Abstract: Traditionally,
data warehouses have been used to analyze historical data. Lately, there
has been a growing trend to use data warehouse to support real-time decision
making. Row Effective tables are a key part of making Active Data Warehousing
(ADW) a reality. The key idea of ADW is to make data available at the right
time. Row Effective processing enables this by making all the different time
slices of data available to whoever needs it. Users with different data latency
needs can all be accommodated. Data can be “frozen” via a view on the proper
time slice. Data as of a point in time can be obtained across multiple tables
or multiple subject areas, resolving consistency and synchronization issues.
This paper will discuss implementations such as coexistence of load and Query
against the same table, performance of load and report queries, scope of
resource (CPU and I/O) savings, how to manage views against the row effective
tables to simplify access, and how to handle full refreshes of row effective
tables.