Since 2016, the Advanced Distributed Learning (ADL) Initiative has been developing the Total Learning Architecture (TLA), a 4-pillar data strategy for managing lifelong learning. Each pillar describes a type of learning-related data that needs to be captured, managed, and shared across an organization. Each data pillar is built on a set of international data standards that combine to increase the granularity and fidelity of learner data. Reusable Competency Definitions (IEEE 1484.20.1 RCD) are used to describe the Knowledge, Skills, Abilities, and Other behaviors (KSAOs) that are required in the workplace (e.g., the operational environment). Learning Activity Metadata (IEEE P2881 Learning Activity Metadata) is used to describe the various learning resources an organization uses to train and educate its people. The Experience API (IEEE 9274.1 xAPI) is used to track and manage learner performance both inside and outside a learning activity. An Enterprise Learner Record, currently an IEEE study group, is used to track and manage each learner's level of competency within the organization. Together, this data enables a ledger of learner performance that ties all learning activities that a learner completes to competencies, credentials, and ultimately to the different career trajectories that a learner may pursue. The TLA data strategy includes linkages across the different standards listed above and collectively provide a data foundation for adaptive systems to build upon. This paper and discussion will walk viewers through the different data models that are being used to drive development of these standards.