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Jennifer Pip

Data Science: 5 tips on how my company should do it?

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The saying that no two companies run their business the same definitely applies on this topic. Providing advisory on Data Science and AI is what we do, and we’re good at it. So when a client or old-colleague bumps into me at a conference and any variation of the question “how do I start with data science at my company?”, I first collect myself, take a deep breath and pause before I geek out about this topic that is amazing. Then with calm poised self I ask, “Why do you think your company needs a data science initiative?”

That’s right. We shouldn’t all believe that every company needs to spend time, money, and resources on data science, data mining, or advanced analytics. But when the justification to do so can be rationalized with some strong people ROI or business ROI, then all lights should go green and here’s 5 quick tips that both rationalize and move an organization in the right direction.

#1 – Determine that What of Data Science?

#2 – Determine the Who of Data Science?

#3 – Consult and Expert – Even if Just an Hour

#4 – Talk Infrastructure First

#5 – Discuss Iterative Development, Maintenance, and Outputs

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Building a Generative AI Competency (or the First Gen AI Project)

When Building a Generative AI Competency one must identify the necessary infrastructure, architecture, platform, and other resources and partners that can help an AI initiative be successful. We have just like many data warehouse and digital transformation initiatives over the last 20 years fail because of poor leadership, or companies only going half in on the objective.

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