Top 50 Data Integration Interview Questions and Answers
Updated 19 Nov 2024
Q1. Informatica - How can we handle duplicates in mappings
Duplicates in mappings can be handled using various techniques in Informatica.
Use the Sorter transformation to sort the data and then use the Aggregator transformation to eliminate duplicates.
Use the Expression transformation with the DISTINCT keyword to remove duplicates.
Use the Rank transformation to rank the data and then filter out the duplicates based on the rank.
Use the Lookup transformation to check for duplicates in a reference table and filter them out.
Use the Update...read more
Event handlers in SSIS are workflows that are triggered by specific events during the execution of a package.
Event handlers can be used to perform additional tasks or actions based on the success or failure of specific tasks within a package.
Common events that can trigger event handlers include OnError, OnPreExecute, OnPostExecute, OnWarning, etc.
Event handlers can be configured to send emails, log information, execute scripts, or perform other actions based on the event that...read more
Q3. what is IR, and difference between dataset and linked service
IR stands for Integration Runtime. Dataset is a representation of data, while linked service is a connection to the data source.
IR is a compute infrastructure used to provide data integration capabilities
Dataset is a structured representation of data used in data engineering tasks
Linked service is a connection to a data source, providing access to the data
IR enables data movement and transformation between different data sources
Dataset defines the schema and structure of the ...read more
Q4. How do we do delta load using adf?
Delta load in ADF is achieved by comparing source and target data and only loading the changed data.
Use a Lookup activity to retrieve the latest watermark or timestamp from the target table
Use a Source activity to extract data from the source system based on the watermark or timestamp
Use a Join activity to compare the source and target data and identify the changed records
Use a Sink activity to load only the changed records into the target table
Q5. What is BODS ?
BODS stands for Business Objects Data Services, a data integration tool by SAP for ETL processes.
BODS is used for extracting, transforming, and loading data between different systems.
It can connect to various data sources like databases, applications, and files.
BODS allows for data quality management, data profiling, and metadata management.
It is commonly used for data migration, data warehousing, and data synchronization.
Example: Using BODS to extract customer data from a CR...read more
Q6. How to impomport IDOC.?
IDOC can be imported using SAP PI/PO through IDOC adapter.
Create a sender IDOC adapter in SAP PI/PO
Configure the adapter with the necessary parameters
Create a receiver channel to receive the IDOC
Map the IDOC fields to the target system fields
Test the IDOC import process
Q7. What do you know about PDI ?
PDI stands for Product Development Inc. It is a global provider of enterprise software solutions.
PDI offers software solutions for convenience stores, petroleum wholesale, and logistics industries.
Their software solutions include ERP, fuel pricing, loyalty programs, and mobile solutions.
PDI has offices in North America, Europe, and Asia-Pacific regions.
Their clients include major companies such as 7-Eleven, Chevron, and Circle K.
Q8. How long you working on bods system
I have been working on the BODS system for 5 years.
I have 5 years of experience working on the BODS system.
I have successfully implemented multiple projects using the BODS system.
I am familiar with the latest updates and features of the BODS system.
I have trained and mentored junior consultants on the BODS system.
I have a deep understanding of the BODS system's architecture and functionality.
Data Integration Jobs
Q9. How to go with inbound idocs implementation? what is extension in idoc?
Inbound IDoc implementation involves configuring partner profiles and processing the IDoc data. Extension in IDoc allows adding custom fields to the standard IDoc structure.
Create a partner profile for the sender system in transaction WE20
Define the IDoc type and message type in transaction WE82
Create a port and assign it to the partner profile in transaction WE21
Configure the inbound processing in transaction BD51
Extension in IDoc involves adding custom segments or fields to...read more
Q10. What are the different PI adapter you have worked on?
I have worked on various PI adapters including PI JDBC, PI ODBC, PI Web API, and PI AF SDK.
PI JDBC adapter for connecting to PI data archive using Java
PI ODBC adapter for connecting to PI data archive using ODBC drivers
PI Web API adapter for accessing PI data archive through web services
PI AF SDK adapter for accessing PI Asset Framework data
Q11. 4. How to connect SQL server to databricks
To connect SQL server to Databricks, use JDBC/ODBC drivers and configure the connection settings.
Install the appropriate JDBC/ODBC driver for SQL server
Configure the connection settings in Databricks
Use the JDBC/ODBC driver to establish the connection
Q12. How can you call data into framework
Data can be called into framework using various methods.
