Our service offer for corporate market is relatively wide. It consists of specialized consulting in identifying business processes, analyzing information flow, defining data models, selecting appropriate software solutions for our customers etc. We also support installation of large systems, and provide dedicated software to be integrated with them or to work as standalone applications.
A very important field of our activity is advanced data analysis commonly described as data mining. Here we employ Statsoft, Oracle and SPPS dedicated software, as well as our own tool, N-Predictor.
We are also quite experienced in the software systems supporting IT infrastructure management of companies. Last not least we offer them outsourcing services including hardware and software maintenance.
Data mining stands for searching knowledge, hidden somewhere in gigabyte databases. Knowledge is something more than just information, it implies structure i.e., specific correlation, statistical rules or some other dependencies, which can be expressed in terms of mathematics or of a natural language. Of course, it is not easy to find them - sometimes one is even not aware of their existence. On the other hand, they can be worth many million dollars if e.g., they refer to market reactions important for a given branch. Sometimes to catch them means to be able to predict future, and obviously to gain advantage over competitors. An obvious example would be the extrapolation of stock market quotations, but actually each big company stores different data on the disks of its computers and, dependently on the approach, those data can either have a pure historical value, or they can serve as a source material for interesting market analysis, which total cost may be decreased by an important part, namely that corresponding to data gathering.
Usually, when extracting information from databases, one knows quite well what one is looking for. Building complex, cross reports may be sometimes very complicated technically, but it is always a well defined procedure - a report answers a precise question, like "Display all customers, who purchased goods worth over $10.000 during last month and have not paid for them yet.". Now, the most important about data mining is that we can not ask any precise question. We only wish to know if there is some hidden knowledge in the database.
Some common applications of data mining:
To do data mining one needs dedicated tools, allowing one to notice complex correlation between data stored in big corporate databases. Here our consultants apply products offered by SPSS (mainly Clementine) and Oracle (Darwin, 9i). For some purpose they also use our own dedicated prediction system N-Predictor, based on neural networks .
Now supporting data mining functions buitl-in the database 9i developed by Oracle are available. Any further information on it can be found in the article published in conference material of the Polish Oracle User Group.
Artificial neural network is a system which process data parallel in a way human brain does. Although the analogy is (at least so far) rather weak, neural networks reveal surprisingly many features, typical rather for thinking creatures than for traditional silicon computers. It is the essence of neural networks that they can be trained, actually by a lengthy procedure of adjusting a huge number of coefficients "weighting" the processed signals, called synaptic weights. From the human point of view neural networks are black boxes, creating e.g., quite good predictions in their own way. A trained network is a system which reacts on particular input signals in an appropriate way and thus it can be a model of some phenomenon or manufacturing process, predicting its future behavior.
To learn more about neural networks, click here
Decision trees algorithms enable one to automatically generate analytic sentences describing data like e.g., "If the thermometer 1 measures the temperature higher than 150 centigrade and the thermometer 2 measures the temperature higher than 120 centigrade then a damage is probable". This property is very important, since the skill of formulating such sentences about the surrounding world is a necessary (but not sufficient) condition to say that one "understands" this world.
One can view data records as points in a multidimensional space, which dimensions correspond to particular data attributes. If e.g., the data is about some machine, the dimensions can be temperature, pressure, power consumption etc. It may happen that the data records are spread out completely chaotically in such a space. However, sometimes they are grouped and build a sort of condensations, the so called clusters, which have usually some important meaning. Thus, e.g., if there are some clusters in a space describing address and education of people, this means that both features are related to each other. In two-dimensional spaces clusters may be seen with the naked eye, but in the case of many dimensions it is generally difficult to spot them without using special mathematical methods e.g., the so called K-means algorithm.
IT Infrastructure management
It would seem strange if IT people themselves were not affected by the rapid expansion of information technology. Their work is far from being cheap and they know better than anyone else, how helpful computers can be. Besides, they are not afraid of loosing their jobs, because it is commonly known that computers generally do not throw out of employment computer specialists.
Thus, IT departments - and not only their heads - should understand the necessity of using systems supporting IT infrastructure management (whatever this could really mean).
Actually, if the number of computers in a company is pretty large, it is not easy to say what one really possesses. Every machine has its own inner structure i.e., it constitutes of components, which can be exchanged or modified. The components come often from different vendors, they are subjected to different warranty or service agreements. Software looks more or less the same. Thus, it turns out that efficient cataloguing cannot be performed by means of a sheet of paper, of a spreadsheet, or even of a simple, dedicated program, developed ad hoc.
To get the necessary information, one installs special pieces of software on particular workstations or active network devices, the so called inteligent agents, who permanently control their configuration and activity. All information coming from the appropriate system elements to the central unit, independently how it is transferred, can be used both for current operations (e.g., an exchange of a malfunctioning processor cooling fan), and for strategic analyses.
IT departments establish special help desk centers, which employes are called in to fix the damages and to restore the original state. For obvious reasons, all user claims and help desk reactions should be carefully registered and here a copybook is clearly not enough. One needs computer systems to enable the management the appropriate control and detailed analyses concerning e.g., hardware and software failure frequency, reaction time, work efficiency etc.
The basic minimum of securing computer systems against intrusions is achieved by passive elements i.e., protected by passwords access to data and services, proxy servers, firewalls etc. However, in the case of large companies, and of the ones particularly liable to attacks, this is definitely not enough. Systems must defend actively i.e., permanently monitor and diagnose the situation, alert administrators and even disconnect some elements if any attempts of attack are spot. One has to monitor in real time the network traffic in order to detect intrusions and to analyze the activity of modems installed or duble network adapters in connection with untypical attempts to access databases or other events, looking innocent at first glance.
Strategic analyses, actually performed by company management, are based on various kinds of reports emerging from the gathered information. The reports should be very flexible when selecting data but at the same time they should have a clear, uniform, graphic form and their building should not be difficult.
Last not least, there is a group of problems connected with the functioning of IT department itself, referring to a sort of inner control. It concerns user claims and help desk reactions, the entire system mortality, repairing damages, and services of external companies. IT management is often forced to perform various economic analyses and answer questions like: "What should I do in order to increase work efficiency, to decrease costs or to prove my expenses reasonable?".