Smaller practitioners are finding analytics operations frameworks where it is quickly becoming widely accepted that advanced machine learning and data analytics should be a part of any practice helping customers solve business problems through deep learning techniques.
In January this year, for example, new research came out that shows how deep learning is being used to detect the earliest stages of skin cancer, matching human doctor capability. This is an example of just how much investment healthcare is putting into predictive analytics. In the fintech space, there’s a buzz around AI being used to fight fraud and improve cyber security.
But it’s not just these sectors. Although adoption of analytics may be a little slower with Telcos and manufacturers, it won’t be long before machine learning leads their agenda too. As early as 2025 we’ll see the new wave of technology break down the existing data silos, and companies will achieve the results that they expect and need.
Recently, local practitioners have been embracing the combined approach – blending data science with computer skills. This generates value by use case by uniting a company’s capabilities, which has until recently still resided in silos.Recently, local practitioners have been embracing the combined approach – blending data science with computer skills. Click To Tweet
Adaptable practitioners are going to do better, faster, than their rivals on the AI and machine learning wave. Combining skills from a variety of departments will serve the wider company purpose, and it’s exciting to think what the next three years hold for the wider analytics space.
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