Emerging trend expands data science capabilities to more people using AI

This is a guest blogpost by Andrew Beers, CTO, Tableau.
Ideally, every business decision today would be based on a thorough understanding of all relevant data available. But there’s simply too much data for many organisations to handle and not enough people who understand how to harness all this data to drive transformation. This dilemma has sparked new trends — one of which centres on data science and it’s becoming imperative to business transformation.
Data science is a critical part of the analytics process, and data science teams are great at producing precise models, which are often then used to drive automated processes that accelerate transformation. But this precision comes at the expense of a more complex, time-consuming design process. And oftentimes data science teams are maxed out. Plus, they don’t always have the right context and domain expertise that your other expert business analysts do.
That’s all starting to change for the better. Technologies like AI and Machine Learning are expanding data science capabilities to more people so they can make better decisions faster — regardless of their technical expertise. It gives people with the right domain expertise and business context the ability to build predictive models, plan simulations and scenarios, and cluster data.
This means more people across the business are better equipped to tackle tough questions like resource allocation, prioritisation, staffing, and logistics. For example, taking a data-led approach to marketing and sales with opportunity scoring, predicting time to close, and many other CRM-related use cases that most data science teams can’t prioritise are highly valuable.
Or a sales team might use predictive modelling to determine the most profitable upsell opportunities. An algorithm can offer predictions about the likelihood that a customer will buy, though it doesn’t have the critical knowledge of an account executive managing the business relationship. But if the account executive can tap data science capabilities using AI, then they can explore various possibilities and see which scenarios will best help their customers achieve their goals.
This also frees up time for data science teams and allows them to tackle the really big, mission-critical problems. Traditional data science processes might be overkill for most business questions since deploying and integrating traditional custom models is complex, requiring statisticians and data scientists to make solutions consumable and actionable by end-users. This new trend empowers people to create and iterate on predictive models which can enhance their ability to think fast and act with confidence.
But perhaps the real magic behind this emerging trend is how it proves that AI can enhance people’s unique perspective and experience to drive better decisions faster. Simply put, AI can help people do more with data. And over this past year, we’ve even seen organisations across every industry use data to make powerful transformations happen. So don’t be fooled by claims that AI will replace people. Time and time again, we’ve seen the brilliant work that comes when people tap AI to enhance their ability to use data to make better decisions.
Decisions that can transform an organisation, if not the entire world.