Environments with embedded learning analytics offer transformative possibilities for education. It can provide personalized learning paths in which analytics can identify individual strengths and gaps, to enable tailored instruction and adaptive content delivery. It can also be used early intervention which helps detect patterns of disengagement or low performance that educators can assist before the learner fall behind. Teachers can also gain insights into the kind of activities that can be most effective to conduct adjustment in the teaching process. Despite its promise, embedding learning analytics into learning environments can be a potential risk to data privacy and ethical concerns. Algorithms may unintentionally reinforce biases or overlook contextual factors affecting performance. It also requires resources that may limit learners and teachers. Educator's readiness is also another factor that may hinder success of learning. Students may also be too reliant on analytics and it can reduce their autonomy or give additional pressure. An example of this is Canvas which is a learning management system which offers powerful embedded learning analytics that help educators monitor student engagement, predict performance, and personalize instruction. It has multi-layered analytics which tracks students' participation. The learning Mastery Gradebook also aligns student performance with learning outcomes, helps teachers assess mastery of standards. However, teachers need training to interpret analytics meaningfully and avoid over-reliance on surface-level metrics.