INFS 247 Lecture Notes - Lecture 6: Data Warehouse, Time Horizon, Data Mart
19 Jun 2018
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INFS Lecture 6
Data warehouse
Operational Vs. Analytical Data
oOperational information (Transactional information) – the information collected and
used in support of day to day operational needs in businesses and other organizations
oOperational database – collects and presents operational information in support of daily
operational procedures and processes
oAnalytical information – the information collected and used in support of analytical
tasks
oAnalytical database (i.e. data warehouse) - collects and presents analytical information
in support of analytical tasks
Data warehouse
oReasons for the creation of a data warehouse as a separate analytical database
Time horizon difference – the difference between how long the data is useful
for transactional vs. analytical needs
Performance reasons – the performance of operational day-to-day tasks
involving data use can be severely diminished if such tasks have to compete for
computing resources with analytical tasks
Difference in structuring of data – It is often impossible to structure a database
which can be used in an efficient manner for both operational and analytical
purposes
oCan be modeled and structured differently than operational databases
oDifferent technologies for storage and retrieval
oData warehouses used by different users (smaller)
Data warehouse components
oDWC
Source systems (operational databases) – operational databases that provide
analytically useful information for the data warehouse’s subjects of analysis
Extraction-transformation-load (ETL) infrastructure – Facilitates the retrieval of
data from operational databases into the data warehouses
Data warehouse
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Data warehouse: reasons for the creation of a data warehouse as a separate analytical database. Time horizon difference the difference between how long the data is useful for transactional vs. analytical needs. Performance reasons the performance of operational day-to-day tasks involving data use can be severely diminished if such tasks have to compete for computing resources with analytical tasks. Source systems (operational databases) operational databases that provide analytically useful information for the data warehouse"s subjects of analysis. Extraction-transformation-load (etl) infrastructure facilitates the retrieval of data from operational databases into the data warehouses. Front-end (bi) applications - provide access to the data warehouse for users who are engaging in indirect use. Data store based on the same principles as a data warehouse, but with a more limited scope: independent dm. Stand alone data mart, created in the same fashion as the data warehouse. Has own source systems and etl infrastructure: dependent dm.