Data can be called using APIs
Data can be called using database connections
Data can be called using file imports
Data can be called using web services
Data can be called using data providers
Q13. Explain data integration & pipeline
Data integration & pipeline involves combining data from multiple sources and processing it to make it usable for analysis.
Data integration is the process of combining data from different sources into a single, unified view.
Data pipeline refers to the series of steps that data goes through from collection to analysis.
Data integration ensures that data is clean, consistent, and accurate before being processed in the pipeline.
Examples of data integration tools include Talend, I...read more
Q14. Design a app which will bring data from lot of external vendors in different formats
Design an app to bring data from external vendors in different formats
Create a data ingestion pipeline to collect data from various vendors
Implement data transformation processes to standardize formats
Utilize APIs or web scraping techniques to retrieve data from vendors
Use a database to store and manage the collected data
Implement data validation and cleansing techniques to ensure data quality
Q15. What is difference between ALE and EDI Idoc
ALE is a technology used for exchanging business data between different systems within an organization, while EDI Idoc is a specific format used for exchanging data between different systems outside an organization.
ALE (Application Link Enabling) is used for communication within an organization's systems.
EDI (Electronic Data Interchange) Idoc is a specific format used for exchanging data between different systems outside an organization.
ALE is real-time data exchange, while E...read more
Q16. Informatica - How will you select last 10 lines from a file in mapping
To select the last 10 lines from a file in Informatica mapping, use the Source Qualifier transformation with a SQL override.
Add a Source Qualifier transformation to the mapping.
In the Source Qualifier transformation, specify the file as the source and set the appropriate file properties.
Write a SQL override in the Source Qualifier transformation to select the last 10 lines from the file.
Use the ROWNUM pseudocolumn or the ROW_NUMBER() function to order the rows in descending o...read more
Q17. How would you kill any job in Datastage
To kill a job in Datastage
Stop the job manually from the Director client
Terminate the job from the command line using the dsjob command
Kill the job process from the operating system level
Delete the job from the Datastage repository
Q18. How will you get the data into the BI
Data can be extracted from various sources like databases, APIs, flat files, etc. and transformed using ETL tools before loading into BI.
Identify data sources and their accessibility
Choose appropriate ETL tool for data extraction and transformation
Design data model and schema for BI
Load data into BI using ETL tool
Validate and verify data accuracy and completeness
Q19. Difference between connected and unconnected lookup
Connected lookup is used in mapping flow, while unconnected lookup is used in expression transformation.
Connected lookup is used in mapping flow, while unconnected lookup is used in expression transformation.
Connected lookup receives input values directly from the pipeline, while unconnected lookup receives input values from the calling transformation.
Connected lookup returns a value to the pipeline, while unconnected lookup returns a value to the calling transformation.
Conne...read more
Q20. ETL- how to do the incremental load in ADF and in SSIS
Incremental load in ADF and SSIS involves identifying new or updated data and loading only those changes.
In ADF, use watermark columns to track the last loaded value and filter data based on this value
In SSIS, use CDC (Change Data Capture) components or custom scripts to identify new or updated data
Both ADF and SSIS support incremental loading by comparing source and target data to determine changes
Q21. How do you know ETL tool connects to servers
ETL tools connect to servers through various methods such as JDBC, ODBC, APIs, and FTP
ETL tools can connect to servers using JDBC (Java Database Connectivity) for databases like MySQL, Oracle, etc.
ODBC (Open Database Connectivity) can be used to connect ETL tools to servers for data extraction and loading
APIs (Application Programming Interfaces) are commonly used to connect ETL tools to web services and cloud platforms
FTP (File Transfer Protocol) can be utilized to transfer f...read more
Q22. Tell me about CDC stage
CDC stage refers to the Centers for Disease Control and Prevention's classification system for the progression of a disease.
CDC stage is used to categorize the severity and progression of diseases.
It helps in determining the appropriate treatment and management strategies.
CDC stages are often used in the context of HIV/AIDS, cancer, and other chronic illnesses.
Each stage is defined based on specific criteria, such as symptoms, laboratory results, and disease progression.
For e...read more
Q23. Explain process in adf
ADF stands for Azure Data Factory, a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
ADF allows you to create data-driven workflows for orchestrating and automating data movement and data transformation.
