Degree of Intelligence
How many, how often, where?Ad hoc reports
Standard reports What happened?
Where exactly is the problem?
What actions are needed?
Why is this happening?
What’s the best that can happen?
What if these trends continue?
What will happen next?
DATA INFORMATION KNOWLEDGE INTELLIGENCE
BasicArchitecture of OBIEE
System components are still C/C++ executable and are
controlled by OPMN and managed by Fusion
Java Components are J2EE applications and are usually
installed in the managed server and controlled by
Fusion Middleware Control.
SYSTEM AND JAVA COMPONENTS
• Its adopted to start, stop and monitor processes across
system components (BI Server, BI Presentation Server,
BI Scheduler and BI Cluster Controller).
• You can either access OPMN through the command
line (opmnctl), or Oracle’s recommended approach is
to use a graphical interface within Fusion Middleware
• OPMN is also used in the 11g stack to control Essbase,
Discoverer and other BI components, so it’s a tool that’s
Oracle Process Manger and
Manage System Components (BI Server, BI
Presentation Server etc)
Start, Stop and Restart all System Components and
Configure Preferences and Defaults
Scale out System Components
Performance Monitoring and Diagnostics
Oracle Enterprise Manager Fusion
Users queries via the
The Oracle BI Server
converts these queries to
physical SQL/MDX, via the
Oracle BI Repository
Queries are passed to the
databases and OLAP cubes
Data returned to users in
the form of dashboards
Web Server: Oracle Analytics’ Web Server caches
queries and query results. When a user submits a
query, the web server examines the logical SQL to see
if it matches an existing cached query. If it does, then
the Web Server uses the results without re-submitting
logical SQL to the Oracle BI Server.
The Oracle BI Server also allows queries that require
extensive database processing to be pre-scheduled to
run so that results are already available when users
open their dashboards.
OBIEE Security: Repositories and
RPD File Security
It contains all the metadata, security rules, database
connection information and SQL used by an OBIEE
The RPD file is password protected and the whole file
Only the Oracle BI Administration tool can create or
open RPD files and BI Administration tool runs only
Data level security: This controls the type and amount of
data that you can see in a report.
Object level security: This provides security for objects
stored in the Web Catalog, such as dashboards, dashboard
pages, folders, and reports. (Web object security) or
User level Security
User-level security refers to authentication and
confirmation of the identity of a user based on the
The physical layer:
Represents the physical structure of the data sources to
which the Oracle BI Server submits queries.
Represents the actual tables and columns of a
• It also contains the connection definition to that
database, or data source.
• join definitions including primary and foreign keys.
Business Model mapping:
This is where business logic is added in to the mix in
the form of formulas.
The business model simplifies the physical schema
and maps the users’ business vocabulary to physical
Your aggregation rules are defined here as well.
Approaches to OLAP Servers
Three possibilities for OLAP servers
(1) Relational OLAP (ROLAP)
(2) Multidimensional OLAP (MOLAP)
(3) Hybrid OLAP (HOLAP)
ROLAP: Dimensional Modeling Using
Relational and specialized relational DBMS to store and
manage warehouse data/OLAP supported on top of a
Special schema design: star, snowflake
Special indexes: bitmap, multi-table join
Proven technology (relational model, DBMS), tend to
outperform specialized MDDB especially on large data sets
IBM DB2, Oracle, Sybase IQ, RedBrick, Informix
Points to be noticed about ROLAP
Defines complex, multi-dimensional data with simple
Reduces the number of joins a query has to process
Allows the data warehouse to evolve with rel. low
Can contain both detailed and summarized data.
ROLAP is based on familiar, proven, and already
SQL for multi-dimensional manipulation of
MOLAP: Dimensional Modeling Using the
Multi Dimensional Model
MDDB: a special-purpose data model
Specialized data structures
• Multicubes vs Hypercubes
Array-based storage structures
Direct access to array data structures
Sometimes on top of relational DB
Pilot, Arbor Essbase, Gentia
Points to be noticed about MOLAP
Pre-calculating or pre-consolidating transactional data improves
Fully pre-consolidating incoming data, MDDs require an enormous
amount of overhead both in processing time and in storage. An input
file of 200MB can easily expand to 5GB
MDDs are great candidates for the <50GB department data marts.
Rolling up and Drilling down through aggregate data.
With MDDs, application design is essentially the definition of
dimensions and calculation rules, while the RDBMS requires that the
database schema be a star or snowflake.
Hybrid OLAP (HOLAP)
HOLAP = Hybrid OLAP:
Best of both worlds
Storing detailed data in RDBMS to optimize time of
Storing aggregated data in MDBMS for fast query
User access via MOLAP tools
In this mode HOLAP
stores aggregations in MOLAP for fast query
performance, and detailed data in ROLAP to optimize
time of cube processing.
• Horizontal partitioning
In this mode HOLAP stores
some slice of data, usually the more recent one (i.e.
sliced by Time dimension) in MOLAP for fast query
performance, and older data in ROLAP.
l access Multidimensiona
data Meta data
Data Flow in HOLAP
When deciding which technology to go for,
How fast will the system appear to the end-user?
MDD server vendors believe this is a key point in their favor.
2) Data volume and scalability:
While MDD servers can handle up to 50GB of storage, RDBMS
servers can handle hundreds of gigabytes and terabytes.
Information Sources Data Warehouse