You need to design a partitioning strategy that meets the requirements

You are designing a partitioning strategy for a SQL Server Analysis Services (SSAS) cube.
New data is loaded in real-time into the data warehouse that feeds the cube. Between 10
million and 15 million rows of data are loaded into the main fact table each day from a
Microsoft Azure SQL Database.
You have the following requirements:
Maximize cube query performance during business hours.
Ensure that data is available in the cube as soon as possible after it is loaded into the data
warehouse.
You need to design a partitioning strategy that meets the requirements.
What should you do? (More than one answer choice may achieve the goal. Select the BEST
answer.)

You are designing a partitioning strategy for a SQL Server Analysis Services (SSAS) cube.
New data is loaded in real-time into the data warehouse that feeds the cube. Between 10
million and 15 million rows of data are loaded into the main fact table each day from a
Microsoft Azure SQL Database.
You have the following requirements:
Maximize cube query performance during business hours.
Ensure that data is available in the cube as soon as possible after it is loaded into the data
warehouse.
You need to design a partitioning strategy that meets the requirements.
What should you do? (More than one answer choice may achieve the goal. Select the BEST
answer.)

A.
Partition the cube by day for history, using hybrid OLAP (HOLAP) storage mode. Create a
daily partition that uses multidimensional OLAP (MOLAP) storage mode during the day.
Reprocess the partition incrementally during the day.

B.
Partition the cube by week for history. Create a daily partition that uses multidimensional
OLAP (MOLAP) storage mode. Process the partition periodically to add new data.

C.
Partition the cube by day for history, using multidimensional OLAP (MOLAP) storage
mode. Create a daily partition that uses proactive caching during the day. Reprocess the
partition in full MOLAP storage mode at night

D.
Partition the cube by day for history, using multidimensional OLAP (MOLAP) storage
mode. Create a daily partition that uses relational OLAP (ROLAP) storage mode during the
day. Reprocess the partition in full MOLAP storage mode at night.

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Dude

Dude

Sounds like C could be the answer.

Question: Ensure that data is available in the cube as soon as possible after it is loaded into the data
warehouse.

Therefore, proactive caching makes sense.

https://msdn.microsoft.com/en-us/library/ms174769.aspx

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Henrov

Henrov

I agree wholeheartedly:

If you have applications in which your users need to see recent data and you also want the performance advantages of MOLAP storage, SQL Server Analysis Services offers the option of proactive caching to address this scenario, particularly in combination with the use of partitions. Proactive caching is set on a per partition and per dimension basis. Proactive caching options can provide a balance between the enhanced performance of MOLAP storage and the immediacy of ROLAP storage, and provide automatic partition processing when underlying data changes or on a set schedule.

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