As the world we live in becomes faster, more complex and a little crazier every day, we humans have adapted to the demands placed on us by reinforcing our need for mass convenience and instant everything.
You don`t have to give up a Saturday to work in the garden anymore because the garden service does the job in 45 minutes. No more slaving over a hot stove: you can pick up burgers without getting out of the car. In fact, you can have any dish you like from Piet`s pap-and-wors special to Vietnamese delicacies delivered to your door in less than 45 minutes after ordering them over the phone.
"We live in a world of instant convenience in which we have conditioned ourselves that everything should be available easily and now," says Aubrey van Aswegen, MD of Knowledge Integration Dynamics (KID).
Technology has brought us many benefits, but it is often easy to accept the benefits as a given and forget that some tasks still require skills and work. This is very evident in the business intelligence (BI) market. "BI is not a new discipline," Van Aswegen states. "Business leaders have known for many years that by examining company data collected in day-to-day transactions, orders, shipments and complaints, they can gain valuable knowledge to assist them in making decisions to benefit the bottom line." In days gone by, the process went something along the lines of:
* Manager would call the IT department and put in a request for a new or updated report drawn from the corporate database at regular intervals.
* Someone in IT would write the code to generate the report and print it out in a specific format - after a certain amount of time had elapsed, depending on the manager`s importance and standing in IT.
* The manager would then use this printout as a BI tool.
* If the report didn`t deliver as required, it was back to IT to fix the program and rerun the query.
A cumbersome process. In addition, in large organisations, these queries could retard the performance of the company`s networks and databases as more managers queried more and more data. The technical skills needed to maintain and continually improve these queries also took its toll.
The solution was to remove the processing from the transaction systems and make use of online analytical processing (OLAP) tools. These systems reduced the load on transactional systems, while also giving BI an easier front-end interface so that managers could handle their own queries and tweak them as required.
The time required was substantially improved and users could query data in various dimensions and then query the results in different dimensions. The concept of "slicing and dicing" data became possible and users were assisted in finding the right questions to ask and discovering patterns in the data that could influence business decisions.
"As far as OLAP tools extended, they were initially useful in giving companies an edge," comments Van Aswegen, "but when everyone is using the same tools, where does one obtain competitive advantage?"
This is where data mining comes into play. "While OLAP tools can assist in finding and monitoring preset answers and known patterns, the purpose behind data mining is to reveal unknown patterns, thus providing a real, sustainable competitive advantage," Van Aswegen says.
Data mining tools are designed to use various strategies, including statistical analysis and neural networks to find and extract data correlations for users. "Data mining is not a simple task that can be automated to a push-button query, however," warns Van Aswegen. "Specialist skills are required to make full use of the various tools available on the market. This costs more, but can also yield insights that direct organisations to new markets, reduce costs and more. "It`s the same as servicing your BMW: Joe`s Garage can have a bash at it, but if you want guaranteed results, you get a certified technician."
BI is a broad field. In many cases, OLAP tools provide exactly what organisations require in terms of sifting through data and detecting known patterns and asking the correct questions. Data mining, on the other hand, gains in value as you give it more data across a broader spectrum of subject areas. It is organisations looking for an edge that will invest in data mining solutions as a way to delve deeper into more data and find unique competitive differentiators.
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