51.What are different types of parsing?
Quick parsing Thorough parsing
52.What are Lookup and Fact Tables?
A lookup (Dimension) table contains information about the entities. In general the
Dimension and details objects are derived from lookup tables. A fact table contains the statistical information about transactions.
53.What is Designer?
Designer is the Business objects product that is intended to develop the universes. These universe is the semantic - layer of the database structure that isolates from technical issues.
54.What is Surrogate Key?
Surrogate keys are keys that are maintained within the data warehouse instead of keys taken from source data systems.
55.What are the pitfalls of DWH?
Limited value of data (Historical data not current data) DW solutions complicate business processes
DW solutions may have too long a learning curve Costs of cleaning, capturing and delivering data
56.How do you handle large datasets?
By Using Bulk utility mode at the session level and if possible by disabling constraints after consulting with
DBA; Using Bulk utility mode would mean that no writing is taking place in Roll Back Segment so loading is faster. However the pitfall is that recovery is not possible.
57.What are the limitations of handling long datatypes?
When the length of a datatype (e.g varchar2(4000)) goes beyond 4000, Informatica makes this as varchar2(2000).
58.What are the types of OLAP?
ROLAP (Relational OLAP) - Users see their data organized in cubes and dimensions but the data is really stored in RDBMS. The performance is slow. A storage mode that uses tables in a relational
database to store multidimensional structures.
MOLAP (Multidimensional OLAP) - Users see their data organized in cubes and dimensions but the data is really stored in MDBMS. Query performance is fast. HOLAP (Hybrid OLAP) - It is a combination
of ROLAP and HOLAP. EG: HOLOs. In this one will find data queries on aggregated data as well as detailed data.
59.What is the difference between data mart and data warehouse?
Data mart used on a business division/department level where as data warehouse is
used on enterprise level.
60.What is Meta data?
Data about the data, contains the location and description of data warehouse system components such as name, definitions and end user views.
Quick parsing Thorough parsing
52.What are Lookup and Fact Tables?
A lookup (Dimension) table contains information about the entities. In general the
Dimension and details objects are derived from lookup tables. A fact table contains the statistical information about transactions.
53.What is Designer?
Designer is the Business objects product that is intended to develop the universes. These universe is the semantic - layer of the database structure that isolates from technical issues.
54.What is Surrogate Key?
Surrogate keys are keys that are maintained within the data warehouse instead of keys taken from source data systems.
55.What are the pitfalls of DWH?
Limited value of data (Historical data not current data) DW solutions complicate business processes
DW solutions may have too long a learning curve Costs of cleaning, capturing and delivering data
56.How do you handle large datasets?
By Using Bulk utility mode at the session level and if possible by disabling constraints after consulting with
DBA; Using Bulk utility mode would mean that no writing is taking place in Roll Back Segment so loading is faster. However the pitfall is that recovery is not possible.
57.What are the limitations of handling long datatypes?
When the length of a datatype (e.g varchar2(4000)) goes beyond 4000, Informatica makes this as varchar2(2000).
58.What are the types of OLAP?
ROLAP (Relational OLAP) - Users see their data organized in cubes and dimensions but the data is really stored in RDBMS. The performance is slow. A storage mode that uses tables in a relational
database to store multidimensional structures.
MOLAP (Multidimensional OLAP) - Users see their data organized in cubes and dimensions but the data is really stored in MDBMS. Query performance is fast. HOLAP (Hybrid OLAP) - It is a combination
of ROLAP and HOLAP. EG: HOLOs. In this one will find data queries on aggregated data as well as detailed data.
59.What is the difference between data mart and data warehouse?
Data mart used on a business division/department level where as data warehouse is
used on enterprise level.
60.What is Meta data?
Data about the data, contains the location and description of data warehouse system components such as name, definitions and end user views.
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