SAP BW enables Online Analytical Processing (OLAP) for the staging of information from large amounts of operative and historical data. OLAP technology permits multi-dimensional analyses according to various business perspectives.
At the core of any OLAP system is the concept of an OLAP cube (also called a 'multidimensional cube' or a hypercube). It consists of numeric facts called measures which are categorized by dimesnions .The cube metadata is typically created from a star schema or snowflake schema of tables in a relational database.
The OLAP Area can be divided into three components :
1. BEx Analyzer
2. BEx Web Application
3. BEx Mobile Intelligence
Online transaction processing, or OLTP, refers to a class of systems that facilitate and manage transaction-oriented applications, typically for data entry and retrieval transaction processing . OLTP has also been used to refer to processing in which the system responds immediately to user requests .The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).
In general we can say that OLTP provides source data to data warehouses and the OLAP is used to analyze it .So OLTP is also referred as Operative Environment and OLAP as Informative Environment.
| OLTP System
|| OLAP System
|Source of data||Operational data; OLTPs are the original source of the data.|| Consolidation data; OLAP data comes from the
various OLTP Databases
| Purpose of data
||To control and run fundamental business tasks|| To help with planning, problem solving, and
|Processing Speed|| Typicall Very Fast
|| Depends on the amount of data involved; batch
data refreshes and complex queries may take
many hours; query speed can be improved by
|Database Design||Highly normalized with many tables|| Typically de-normalized with fewer tables; use of
star and/or snowflake schemas.
|Backup and Recovery|| Backup religiously; operational data is critical to run the business,
data loss is likely to entail
significant monetary loss and legal liability
| Instead of regular backups, some environments
may consider simply reloading the OLTP data as a
| Age Of Data
|Queries|| Relatively standardized and simple queries
Returning relatively few records
| Often complex queries involving aggregations
| Data Base Operations
|| Add , Modify , Delete , Update and Read
|What the data Reveals||A snapshot of ongoing business processes|| Multi-dimensional views of various kinds of
| Data Set
|| 6 - 18 months
|| 2 - 7 years