You can use ADF to ingest data from various sources, process and transform the data, and then publish the data to different destinations.
ADF supports a wide range of data integration scenarios, including batch processing, rea...read more
Q24. What is IR - integration Runtime? what are the types of IR
Integration Runtime (IR) is a compute infrastructure that provides data integration capabilities across different network environments.
IR is used in Azure Data Factory to provide data integration capabilities
There are three types of IR: Azure, Self-hosted, and Azure-SSIS
Azure IR is fully managed by Microsoft and is used for data movement in the cloud
Self-hosted IR allows data movement between on-premises and cloud data stores
Azure-SSIS IR is used for running SQL Server Integr...read more
Q25. How to integrate data in EPBcS
Integrating data in EPBcS involves mapping data sources, defining data mappings, and setting up data integration processes.
Map data sources to EPBcS data model
Define data mappings between source systems and EPBcS
Set up data integration processes to transfer data into EPBcS
Use ETL tools like Informatica or Talend for data integration
Ensure data quality and consistency during integration
Q26. What is mapplet
A mapplet is a reusable object in Informatica PowerCenter that contains a set of transformations.
Mapplets can be used in multiple mappings to perform the same set of transformations.
They can simplify mapping development by encapsulating common logic.
Mapplets can have input and output ports to connect with other transformations.
Q27. how many transformation are there in sap bods
There are 4 main transformations in SAP BODS.
There are 4 main transformations in SAP BODS: Query transform, Case transform, Map operation transform, and Validation transform.
Query transform is used to extract data from a source and apply filters, joins, and other operations.
Case transform is used for conditional processing and data manipulation.
Map operation transform is used for data mapping and transformation.
Validation transform is used to validate data based on predefined...read more
Q28. Diff between powercenter and IICS
PowerCenter is an on-premise data integration tool, while IICS is a cloud-based integration platform.
PowerCenter is on-premise, IICS is cloud-based
PowerCenter is a traditional ETL tool, IICS is a modern integration platform
PowerCenter requires infrastructure setup, IICS is managed by Informatica
PowerCenter is more suitable for large enterprises with on-premise data, IICS is better for cloud-based integrations
Q29. Difference between FBDI and ADFDI?
FBDI is used for bulk data imports while ADFDI is used for interactive data entry and updates.
FBDI stands for File-Based Data Import and is used for bulk data imports into Oracle Cloud applications.
ADFDI stands for Application Development Framework Desktop Integration and is used for interactive data entry and updates.
FBDI requires users to prepare data in predefined templates and upload them in batches.
ADFDI allows users to directly interact with Oracle Cloud applications fr...read more
Q30. How to integrate entities
Integrating entities involves connecting different systems or components to work together seamlessly.
Identify the entities that need to be integrated
Determine the communication protocols and data formats for integration
Develop APIs or middleware to facilitate communication
Test the integration to ensure proper functionality
Monitor and maintain the integration for ongoing performance
Q31. What happens if Treat source row property as "Update" at session level but at target object "Delete" is checked?
The source row will be treated as an update, but the target object will be deleted.
The session level property 'Treat source row as Update' will be applied to the source row.
The target object will be deleted regardless of the update status of the source row.
This can result in data loss if the source row contains important information.
Q32. Do we integration btwn SAP datasphere and SAC
Yes, integration between SAP DataSphere and SAC is possible.
SAP DataSphere can be integrated with SAP Analytics Cloud (SAC) to enable data sharing and analysis.
Integration allows users to access and analyze data from SAP DataSphere within SAC.
Data can be imported from SAP DataSphere into SAC for further analysis and visualization.
Integration enables real-time data updates and synchronization between SAP DataSphere and SAC.
Users can create dashboards, reports, and visualizatio...read more
Q33. For each loop in SSIS
For each loop in SSIS
For each loop is used to iterate through a collection of items in SSIS
It can be used to loop through files, folders, database tables, etc.
The loop can be configured to run until a certain condition is met
Variables can be used to store the current item being processed
The loop can be nested within other loops or control flow tasks
Q34. Indirect file loading in informaticw
Indirect file loading is a process of loading data from a file that is not directly connected to the target system.
Indirect file loading involves using an intermediate file to load data into the target system.
This method is useful when the source file is not compatible with the target system.
Indirect file loading can be achieved using Informatica's indirect file method or by using a custom script.
