A Data warehouse is a subject oriented, integrated ,time variant, non volatile collection of data in support of management’s decision making process.
What are the types of data warehouses?
There are three types of data warehouses:
- Enterprise Data Warehouse
- ODS (operational data store)
- Data Mart
A data mart is a subset of data warehouse that is designed for a particular line of business, such as sales, marketing, or finance. In a dependent data mart, data can be derived from an enterprise wide data warehouse. In an independent data mart can be collected directly from sources.
What is star schema?
A star schema is the simplest form of data warehouse schema that consists of one or more dimensional and fact tables.
What is snow flake schema?
A Snowflake schema is nothing but one Fact table which is connected to a number of dimension tables, The snowflake and star schema are methods of storing data which are multidimensional in nature.
What are ETL Tools?
ETL Tools are stands for Extraction, Transformation, and Loading the data into the data warehouse for decision making. ETL refers to the methods involved in accessing and manipulating source data and loading it into target database.
What are Dimensional table?
Dimension tables contain attributes that describe fact records in the fact table.
What is Data Modelling?
Data Modeling is representing the real world set of data structures or entities and their relationship in their of data models, required for a database. Data Modelling consists of various types like :
- Conceptual data modeling
- Logical data modeling
- Physical data modeling
- Enterprise data modeling
- Relation data modeling
- Dimensional data modeling.
Surrogate key is a substitution for the natural primary key. It is just a unique identifier or number of each row that can be used for the primary key to the table.
What is Data Mining?
A Data Mining is the process of analyzing data from different perpectives and summarizing it into useful information.
What is Operational Data Store?
A ODS is an operational data store which comes as a second layer in a datawarehouse architecture. It has got the characteristics of both OLTP and DSS systems.
What is the Difference between OLTP and OLAP?
OLTP is nothing but OnLine Transaction Processing which contains a normalised tables.
But OLAP(Online Analtical Programming) contains the history of OLTP data which is non-volatile acts as a Decisions Support System.
How many types of dimensions are available in Informatica?
There are three types of dimensions available are :
- Junk dimension
- Degenerative Dimension
- Conformed Dimension
ER Modeling is used for normalizing the OLTP database design. Dimesional Modeling is used for de-normalizing the ROLAP / MOLAP design.
What is the maplet?
Maplet is a set of transformations that you build in the maplet designer and you can use in multiple mapings.
What is Session and Batches?
A session is a set of commands that describes the server to move data to the target. A Batch is set of tasks that may include one or more numbar of tasks (sessions, ewent wait, email, command, etc).
What are slowly changing dimensions?
Dimensions that change overtime are called Slowly Changing Dimensions(SCD).
- Slowly Changing Dimension-Type1 : Which has only current records.
- Slowly Changing Dimension-Type2 : Which has current records + historical records.
- Slowly Changing Dimension-Type3 : Which has current records + one previous records.
There are two modes of data movement are:
- Normal Mode in which for every record a separate DML stmt will be prepared and executed.
- Bulk Mode in which for multiple records DML stmt will be preapred and executed thus improves performance.
An Active Transformation can change the number of rows that pass through it from source to target i.e it eliminates rows that do not meet the condition in transformation.
A Passive Transformation does not change the number of rows that pass through it i.e it passes all rows through the transformation.
What is the difference between connected and unconnected transformation?
Connected transformation is connected to other transformations or directly to target table in the mapping.
An Unconnected Transformation is not connected to other transformations in the mapping. It is called within another transformation, and returns a value to that transformation.
What are Aggregator Transformation?
Aggregator transformation is an Active and Connected transformation. This transformation is useful to perform calculations such as averages and sums (mainly to perform calculations on multiple rows or groups).
What are Expression transformation?
Expression transformation is a Passive and Connected transformation. This can be used to calculate values in a single row before writing to the target.
What are Filter transformation?
Filter transformation is an Active and Connected transformation. This can be used to filter rows in a mapping that do not meet the condition.
What are Joiner transformation?
Joiner Transformation is an Active and Connected transformation. This can be used to join two sources coming from two different locations or from same location.
Why we use lookup transformations?
Lookup Transformations can access data from relational tables that are not sources in mapping.
What are Normalizer transformation?
Normalizer Transformation is an Active and Connected transformation. It is used mainly with COBOL sources where most of the time data is stored in denormalized format. Also, Normalizer transformation can be used to create multiple rows from a single row of data.
What are Rank transformation?
Rank transformation is an Active and Connected transformation. It is used to select the top or bottom rank of data.
What are Router transformation?
Router transformationis an Active and Connected transformation. It is similar to filter transformation. The only difference is, filter transformation drops the data that do not meet the condition whereas router has an option to capture the data that do not meet the condition. It is useful to test multiple conditions.
What are Sorter transformation?
Sorter transformation is a Connected and an Active transformation. It allows to sort data either in ascending or descending order according to a specified field.
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