Basics of Transaction Management
9 important questions on Basics of Transaction Management
What are the decision making levels? And its systems?
- day to day business decisions
- short time frame
- OLTP: online transaction processing
Tactical level
- middle management decisions
- medium term focus
Strategic level
- senior management
- long term focus
Operational systems
- operational level
- focus on simple insert, update, delete, select statements
- transaction throughput
Decision support systems
- tactical + strategic level
- focus on data retrieval by answering complex ad hoc queries
- represent data in a multidimensional way
- trend analysis
Difference transactional system and data warehouse?
Latency: real time - periodic snapshots
Design: application oriented - subject oriented
Normalization: normalized - denormalized
Manipulation: Insert/Update/Delete/Select - Insert/Select
Transaction management: Important - Less of concern
Type of queries: many simple - fewer but complex
What are the different data warehouse schemas?
- fact table: one tuple per transaction or event and also measurement data
- dimension table: further info about each of the facts. Criteria for aggregating the data. Often denormalized
Snowflake schema
- in case dimension tables grow too large
- in case most queries dont make use of the outer level dimension tables
Fact constellation
- more fact tables and innser dimension tables that link to both.
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What are the specific schema issues?
Granularity of the fact table
Factless fact tables
Optimizing the dimensions tables
Defining junk dimensions
Defining outrigger tables
Slowly changing dimensions
Rapidly changing dimensions
What are surrogate keys?
What are junk dimensions?
What are outrigger tables?
What are slowly and rapidly changing dimensions?
- dimensions that change slowly and irregularly over a period of time. Check 4 approaches on slides
Rapidly
- change rapidly and regularly over period of time. Some approaches result into a lot of rows. Split customer information into stable and rapidly changing information which is put in mini-dimension table
What is the ETL process?
- can consume upto 80% of all efforts needed to set up a data warehouse
- dump the data in a so-called staging area where the ETL activities can be executed
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