Examples of indirect file loading include loading data from a mainframe system o...read more
Q35. Joiner transformation Connected and unconnected look u difference
Joiner transformation - connected and unconnected look up difference
Joiner transformation is used to join two sources based on a common key
Connected lookup is used when the lookup table is in the same mapping
Unconnected lookup is used when the lookup table is outside the mapping
Connected lookup returns multiple rows while unconnected lookup returns only one row
Joiner transformation can be used with both connected and unconnected lookup
Q36. Basic advantage of Talend.
Talend provides a unified platform for data integration and management, enabling organizations to easily connect and analyze data from various sources.
Talend simplifies data integration processes by providing a drag-and-drop interface for designing workflows.
It supports a wide range of data sources and formats, making it versatile for different use cases.
Talend offers built-in connectors for popular databases, cloud services, and applications, reducing the need for custom cod...read more
Q37. Types of edi mapping
Types of EDI mapping include structural mapping, cross-referencing mapping, and code set mapping.
Structural mapping involves mapping data from one format to another based on the structure of the data
Cross-referencing mapping involves mapping data by using a cross-reference table to match values between different systems
Code set mapping involves mapping data by translating codes from one system to another, such as translating product codes or currency codes
Q38. IICS implementation using cloud and on Prem RDBMS.
IICS implementation involves integrating cloud applications with on-premises RDBMS for seamless data flow.
Utilize Informatica Intelligent Cloud Services (IICS) to connect cloud applications with on-premises RDBMS
Leverage connectors provided by IICS for seamless integration
Ensure proper security measures are in place for data transfer between cloud and on-premises systems
Q39. Talend components which you worked
I have worked with various Talend components including tMap, tFilterRow, tAggregateRow, tSortRow, tFileInputDelimited, tFileOutputDelimited, tJavaFlex, tJavaRow, tNormalize, tDenormalize, tPivotToColumnsDelimited, tUnpivot, tReplace, tExtractRegexFields, tExtractXMLField, tExtractJSONField, tConvertType, tJoin, tReplicate, tSample, tRandom, tSystem, tSleep, tWarn, tDie, tSendMail, tFTP, tSSH, tS3Input, tS3Output, tRedshiftInput, tRedshiftOutput, tSalesforceInput, tSalesforceO...read more
Q40. Which loading methodology I am using and how you are implementing via syniti.
I am using the Extract, Transform, Load (ETL) methodology and implementing it via Syniti.
I am extracting data from various sources such as databases, files, and applications.
I am transforming the data to meet the requirements of the target system or database.
I am loading the transformed data into the target system using Syniti's data integration tools.
For example, I may be using Syniti Data Replication to replicate data from one database to another in real-time.
Q41. To organinise and keep golden data by analysing and merging data from different sources
The process involves analyzing and merging data from various sources to create a single, accurate, and reliable 'golden' record.
Identify all sources of data that need to be merged
Cleanse and standardize the data to ensure consistency
Use data matching and deduplication techniques to eliminate duplicates
Create rules for resolving conflicts between different data sources
Implement a master data management system to store and manage the golden record
Q42. 1. Explain SCD Type 2 Implementation in Informatica
SCD Type 2 is a technique used to track historical changes in data over time in a data warehouse.
SCD Type 2 maintains a separate row for each change in data, with a start and end date.
It requires a surrogate key to uniquely identify each row.
Informatica provides a built-in SCD Type 2 transformation to implement this technique.
Example: tracking changes in customer addresses over time.
Different row transformations in SSIS include Conditional Split, Derived Column, Lookup, and Merge.
Conditional Split: Routes data rows to different outputs based on specified conditions.
Derived Column: Adds new columns or modifies existing columns using expressions.
Lookup: Retrieves data from a related table based on a specified key.
Merge: Combines data from multiple sources into a single dataset.
Q44. How would you tackle in different source of data
I would approach different sources of data by first understanding the data structure, cleaning and transforming the data, and then integrating it for analysis.
Identify the different sources of data and their formats (e.g. CSV, Excel, databases, APIs)
Assess the quality of data and perform data cleaning and transformation processes
Integrate the data from various sources using tools like SQL, Python, or BI tools
Create a data model to combine and analyze the integrated data
Perfor...read more
Q45. How to copy recent files in adf
Use GetMetadata activity to get recent files and then copy them using Copy Data activity in ADF.
Use GetMetadata activity in Azure Data Factory to retrieve information about recent files.
