Augmented Analytics – 4/4: Unchaining the Data Scientist

Disruptive technologies are often scary, especially to people who fear that the technologies will make their jobs and possibly even their careers obsolete. Imagine how much the carriage driver must have feared—and likely hated—those “horseless carriages” that have revolutionized the way that we travel. What the Luddites fail to grasp is that those new technologies often create more jobs than they supplant. They also free up our time so we can devote ourselves to more satisfying work. After all, who really wants to do a tedious task that a machine can do for us?

As we mentioned in the first blog of this series, data analytics is just entering a disruption phase. That truth might frighten some readers, but you data scientists should know that you aren’t in danger of becoming obsolete anytime soon. Augmented analytics isn’t the enemy. In fact, it will remove the most tiresome and labor-intensive work from your plate. Those tasks that used to eat up so much of your day are going to be handled by AI. No longer will you be chained to your desk, forced to engage in mind-numbing drudgery.

Much of the work done in the earliest stages of data analysis involves educated guesses. With so many data points and possible combinations of variables, it’s virtually impossible to know how useful a model will be in revealing actionable truth until the model is built and tested. That process entails a lot of monotonous, manual exploration. It’s the least enjoyable part of the job, but for data scientists who only employ traditional analytics methods, it also consumes the vast majority of the data scientist’s day. But it doesn’t have to be that way.

The machine learning algorithms that undergird augmented analytics automate much of that irksome model selection and management. By farming out that work to a machine learning system, data scientists are free to turn their attention to more interesting tasks like building models that offer the most telling glimpses into an organization’s soul. And because augmented analytics is powered by AI, data scientists can test a dizzying array of models. What’s not to like about a system that allows data scientists to do more of what they love?

Validation and communication will become an increasingly important part to the data scientist’s day. Augmented analytics will bring the actual data scientist together often with the citizen data scientist in order to discuss and test the AI-delivered insights. With the right communications platform, the data scientist can share thoughts that illuminate the process by which the AI reaches conclusions. All of that will help organizations make more informed decisions about existing products and future plans.

So fear not, data scientists. Your jobs are safe. And you’ll have the AI to thank when you finally take that vacation you’ve been promising yourself for years.

To see augmented analytics in action, sign up for a free demo of Kubit’s smart analytics service. We’re revolutionizing the field and unchaining data scientists from their desks.

This is part 4 in a series of 4 posts about Augmented Analytics:

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