Sisense BI ElastiCube Management & Data Connectivity 2

Question 1

What is the purpose of ElastiCube clustering in a Sisense deployment?

Accepted Answer

To provide high availability and load balancing across multiple ElastiCube Server instances

Answer

To split large datasets across multiple database tables

Answer

To group related dashboards together for navigation

Answer

To manage user group permissions more efficiently

Question 2

How can custom SQL queries be incorporated into an ElastiCube schema in Sisense?

Accepted Answer

By using the Custom SQL Table option within ElastiCube Manager

Answer

By editing the .ecschema XML file directly with raw SQL

Answer

By writing stored procedures in the source database only

Answer

Custom SQL is not supported; only visual table imports work

Question 3

What is a calculated column in a Sisense ElastiCube?

Accepted Answer

A derived column created using a formula expression and stored during the build process

Answer

A column sourced directly from a calculated field in the source database

Answer

A column generated by aggregating data from multiple tables at query time

Answer

A column that is computed dynamically each time a dashboard loads

Question 4

Which build type should be selected when only the structure of tables in the ElastiCube has changed but no data changes occurred?

Accepted Answer

Schema Changes Only

Answer

Full Build

Answer

Accumulative Build

Answer

Metadata Refresh Only

Question 5

What is the recommended approach in Sisense for connecting to cloud SaaS data sources like Salesforce or Google Analytics?

Accepted Answer

Use Sisense's native cloud connectors available in ElastiCube Manager

Answer

Export data to CSV manually and import on a schedule

Answer

Write a custom REST API connector from scratch using Python

Answer

Cloud SaaS sources are not supported natively; only on-premises databases work

Question 6

Which Sisense component is the dedicated tool for designing and building ElastiCube data models?

Accepted Answer

ElastiCube Manager

Answer

Sisense Dashboard Designer

Answer

Sisense Query Builder

Answer

Sisense Schema Studio

Question 7

What key performance advantage does ElastiCube's columnar storage provide for analytical workloads?

Accepted Answer

Better performance for aggregations and scans on large datasets by reading only relevant columns

Answer

Faster row-level OLTP transaction processing

Answer

Improved performance for frequent single-record inserts and updates

Answer

Reduced storage space through row-level compression algorithms