| business
intelligence
features |
| Change
Data Capture: |
|
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|
 |
New feature that
allows incremental changes from target data sources to be captured and applied to the data
warehouse automatically. |
|
| Multi-Table
Inserts: |
|
|
|
| Provides enormous performance
benefits for large data loads by providing the ability to insert into more than one table with a
single SQL statement. |
|
| SQL
"merge" Command: |
|
|
|
| Can dynamically decide whether
to insert data or update current data during a load, depending on whether a corresponding row already
exists in a table. |
|
| SQL "with"
Clause: |
|
|
| Optimises query
speed by eliminating redundant processing in complex queries. Enables a SELECT statement
to define the subquery block at the start of the query, process the block just once, label
the results, and then refer to the results multiple times. |
|
| New
Analytical SQL functions: |
|
|
|
| 9i provides a
number of new SQL functions to serve the Business Intelligence user including complex
percentile calculations, ranks & distributions, new statistics and first/last aggregates. |
|
| List
partitioning: |
|
|
|
| A new partitioning method
that allows you to specify discrete values on which to partition your table. Allows unordered
and unrelated sets of data to be grouped and organised together according to data models. |
|
| Range
& Hash partitioning: |
|
|
|
| Can now partition
on all Oracle data types and table types such as IOT's. |
|
| Improved
Global Index maintenance: |
|
|
|
| The
new partition statement clause "update global indexes" causes
Oracle to automatically maintain global indexes when table
partitions are added/altered or dropped, giving
improved efficiency and availability. Previously, global indexes
had to be manually rebuilt when partitions were modified. |
|
|
|
|
| Table
Functions: |
|
|
|
|
Eliminate the
need to stage data into physical objects during complex data transformation and load
sequences. Using Oracle object types and object tables in PL/SQL, data can be dynamically
passed through functions in sequence (known as "pipelining") and only the end result is
inserted into a physical object. This additionally enables parallelism of the process
because each stage of the process can run concurrently rather than one stage waiting
for the other to finish. Powerful stuff! |
|
|
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|
 |
| External
Tables: |
|
|
|
|
|
| Define external files
as tables in the data dictionary and be able to query them as you would ordinary Oracle tables.
This provides for very fast data loads as you can load data from an external file using an
"insert into … select from" statement instead of using SQL*Loader. Also enables easy
parallelism of data loads without having to split up the file to be loaded. |
|
| Bitmap
Join Indexes: |
|
|
|
| Provide for further performance improvements
on join indexes (indexes that can span more than one table), especially in star schemas
with fact and dimension tables. In addition, bitmap join indexes can eliminate some of
the key iteration and bitmap merge work which is often present in star queries with
bitmap indexes on the fact table. |
|
| Enhanced
Query Rewrite Features: |
|
|
|
| Query
rewrite can still be used (with materialized views) when
the result set only contains some of the data
(e.g. because the BETWEEN clause is being used). |
|
| Data
Block Pre-fetching: |
|
|
|
| This
entirely transparent feature delays data block reads until
multiple rows specified by the
underlying index are ready to be accessed and then retrieves
multiple data blocks at once, rather than reading a single
data block at a time. This provides enormous performance
gains for queries that are using indexes whose blocks are poorly
clustered as it makes best use of system I/O capacity. |
|
| Data
Mining: |
|
|
|
| Incorporates
Oracle data mining technology into the database so data,
data preparation, model building, and
model scoring activities all remain in the database and applications
can be built on top. Includes important data mining algorithms.
This is an optional extra. |
|
|
|
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| OLAP
Server: |
|
|
|
| Scalable,
high performance OLAP calculation engine. |
|
| Summary
Advisor Wizard: |
|
|
|
| A
new feature of the Enterprise Manager that provides an interactive
environment in which to build and
optimise materialized views. Helps you proactively optimise
your aggregated data based on information gathered from workloads
against the data or based on a hypothetical
workload. Makes the most cost-effective trade-offs when recommending
the creation of new materialized views and evaluating the
performance of existing materialized views. |
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