Data Integration Interview Preparation Guide
Sharpen your Data Integration interview expertise with our handpicked 24 questions. Each question is crafted to challenge your understanding and proficiency in Data Integration. Suitable for all skill levels, these questions are essential for effective preparation. Get the free PDF download to access all 24 questions and excel in your Data Integration interview. This comprehensive guide is essential for effective study and confidence building.24 Data Integration Questions and Answers:
1 :: Explain how to adjust the performance of Data Integrator?
Following are the ways to perform this:
- Using array fetch size.
- Ordering the joins.
- Extracted data minimizing.
- Locale conversion minimization.
- Setting target-based options to optimize the performance.
- Improving throughput.
- Data type conversion minimization.
- Using array fetch size.
- Ordering the joins.
- Extracted data minimizing.
- Locale conversion minimization.
- Setting target-based options to optimize the performance.
- Improving throughput.
- Data type conversion minimization.
2 :: Explain what are the benefits of data integration?
Following are the benefits of data integration:
- Makes reporting, monitoring, placing customer information across the enterprise flexible and
convenient.
- Data usage is efficient.
- Cost Effective.
- Risk adjusted profitability management as it allows accurate data extraction.
- Allows timely and reliable reporting, as data quality is the prime technology for business challenges.
- Makes reporting, monitoring, placing customer information across the enterprise flexible and
convenient.
- Data usage is efficient.
- Cost Effective.
- Risk adjusted profitability management as it allows accurate data extraction.
- Allows timely and reliable reporting, as data quality is the prime technology for business challenges.
3 :: Can you explain what are the three major types of data integration jobs?
Following are the major data integration jobs:
- Transformation jobs – for preparing data
- Should be used when data must not be changed unless job completion of transforming data of a particular subject of interest
- Provisioning jobs - for transmission of data
- Should be used when data must not be changed unless job transformation when the data provisioning is large.
- Hybrid jobs – to perform both transformation and provisioning jobs.
- Data must be changed irrespective of success / failure.
- Should be implemented neither the transformation nor the provisioning requirements are large
- Transformation jobs – for preparing data
- Should be used when data must not be changed unless job completion of transforming data of a particular subject of interest
- Provisioning jobs - for transmission of data
- Should be used when data must not be changed unless job transformation when the data provisioning is large.
- Hybrid jobs – to perform both transformation and provisioning jobs.
- Data must be changed irrespective of success / failure.
- Should be implemented neither the transformation nor the provisioning requirements are large
4 :: What is Manual Integration?
- Also known as Common User Interface.
- All the relevant information to access form the source system or web page interface is operated by the users.
- Unified view of the data does not exist.
- All the relevant information to access form the source system or web page interface is operated by the users.
- Unified view of the data does not exist.
5 :: What is Application Based Integration?
- ABI requires specific applications for implementing all the integration efforts.
- When the number of applications is limited, this approach is well manageable.
- When the number of applications is limited, this approach is well manageable.
6 :: What is Physical Data Integration?
- Physical Data Integration is all about creating new system that replicates data from the source systems.
- This process is done to manage the data independent of the original system.
- Data Warehouse is the example of Physical Data Integration.
- The benefits of PDI include data version management, combination of data from various sources, like mainframes, flat files, databases.
- A separate system is needed for handling vast data volumes.
- This process is done to manage the data independent of the original system.
- Data Warehouse is the example of Physical Data Integration.
- The benefits of PDI include data version management, combination of data from various sources, like mainframes, flat files, databases.
- A separate system is needed for handling vast data volumes.
7 :: What is Data Integration hierarchy?
The DI hierarchy is as follows:
- Project->JOB->WorkFlow->DataFlow.
- WorkFlow also has scripts.
- Source, Query, Target are under Data Flow and known as Transformations.
- Workflow, Dataflow, data, files or tables usage for certain number of times, is specified by usage count.
- Objects can be used more than once in Data Integration. These objects are known as reusable objects.
- Project->JOB->WorkFlow->DataFlow.
- WorkFlow also has scripts.
- Source, Query, Target are under Data Flow and known as Transformations.
- Workflow, Dataflow, data, files or tables usage for certain number of times, is specified by usage count.
- Objects can be used more than once in Data Integration. These objects are known as reusable objects.
8 :: Explain what is Hierarchy Flattening?
- Construction of parent/child relationships hierarchy is known as Hierarchy Flattening.
- A description of hierarchy in the vertical or horizontal format is produced.
- The hierarchy pattern includes Parent column, Child Column, Parent Attributes and Child Attributes.
- Hierarchy Flattening allows to understand the basic hierarchy of BI in a lucid manner.
- As the flattening is done in horizontal or vertical format, the sub elements are easily identified.
- A description of hierarchy in the vertical or horizontal format is produced.
- The hierarchy pattern includes Parent column, Child Column, Parent Attributes and Child Attributes.
- Hierarchy Flattening allows to understand the basic hierarchy of BI in a lucid manner.
- As the flattening is done in horizontal or vertical format, the sub elements are easily identified.
9 :: What are Data Integrator Metadata Reports?
- Browser-based analysis and reporting capabilities are provided by Metadata reports.
- The DI Metadata Reports are generated on metadata that associates with
1. Data Integration jobs.
2. Other BO applications those are associated with Data Integration.
- Three modules are provided by Metadata Reports. They are
1. Operational Dashboards.
2. Auto Documentation.
3. Impact and Lineage analysis.
- The DI Metadata Reports are generated on metadata that associates with
1. Data Integration jobs.
2. Other BO applications those are associated with Data Integration.
- Three modules are provided by Metadata Reports. They are
1. Operational Dashboards.
2. Auto Documentation.
3. Impact and Lineage analysis.
10 :: Explain various caches available in Data Integrator?
- NO_CACHE – It is used for not caching values.
- PRE_LOAD_CACHE – Result column preloads and compares the column into the memory, prior to executing the lookup.
- PRE_LOAD_CACHE is used when the table can exactly fit in the memory space.
- DEMAND_LOAD_CACHE – Result column loads and compares the column into the memory when a function performs the execution.
- DEMAND_LOAD_CACHE is suitable while looking up the highly repetitive values with small subset of data.
- PRE_LOAD_CACHE – Result column preloads and compares the column into the memory, prior to executing the lookup.
- PRE_LOAD_CACHE is used when the table can exactly fit in the memory space.
- DEMAND_LOAD_CACHE – Result column loads and compares the column into the memory when a function performs the execution.
- DEMAND_LOAD_CACHE is suitable while looking up the highly repetitive values with small subset of data.