Answer:

• A mapplet is a reusable object that contains a set of transformations. It is used to encapsulate a group of transformations that can be used in multiple mappings.
• A reusable transformation is a transformation that is created within a mapping but can be reused in other mappings.

Answer:

Target load order determines the sequence in which the targets are loaded during a session. It can be set to one of the following:

• Load Order: The targets are loaded in the order in which they appear in the mapping.
• Bulk Load Order: The targets are loaded simultaneously in parallel.
• Concurrent Load Order: The targets are loaded concurrently but not in any particular sequence.

Answer:

SQ stands for Source Qualifier transformation, which is utilized to select records from various sources, including relational tables, flat files, and Informatica PowerExchange services. It functions as an active and connected transformation. When you include the source tables in the mapping, the Source Qualifier is automatically added.

The primary function of the Source Qualifier transformation is to convert the source datatypes into Informatica-compatible datatypes. However, if the source datatype does not match with the Informatica compatible datatype, the mapping will become invalid upon saving.

The primary function of the Source Qualifier transformation is to convert the source datatypes into Informatica-compatible datatypes. However, if the source datatype does not match with the Informatica compatible datatype, the mapping will become invalid upon saving.

Answer:

A Sorter Transformation is a component used in data transformation tasks to sort data based on one or more specified criteria. It is commonly used in ETL tools and platforms to arrange data in a particular order before loading it into a target database or data warehouse. The Sorter Transformation takes input data and orders as per the defined sorting conditions, such as ascending or descending order, and sorts the data based on one or more specified columns. The sorted output is then available for further processing or loading into the target system.

Answer:

The Sequence Generator transformation is an active and connected transformation that produces numerical values. It is utilized for generating unique primary key values, filling in missing primary keys, or cycling through a sequential range of numbers.

Answer:

In Informatica, the Lookup transformation is a powerful tool used to retrieve data from a reference dataset and use it to perform transformations on the main data flow in a mapping.

Answer:

In Informatica, the aggregator transformation is one of the fundamental transformations used in data integration and ETL processes. It is a powerful transformation that performs aggregate calculations on groups of data and produces summary results. The aggregator transformation is commonly used for tasks such as calculating sums, averages, counts, and others on groups of data.

Answer:

In Informatica, a “Joiner Transformation” is a type of transformation used in the data integration process. It is used to combine data from two or more sources based on a common key or condition. The join operation is similar to an SQL join, where rows from different sources are matched based on the specified join condition, and the result is a combined output.

Answer:

Here’s how a Joiner Transformation works:

1. Input Groups: The Joiner Transformation takes two sets of input data: the Master Input and the Detail Input. These input groups are often referred to as “Master” and “Detail” sources.
2. Join Condition: The transformation requires a join condition to specify how the data should be matched between the two input groups. The join condition typically involves a common key column between the Master and Detail sources.
3. Join Types: Informatica supports various join types such as Inner Join, Outer Join (Left Outer Join, Right Outer Join, Full Outer Join), and Custom Join.
   • Inner Join: It returns only the matching rows from both the Master and Detail sources.
   • Outer Join: It returns matching rows as well as any unmatched rows from one or both sources.
   • Custom Join: It allows specifying a custom condition for joining the data.
4. Output: After the join operation, the transformation produces a combined output based on the join condition and join type selected.

Answer:

A surrogate key is a unique identifier assigned to each row or record in a database table. It is a system-generated or artificially created key, and its main purpose is to uniquely identify records in the table. Surrogate keys are typically integers, often auto-incremented by the database management system (DBMS) as new records are inserted.

Answer:

Following tools are available in workflow manager:

• Worklet Designer
• Workflow Designer
• Repository Manager
• Workflow Monitor
• Task Mapping Designer
• Task Designer

Answer:

The term “Update Strategy Transform” refers to a transformation that is used within the Informatica PowerCenter ETL (Extract, Transform, Load) tool. The Update Strategy Transform is primarily used to determine how data should be treated in the target database based on certain conditions specified in the mapping.

Answer:

The main difference lies in their roles and positions within the ETL process:

• Source Qualifier: Used to define and optimize how data is extracted from the source system. It’s often placed at the beginning of the data flow.
• Filter Transformation: Used to conditionally filter rows of data within the data flow. It’s positioned within the data flow after extraction and possibly other transformations.

Both transformations serve distinct purposes in data integration workflows, helping to shape and manipulate data as it moves from source systems to destination systems.

Answer:

The architecture of Informatica follows a service-oriented approach, known as SOA. The core elements within the architecture of the Informatica server include the load manager, data transfer manager, temporary server, reader, writer, and more. The load manager initiates a request to the reader, which proceeds when the reader is prepared to access data from the source. Once accessed, the data is stored in the temporary server. Subsequently, the data transfer manager retrieves data from the temporary server and facilitates its transfer to the intended target destination.

Answer:

Configuring mappings in Informatica involves defining the transformation logic and the flow of data from source to target. Here’s a step-by-step guide on how to configure mapping in Informatica:

• Open Informatica PowerCenter Designer
• Create a New Mapping
• Add Source and Target Definitions
• Create and connect Transformations
• Configure Transformations
• Define Transformation Logic
• Validate and Test
• Parameterization and Variables
• Session Configuration
• Workflow Integration
• Save and Deploythe Mapping
• Execution and Monitoring the Mapping

Answer:

INFORMATICA PowerCenter is a popular data integration platform developed by Informatica Corporation. It is designed to help organizations manage and integrate data from various sources across their enterprise. PowerCenter provides a comprehensive set of tools for data extraction, transformation, and loading (ETL) processes, enabling businesses to move, transform, and consolidate data from different systems into a centralized location, such as a data warehouse or a data lake.

Answer:

Enterprise Data Warehousing refers to the practice of collecting, storing, managing, and analyzing large volumes of data from various sources within an organization to support business intelligence and decision-making processes. It involves creating a centralized repository, known as a data warehouse, that consolidates data from different departments, systems, and databases into a unified and structured format.

Answer:

Push-down optimization refers to a technique used to enhance the performance of queries by pushing down or moving parts of the query processing closer to the data source, typically a database engine. This optimization aims to reduce the amount of data that needs to be transferred and processed, leading to faster query execution times and improved resource utilization.

Answer:

Dynamic Lookup Cache refers to a feature used in data integration and transformation processes within the Informatica PowerCenter ETL tool. A lookup is a common operation in ETL processes where data from one source is matched with data from another source based on certain criteria. This is often done to enrich or validate data during the transformation process.

Answer:

The key difference between variable ports and mapping variables in Informatica lies in their scope and purpose. Variable ports are used within a single transformation instance for temporary calculations, while mapping variables are used across multiple transformations within a mapping to pass values and maintain consistency across the entire mapping.