Filter the files based on their last modified date to get the most recent ones.
Use Copy Data activity to copy the recent files to the desired destination.
Configure the Copy Data activity with the source and destination datasets and mappings.
Q46. What are the transformations in BODS
Transformations in BODS are used to manipulate data during the ETL process.
Transformations are used to extract, transform, and load data in BODS
Common transformations include Query, Case, Map_Operation, etc.
Transformations can be used to filter, join, aggregate, and cleanse data
Example: Query transformation is used to filter data based on specific criteria
Q47. 3.how to send IDOC flat file to application layer using logical path
Use logical path to send IDOC flat file to application layer
Define logical path in SAP system using transaction code FILE
Assign logical path to a physical directory where the IDOC flat file is stored
Use program RSEOUT00 to send the IDOC flat file to the application layer
Q48. What is the purpose of PDI.
PDI stands for Process Data Interchange. It is used to exchange data between different systems in a standardized format.
PDI is used to transfer data between different systems in a standardized way.
It helps in ensuring data integrity and consistency during data exchange.
PDI can be used in various industries such as manufacturing, healthcare, and finance.
Example: Using PDI to transfer production data from a manufacturing plant to a central database for analysis.
Q49. Have you worked on bods system.
Yes, I have worked on BODS system.
I have experience working with BODS system in my previous role as a Lead Consultant.
I have successfully implemented data integration solutions using BODS system.
I am familiar with the various components and functionalities of BODS system.
I have worked on data extraction, transformation, and loading tasks using BODS system.
I have also worked on integrating BODS system with other systems and databases.
Q50. Two files have different sets of columns in a file how to manage this in ssis
In SSIS, you can manage different sets of columns in two files by using conditional splits and dynamic column mapping.
Use a conditional split transformation to separate the data flow based on the file type or column presence
Create separate data flows for each file type and handle the columns accordingly
Use dynamic column mapping to map the columns dynamically based on the file type
You can use expressions and variables to dynamically handle the column mapping
Handle any additio...read more
Q51. Types of LKM used in file to file loads
There are three types of LKM used in file to file loads: LKM File to SQL, LKM SQL to File, and LKM File to File.
LKM File to SQL is used to load data from a file to a SQL database
LKM SQL to File is used to extract data from a SQL database to a file
LKM File to File is used to move data from one file to another
Q52. What is informatica why we use that tool
Informatica is a data integration tool used for ETL (Extract, Transform, Load) processes.
Used for data integration and ETL processes
Can connect to various data sources and targets
Provides a graphical interface for designing and managing workflows
Supports scheduling and monitoring of workflows
Can handle large volumes of data
Examples of use cases include data warehousing, data migration, and data synchronization
Q53. Containers in ssis
Containers in SSIS are used to group and organize tasks and workflows.
Containers provide a way to group related tasks together.
They help in organizing and managing complex workflows.
There are different types of containers in SSIS, such as Sequence Container, For Loop Container, and Foreach Loop Container.
Containers can be nested within each other to create hierarchical structures.
They allow for better control flow and error handling in SSIS packages.
Q54. How to handle data from multiple sources??
Handle data from multiple sources by integrating, cleaning, and validating it before analysis.
Integrate data using ETL tools like Informatica or Talend.
Cleanse data by removing duplicates, correcting errors, and standardizing formats.
Validate data by performing quality checks and ensuring consistency.
Use data governance practices to maintain data integrity and security.
Examples: Combine sales data from CRM, website analytics, and POS systems for comprehensive analysis.
Q55. Types of triggers in ADF
Triggers in ADF are events that can initiate the execution of a pipeline or a specific activity within a pipeline.
Event-based triggers
Schedule-based triggers
Tumbling window triggers
Blob storage event triggers
Q56. Why you are using BODS?
I am using BODS for data integration, transformation, and loading tasks in SAP environments.
Efficiently integrates data from various sources
Transforms data to meet business requirements
Loads data into SAP systems for analysis and reporting
Q57. ETL - How to do full load in SSIS, mention the steps
To perform a full load in SSIS, you can use the Data Flow Task with a source and destination component.
Create a Data Flow Task in the Control Flow tab of the SSIS package.
Add a source component to extract data from the source system.
Add a destination component to load data into the destination system.
Map the columns from the source to the destination.
Run the package to execute the full load.
Q58. Informatica - What is push down optimization?
