Modern Data Stack
The cloud-native suite of best-of-breed tools for ingestion, storage, transformation, BI, and reverse ETL.
The modern data stack is the cloud-native suite of best-of-breed tools that has displaced monolithic data platforms since 2018. Typical components: cloud data warehouse (Snowflake/BigQuery/Databricks), ELT ingestion (Fivetran, Airbyte, Stitch), in-warehouse transformation (dbt), orchestration (Airflow, Prefect, Dagster), reverse ETL (Hightouch, Census), BI (Looker, Hex, Mode, Tableau), data observability (Monte Carlo, Bigeye), and data catalog (Atlan, Castor). The modern data stack lets data teams move faster, scale elastically, and avoid vendor lock-in. Empire325 architects modern data stacks aligned to each client's existing tooling and team capability.
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Data Transformation
Data warehousing, attribution modeling, and analytics pipelines that unify marketing, sales, and product telemetry.
Explore Data Transformation →Related terms
Data Warehouse
A centralized repository of structured, integrated data from multiple sources, optimized for analytics.
ETL and ELT
Patterns for moving data from sources to analytical stores: ETL transforms before loading; ELT loads first.
First-Party Data
Customer data a company collects directly from its own properties, apps, and interactions.
Customer Data Platform (CDP)
Software that unifies customer data from multiple sources into persistent, accessible profiles.