What is the focus of adaptive models in Pega Analytics?

The focus of adaptive models in Pega Analytics is indeed on adjusting to new data. Adaptive models are designed to continuously learn and update themselves based on incoming data, ensuring that the decisions they support become increasingly accurate and relevant over time. This real-time responsiveness is crucial in dynamic environments where user behaviors and market conditions can change rapidly.

By adjusting to new data, adaptive models effectively improve their predictive capabilities, allowing organizations to make informed decisions based on the most current information. This is particularly valuable in scenarios involving customer interactions where timely and relevant decision-making is critical.

The other options, while related to data and analysis, do not capture the essence of what adaptive models aim to achieve. Handling historical data tends to focus on a static perspective, and creating static reports does not involve the dynamic learning process inherent to adaptive models. Utilizing user input, while important, is part of the broader context and not the sole focus of adaptive models, which rely on continuously analyzing and integrating new data instead.