Data warehouse Concepts - Day 2 i

What is datawarehouse?A data warehouse is built on relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources. It separates analysis workload from transaction workload and enables an organization...

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Data warehouse Concepts - Day 2

dimension table:A dimensional table is a collection of hierarchies and categories along which the user can drill down and drill up. it contains only the textual attributes. LookUp tableA LookUp table is the one which is used when updating a warehouse. When the lookup is placed on the target table (fact table / warehouse) based upon the primary key of the target, it just updates the table by allowing only new records or updated...

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Data warehouse Concepts - Day 1

Data warehouse :A Data warehouse is a repository of integrated information, available for queries and analysis. Data and information are extracted from heterogeneous sources as they are generated. This makes it much easier and more efficient to run queries over data that originally came from different sources". Another definition for data warehouse is: " A data warehouse is a logical collection of information gathered from many...

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Repository tables

In BusinessObjects 6.5 Repository have 57 tables.Security Domain tables 251. OBJ_M_ACTOR2. OBJ_M_USRATTR3. OBJ_M_DOCCST4. OBJ_M_GENPAR5. OBJ_M_MAGICID6. OBJ_M_RESLINK7. OBJ_M_UNIVCST8. OBJ_M_UNIVSLC9. OBJ_M_ACTORDOC10. OBJ_M_DOCUMENTS11. OBJ_M_UNIVERSES12. OBJ_M_ACTORLINK13. OBJ_M_TIMESTAMP14.OBJ_M_UNIVDBCST15.OBJ_M_CONNECTION16.DS_USER_LIST17.OBJ_M_REPOSITORY18.OBJ_M_CATEG19.OBJ_M_CONNECTDATA20.OBJ_M_OBJSLICE21.OBJ_M_RESERVATION22.DS_PENDING_JOB23.OBJ_M_DOCCATEG24.OBJ_M_DOCAT25.OBJ_M_DOCATVARDocument...

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What is a Chasm Trap

What is a Chasm Trap Simply put: A chasm occurs when a series of joins crosses a many >- one -<> A >- B -<> If I were to write a query that spanned all three of those tables the data from table A and C would be duplicated and measure values would be inflated. The inflation factor can be determined by counting the number of rows from the left that match a particular key and multiplying by the number of rows on...

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