Databases Reference
In-Depth Information
Whenever we can specify the semantics of what we need, without
having to specify the steps required to fulfill our requests, those
requests are satisfied at lower cost, in less time, and more reliably.
SCDs stand on the wrong side of that what vs. how divide.
Some IT professionals refer to a type 1.5 SCD. Others describe
types 0, 4, 5 and 6. Suffice it to say that none of these variations
overcome these two fundamental limitations of SCDs. SCDs
do have their place, of course. They are one tool in the data
manager's toolkit. Our point here is, first of all, that they are
not bi-temporal. In addition, even for accessing uni-temporal
data, SCDs are cumbersome and costly. They can, and should,
be replaced by a declarative way of requesting what data is
needed without having to provide explicit directions to that data.
Real-Time Data Warehouses
As for the third of these developments, it muddles the data
warehousing paradigm by blurring the line between regular,
periodic snapshots of tables or entire databases, and irregular
as-needed before-images of rows about to be changed. There
is value in the regularity of periodic snapshots, just as there is
value in the regular mileposts along interstate highways.
Before-images of individual rows, taken just before they are
updated, violate this regular snapshot paradigm, and while
not destroying, certainly erode the milepost value of regular
snapshots.
On the other hand, periodic snapshots fail to capture changes
that are overwritten by later changes, and also fail to capture
inserts that are cancelled by deletes, and vice versa, when these
actions all take place between one snapshot and the next.
As-needed row-level warehousing (real-time warehousing) will
capture all of these database modifications.
Both kinds of historical data have value when collected and
managed properly. But what we actually have, in all too many
historical data warehouses today, is an ill-understood and thus
poorly managed mish-mash of the two kinds of historical data.
As result, these warehouses provide the best of neither world.
The Future of Databases: Seamless Access
to Temporal Data
Let's say that this brief history has shown a progression in
making temporal data “readily available”. But what does “readily
available” really mean, with respect to temporal data?
