2:
Logical
Design
?⤠definition of a plan
for the population
of the Data Staging
Area w.r.t. schemata
mappings
?⤠choice of extraction
policy: incremental
or full extraction
?⤠description of ETL
activities w.r.t.
schemata mappings
and internal
semantics
?⤠identification of an
optimal execution
plan
?⤠appropriate
schemata
mappings
?⤠logical
schema
Table 1. Typical tasks for a data warehouse designer/developer organized by phase
and stage
26 Simitsis, Vassiliadis, Skiadopoulos, & Sellis
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phase, we present the issues and the steps to follow concerning the main tasks of
the warehouse architecture (extraction, transformation, cleaning). The fundamental
deliverable that guides this process is also listed.
Arktos.II:.A.Framework.towards.the.Modeling.and.the...
Optimization of ETL Workflows
In this subsection, we present a framework for traditional data warehouse flows,
named Arktos II, as an exemplary ETL modeling methodology that follows the life
cycle of a data warehouse as we previously presented it. Below, we briefly present
the main contributions of Arktos II, grouped by the phases of the life cycle of
a data warehouse.
Arktos II (Simitsis, Vassiliadis, & Sellis, 2005a; Vassiliadis, Simitsis, Georgantas,
Terrovitis, & Skiadopoulos, 2005) is a framework that studies the design, development,
and optimization of ETL workflows.
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