of the above roles… I got you!
In my next email, I’ll be showing you exactly how to up-level your business acumen skills!
Catch you then!
Lillian
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At Data-Mania, we offer fractional CMO support to B2B tech companies. We specialize in go-to-market & product-led growth for high-growth data and AI startups. Learn more by visiting our website.