Question

course: IT Data Mining and Data Warehousing

There are several typical cube computation methods such as Multi-Way, BUC, and Star-cubing. Briefly describe each one of these methods outlining the key points.

note: need a unique answer and no handwriting please.

Answer 1

According to the questions, there are several typical cube computation methods such as Multi-Way, BUC, and Star-cubing. Data cube computation describes out to be an important task in the implementation of a data warehouse. The pre calculations of a data cube are capable of reducing the response time and improves online analytical processing. Although its a challenge because it requires time and storage space.

Some of the important methods are:

>> Multi-Way method.

>> BUC(Bottom-Up Computation).

>> Star-Cubing method.

The explanations of such methods and their key points are given below:

• Multi-Way Array Method:

Multi way array method is basically an Array-based algorithm that uses multidimensional blocks to get implemented.

The following key points are:

> Tuple comparisons are avoided.

> It supports simultaneous aggregation on various dimensions

> It aggregates values that can be reused for computing previous cuboids

> Proper pruning is not possible with the full materialization.

> No processing of iceberg optimization.

• BUC(Bottom-Up Computation):

Bottom up computation is the “Top-down” method approach that supports partial materialization.

The following key points are:

> Involves iceberg computation of cubes.

> Properly divides dimensions into block chambers.

> It supports iceberg pruning.

> Does not support real-time to time aggregation.

> Huge data cubes calculations.

• Star cubing:

Star cubing is the combination of a bottom-up approach and a top-down approach. So it is also applicable for the Multi-Way Array Method and button-up computation.

The following key points are:

> Star cubing's data structure is almost resemble the H tree.

> It involves the multidimensional computation of the cubes.

> It supports the bottom-up approach that's why it can explore the notation of a shared dimension.

> It follows the Iceberg pruning.

> In star cuboid tree consists of many levels. Every level has its dimension and it can be two-dimensional or three-dimensional.

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