IICS Certification Mass Ingestion and Data Synchronization 2

Question 1

What is 'Data Synchronization' in IICS, and how does it differ from Data Integration mappings?

Accepted Answer

Data Synchronization is a wizard-driven task for simple source-to-target sync without coding; Data Integration uses full mapping design

Answer

Data Synchronization only works with files; Data Integration works with databases

Answer

Data Synchronization runs in real time; Data Integration is batch only

Answer

They are identical features with different names

Question 2

In IICS Mass Ingestion, what is a 'deployment' and why is it needed?

Accepted Answer

The step that activates and persists a Mass Ingestion task configuration, making it ready to run

Answer

A code release of the IICS platform itself

Answer

A backup of the IICS organization settings

Answer

A test run of the task in sandbox mode

Question 3

Which IICS Mass Ingestion option allows you to select specific tables from a source database rather than ingesting all tables?

Accepted Answer

Table filters / table selection in the task configuration

Answer

Custom SQL in the Source transformation

Answer

Schema-level inclusion rules only

Answer

You must ingest all tables and filter at the target

Question 4

In IICS Mass Ingestion Databases with CDC, what is 'Apply latency'?

Accepted Answer

The delay between when a change occurs at the source and when it appears in the target

Answer

The time it takes to deploy a Mass Ingestion task

Answer

The lag between IICS cloud polling and Secure Agent response

Answer

The timeout for stale connection handling

Question 5

In IICS, what file formats are typically supported for Mass Ingestion Files source inputs?

Accepted Answer

Delimited (CSV), fixed-width, JSON, Parquet, and Avro formats

Answer

Only XML files

Answer

Only Excel spreadsheets (.xlsx)

Answer

Only JSON and YAML

Question 6

What is the purpose of 'partitioning' in IICS Mass Ingestion for large tables?

Accepted Answer

Splitting source data into parallel chunks to improve ingestion throughput

Answer

Dividing the target table into physical partitions for storage

Answer

Creating backup copies of data at different time points

Answer

Restricting which rows are visible to each user