# Analytics Glossary: Semantic Layer to Schema Drift | Silicon

URL: https://meetsilicon.com/glossary/

> Plain-English definitions of the data and analytics terms that matter: semantic layer, metrics layer, schema drift, data lineage, dashboard reliability and more.

Glossary
# Analytics glossary
Plain definitions of the data terms you'll hear when you build a data foundation.
Dashboard reliability
Dashboard reliability is the confidence that a dashboard loads, shows current data and calculates its numbers correctly every time someone opens it.
Data freshness
Data freshness is how recently the data behind a table, metric or dashboard was updated, compared with how recent it needs to be.
Data lineage
Data lineage is a map of how data flows from its sources, through transformations, to the metrics, dashboards and reports that use it.
Data observability
Data observability is the practice of monitoring data pipelines and tables for freshness, volume, schema and quality issues so problems are found before users notice.
dbt
dbt (data build tool) is an open-source framework for transforming data in a warehouse using version-controlled SQL, with tests, documentation and lineage built in.
Embedded analytics
Embedded analytics means putting dashboards, charts or data exploration directly inside another application, usually so a company's customers can see their own data.
Headless BI
Headless BI is an approach where metric definitions live in a standalone semantic layer that any tool can query, rather than inside one BI tool.
Metrics layer
A metrics layer is the part of a semantic layer that defines business metrics, like revenue or churn rate, once in code so they can be reused consistently.
Row-level security
Row-level security restricts which rows of data a user can see, based on attributes such as their region, team or customer account.
Schema drift
Schema drift is any unplanned change to the structure of data, such as a renamed column, a dropped field or a changed data type, that can break the queries and dashboards built on it.
Semantic layer
A semantic layer is a shared set of business definitions, such as metrics, dimensions and joins, that sits between a data warehouse and the tools that query it.
Text-to-SQL
Text-to-SQL is the use of AI to turn a plain-English question into a SQL query that runs against a database.
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