Push down optimization is a technique used in Informatica to improve performance by pushing data transformation operations to the source or target database.
Push down optimization reduces the amount of data transferred between the source and target systems.
It allows the database engine to perform transformations, aggregations, and filtering, leveraging its processing power.
By pushing down operations, Informatica minimizes network latency and improves overall performance.
Exampl...read more
Q59. What is the difference between iics and power center
IICS is a cloud-based integration platform while Power Center is an on-premise data integration tool.
IICS is a subscription-based service while Power Center is a perpetual license product.
IICS offers pre-built connectors to various cloud applications while Power Center requires custom coding for cloud integrations.
IICS has a web-based interface while Power Center has a desktop-based interface.
IICS offers real-time data integration while Power Center is more batch-oriented.
IIC...read more
Q60. How to achieve SCD Type 2 in informatica, mention all the transformations used ?
SCD Type 2 in Informatica can be achieved using multiple transformations.
Use a Source Qualifier transformation to read data from the source.
Use an Expression transformation to derive new columns or modify existing ones.
Use a Lookup transformation to look up data in a reference table.
Use a Router transformation to route data to different targets based on conditions.
Use a Filter transformation to filter out unwanted data.
Use a Sequence Generator transformation to generate surro...read more
Q61. How to load few files in Informatica
To load files in Informatica, use the Source Analyzer to import the files, create a mapping, and then run the workflow.
Use the Source Analyzer to import the files into Informatica
Create a mapping in Informatica to define how the data should be transformed and loaded
Use the Workflow Manager to create a workflow that executes the mapping and loads the data
Q62. How would you implement SCD TYPE 2 IN INFORMATICA?
Implementing SCD Type 2 in Informatica involves using Slowly Changing Dimension transformations and mapping variables.
Use Slowly Changing Dimension (SCD) transformations in Informatica to track historical changes in data.
Create mapping variables to keep track of effective start and end dates for each record.
Use Update Strategy transformations to handle inserts, updates, and deletes in the target table.
Implement Type 2 SCD by inserting new records with updated data and marking...read more
Q63. Explain scd2 logic in informatica
SCD2 logic in Informatica is used to track historical changes in data by creating new records for each change.
SCD2 stands for Slowly Changing Dimension Type 2
It involves creating new records for each change in data, while maintaining a link to the previous record
It typically includes effective start and end dates to track the validity of each record
SCD2 logic is commonly used in data warehousing to maintain historical data accurately
Q64. What is Informatica tool
Informatica is a data integration tool used for ETL (Extract, Transform, Load) processes in data engineering.
Informatica is used for extracting data from various sources like databases, flat files, etc.
It can transform the data according to business rules and load it into a target data warehouse or database.
Informatica provides a visual interface for designing ETL workflows and monitoring data integration processes.
It supports scheduling, monitoring, and managing data integra...read more
Q65. Informatica - What are lookups and their types? Differences between those types in terms of input and output ports?
Lookups in Informatica are used to retrieve data from a reference table based on a matching condition.
Lookups are used to perform data transformations and enrich the data in a mapping.
There are three types of lookups in Informatica: Connected, Unconnected, and Static.
Connected lookup returns multiple rows and can be used in any transformation.
Unconnected lookup returns a single value and is used in expressions or transformations.
Static lookup is used to retrieve a single row ...read more
Q66. INFORMATICA ROUTER VS UNION
Informatica Router and Union are used for data integration and transformation.
Informatica Router is used to route data based on certain conditions.
Informatica Union is used to combine data from multiple sources.
Router can be used to split data into multiple targets based on conditions.
Union can be used to merge data from multiple sources into a single target.
Router can be used to implement complex data flows.
Union can be used to eliminate duplicates from the data.
Q67. SCD in informatica
Slowly Changing Dimension (SCD) in Informatica is used to track historical data changes in a data warehouse.
SCD Type 1: Overwrite old data with new data
SCD Type 2: Add new row for each change with effective start and end dates
SCD Type 3: Add columns to track changes without adding new rows
Q68. Push down optimisation in informatica
Push down optimization in Informatica is a technique used to improve performance by pushing processing tasks to the source or target database.
Push down optimization reduces the amount of data transferred between Informatica and the database
It can improve performance by leveraging the processing power of the database
Examples include using SQL queries in Source Qualifier transformations to push filtering and aggregation operations to the database
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