OLAP v/s OLTP
- 2. By: A h s a n I r f a n S h a i k h
- 3. Define Olap (data ware house)? Define Oltp? Comparison between data ware house and OLTP ? “AGENDA”
- 4. A data warehouse is a repository (collection of resources that can be accessed to retrieve information) - OLAP (On-line Analytical Processing) is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations.. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).
- 5. OLTP (On-line Transaction Processing) is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE). These system have detailed day to day transaction data which keeps changing, on everyday basis. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF).
- 7. Both are related to information databases, which provide the means and support for these two types of functioning. Each one of the methods creates a different branch on data management system, with it’s own ideas and processes, but they complement themselves. To analyze and compare them we’ve built this resource!
- 8. Source of data: OLTP: Operational data; OLTPs are the original source of the data. OLAP: Consolidation data; OLAP data comes from the various OLTP Database. Purpose of data: OLTP: To control and run fundamental business tasks OLAP: To help with planning, problem solving, and decision support
- 9. What the data: OLTP: Reveals a snapshot of ongoing business processes. OLAP: Multi-dimensional views of various kinds of business activities. Inserts and Updates: OLTP: Short and fast inserts and updates initiated by end users. OLAP: Periodic long-running batch jobs refresh the data.
- 10. Queries: OLTP: Relatively standardized and simple queries Returning relatively few records. OLAP: Often complex queries involving aggregations Processing Speed: OLTP: Typically very fast. OLAP: Depends on the amount of data involved; batch data refreshes and complex queries may take many hours.
- 11. Space Requirements: OLTP: Can be relatively small if historical data is archived. OLAP: Larger due to the existence of aggregation structures and history data. Database Design : OLTP: Highly normalized with many tables. OLAP: Typically de-normalized with fewer tables.
- 12. OLTP systems is absolutely critical, it needs a complex backup system. Full backups of the data combined with incremental backups are required. OLAP only needs a backup from time to time since it’s data is not critical and doesn’t keep the system running. Backup and Recovery