Data Science Technology New Year’s Resolutions for 2021
2021 is the start of my 10th year in data science/machine learning/advanced analytics technology. In that time, I have cut my teeth in advanced analytics at SAS, spent a year with H2O.ai in the valley drinking from the open-source firehouse, and helped introduce and scale Dataiku in the US more than 1000%.
Now, as an independent consultant and analyst for Datagrom, I am exposed to new technologies and I get to see how they succeed (and often fail) to integrate with business processes and ultimately provide value. How I think about data science technology constantly evolves.
In 2021 I aim to be better at evaluating software and the companies that support it. Here are my New Year’s resolutions for 2021 (Data Science Technology Edition)
Data Science Platform Evaluation Criteria for 2021
User Personas Rule
When looking at technology, does it have a clear persona that it targets, and is it the best possible option for that persona? Favor the tool that remedies the pain best for the persona experiencing this pain. That is, buy coders coding tools. Clickers clicking tools.Consumption Pricing Matters
Do not pay for software you don’t use. If the company doesn’t have a consumption-based pricing option, they might be hiding something about adoption.Avoid unnecessary cloud costs. Go Hybrid.
Most data science is about experimentation. The cloud doesn’t care about this. 100% cloud is not an option for developing data science. Use your local resources!Avoid lock-in because you can
Only allow vendor lock-in if there is a compelling reason to do so. This means that proprietary technology should be highly productive. If it isn’t, pass.Adoption swamps everything else
When users find a way to accomplish work, it will take a substantial (10X) improvement in productivity in order to switch. (Excel still dominates most data and BI work). Why? People don’t love learning new ways to do the same work. If you buy a new technology, make sure it is already growing in adoption during the POC stage.
What are your New Year’s resolutions with data science technology?
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