Multi-dimensional model is an integral aspect of the On-line Analytical Processing which also known as OLAP.
Due to the fact that OLAP is online it provides information quickly, iterative queries are often posed during interactive sessions.Due to the analytical nature of OLAP the queries are often complex. The multi-dimensional model is used to solve this kind of complex queries. The model is important because it applies simplicity.This helps users understand the databases and enables software to plot a course through the databases effectively.
What are the areas of implementation of multi dimensional information modelling in construction? How will it enhance productivity and improve the performance of construction activity?
Hi Ranjith
Just to clarify OLAP does not provide information quickly because it is on-line, it is quick because all of the raw data is held in system RAM. This means you need a massive amount of RAM available to accommodate all the data you have and are likely to need in the foreseeable future.
The primary function of OLAP, is for use as a business intelligence tool, which can be used to understand how a business is performing over different locations and different products over time, hence the three dimensions of the OLAP cube. Of course, you can use many more dimensions if it is appropriate. The open source version PALO, for example, can handle up to 256 dimensions (anything more than 3 dimensions is known as a hypercube).
Large supermarket chains were quick to adopt this software, as it enabled them to analyse how different locations performed, or how much they made from different product lines, and how much they made week by week. The core raw data is generally aggregated to a high level of abstraction for management to see the overview, but they can drill down to identify whatever level of detail they need to analyse queries quickly. They can also "slice and dice" to get the answer to any specific questions they might have.
Since large supermarket chains record live data streams from all their cash registers, they can easily see what products are selling and can handle their inventory needs much more easily. Many provide these data streams direct to product suppliers to allow the product supplier to manage the inventory re-supply for them. They can also track sales flows by shelf, shelf position and location within each store if they want to.
This leads to the collection of vast amounts of data, hence the need for vast data warehouses to store it all, as well as massive compute power to process it, as well as enough system RAM to load it all into.
As you can see, large supermarkets use this system for strategic analysis in order to discover trends and identify opportunities for making more money. Were this to be adopted by construction, an obvious difference is that a large supermarket might stock 40,000 - 100,000 product lines, depending on the size of the store. Many will have hundreds or thousands of store locations. In construction, there will be fewer product lines, but each product will be constructed out of thousands of individual components. With a supermarket, each product will be re-sold many, many times every day, whereas, in construction, each product is unique, although many copies may be built and sold over time. OLAP could certainly be used to collect all the data about costing for each individual properly, but there would need to be a considerable input from both quantity surveyors and management accountants, in order to ensure costs were allocated properly. Providing the additional cost of this would could be justified, then it could be beneficial for cost analysis purposes. But remember, costs can be more volatile in construction, unlike in supermarkets, where large supermarket chains can negotiate fixed price contracts for a whole year. Labour rates may vary from one location to another. Allocating overheads might also be problematic, given that once a construction site is completed, it is necessary to move the staff and equipment to another one.
Hope that helps.
Regards
Bob
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