dateilog

Dateilog is a concept used to describe a date-oriented event log that records occurrences with timestamps and associated metadata to support auditing, provenance, and time-based analysis. It is applicable in data management, analytics, and software systems where precise ordering and traceability of events are important.

Data model: each record (event) typically includes an identifier, a date component, a precise timestamp, an event_type, and a payload or attributes field. Some designs separate date and timestamp to enable efficient partitioning on date while preserving time-of-day resolution. Metadata may include source, user, and version information.

Formats and storage: dateilog can be stored as newline-delimited JSON (JSONL), CSV, or columnar formats like Parquet. It is often organized as an append-only log with partitioning by date and indexing on timestamp to support fast lookups and historical queries.

Use cases: dateilog supports data provenance and audit trails in financial, healthcare, or supply-chain systems; ETL and data warehousing pipelines; event sourcing in software architectures; reproducible experiments and regulatory compliance.

Implementation considerations: design choices around immutability and retention policies; schema evolution; handling time zones and daylight saving changes; scalability and partition pruning; and integration with streaming platforms like Kafka or data lake architectures.

History and relation: dateilog as a general approach arose from the broader need to track events over time and to enable reliable lineage and auditing. It overlaps with concepts such as time-series databases, event logs, and audit logs.