61.How does the recovery mode work in informatica?
In case of load failure an entry is made in OPB_SERV_ENTRY(?) table from where the extent of loading can be determined.
62.What is Aggregate Awareness?
Aggregate awareness is a feature of DESIGNER that makes use of aggregate tables in a database. These are tables that contain pre-calculated data. The purpose of these tables is to enhance the performance of SQL transactions; they are thus used to speed up the execution of queries.
63.What is a difference between OLTP and OLAP?
OLTP
It focus on day to day transaction. Data Stability
Dynamic
Highly normalized. Access Frequency High.
OLAP
It focus on future predictions and decisions Static until refreshed
Demoralized and replicated data Medium to low.
64.When should you use a star schema and when a snowflake schema?
A star schema is a simplest data warehouse schema. Snowflake schema is similar to the star schema. It normalizes dimension table to save data storage space. It can be used to represent hierarchies of information.
65.What parameters can be tweaked to get better performance from a session?
DTM shared memory, Index cache memory, Data cache memory, by indexing, using persistent cache, increasing commit interval etc.
66.What are the benefits of DWH?
Immediate information delivery
Data Integration from across, even outside the organization
Future vision of historical trends Tools for looking at data in new ways Enhanced customer service.
67.Is It Possible to invoke Informatica batch or session outside Informatica UI?
PMCMD.
68.Why we are going for surrogate keys?
Data tables in various source systems may use different keys for the same entity. Keys may change or be reused in the source data systems.
Changes in organizational structures may move keys in the hierarchy.
69.When is more convenient to join in the database or in Informatica?
Definitely at the database level
at the source Qualifier query itself rather than using Joiner transformation
70.How do you measure session performance?
By checking Collect performance Data check box.
71.What is Dimension Table?
It contains data used to reference data stored in the fact table.
Fewer rows
Primarily character data
One primary key (dimensional key) Updatable data
72.What is a database connection?
A connection is a set of parameters that provides access to an RDBMS. These parameters include system information such as the data account, user identification, and the path to the database.
Designer provides three types of connections: secured, shared, and personal.
73.What are all the types of dimensions?
Informational Dimension Structural Dimension Categorical Dimension Partitioning Dimension.
74. What is the difference between data mining and data warehousing?
Data mining, the operational data is analyzed using statistical techniques and clustering techniques to find the hidden patterns and trends. So, the data mines do some kind of summarization of the data and can be used by data warehouses for faster analytical processing for business intelligence.
Data warehouse may make use of a data mine for analytical processing of the data in a faster way.
75. What is difference between view and materialized view?
Views contains query whenever execute views it has read from base table.
A view which is physically stored in a database. Materialized views allow query performance to be enhanced by precalculating costly operations.
In case of load failure an entry is made in OPB_SERV_ENTRY(?) table from where the extent of loading can be determined.
62.What is Aggregate Awareness?
Aggregate awareness is a feature of DESIGNER that makes use of aggregate tables in a database. These are tables that contain pre-calculated data. The purpose of these tables is to enhance the performance of SQL transactions; they are thus used to speed up the execution of queries.
63.What is a difference between OLTP and OLAP?
OLTP
It focus on day to day transaction. Data Stability
Dynamic
Highly normalized. Access Frequency High.
OLAP
It focus on future predictions and decisions Static until refreshed
Demoralized and replicated data Medium to low.
64.When should you use a star schema and when a snowflake schema?
A star schema is a simplest data warehouse schema. Snowflake schema is similar to the star schema. It normalizes dimension table to save data storage space. It can be used to represent hierarchies of information.
65.What parameters can be tweaked to get better performance from a session?
DTM shared memory, Index cache memory, Data cache memory, by indexing, using persistent cache, increasing commit interval etc.
66.What are the benefits of DWH?
Immediate information delivery
Data Integration from across, even outside the organization
Future vision of historical trends Tools for looking at data in new ways Enhanced customer service.
67.Is It Possible to invoke Informatica batch or session outside Informatica UI?
PMCMD.
68.Why we are going for surrogate keys?
Data tables in various source systems may use different keys for the same entity. Keys may change or be reused in the source data systems.
Changes in organizational structures may move keys in the hierarchy.
69.When is more convenient to join in the database or in Informatica?
Definitely at the database level
at the source Qualifier query itself rather than using Joiner transformation
70.How do you measure session performance?
By checking Collect performance Data check box.
71.What is Dimension Table?
It contains data used to reference data stored in the fact table.
Fewer rows
Primarily character data
One primary key (dimensional key) Updatable data
72.What is a database connection?
A connection is a set of parameters that provides access to an RDBMS. These parameters include system information such as the data account, user identification, and the path to the database.
Designer provides three types of connections: secured, shared, and personal.
73.What are all the types of dimensions?
Informational Dimension Structural Dimension Categorical Dimension Partitioning Dimension.
74. What is the difference between data mining and data warehousing?
Data mining, the operational data is analyzed using statistical techniques and clustering techniques to find the hidden patterns and trends. So, the data mines do some kind of summarization of the data and can be used by data warehouses for faster analytical processing for business intelligence.
Data warehouse may make use of a data mine for analytical processing of the data in a faster way.
75. What is difference between view and materialized view?
Views contains query whenever execute views it has read from base table.
A view which is physically stored in a database. Materialized views allow query performance to be enhanced by precalculating costly operations.
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