Reading between the mines.

At some point in earlier times, mining was among the major, most-developing industries. Not surprisingly, history does repeat itself. But this time around, it's not the Au-kind of gold we're after and digging for.

One of the emerging and most powerful disruptive technologies in this day in age is termed data mining. As defined by Kurt Thearting in An Introduction To Data Mining, data mining is the extraction of hidden predictive information from large databases. In simpler words... reading between the mines.

Basically as the subject name indicates, this post is in accordance to our data mining class with Mr. Ramon Duremdes Jr.. Other insights on this are found on my co-data miners who's blog links are found left of this page.

Data mining aids companies focus on all the relevant information they can get hold of. Together with business intelligence, data mining tools, given databases of adequate size and quality, can create business opportunities by automating prediction of trends and behaviors and automating discovery of formerly unidentified patterns.
Data mining tools have the ability to answer business questions that traditionally were constrained with time. They quarry databases for veiled patterns, stumbling on upon information that perhaps human perception may overlook.

In order to survive in today's business ventures, many companies, aside from gathering and analyzing massive amounts of data, also see the need to shift and integrate data mining tools to their existing structures.
Data mining, along with artificial intelligence was listed by GartnerGroup Advanced Technology Note among the major technology areas that are and will keep on booming and in which companies of diverse industries will be investing in within the next couple of years. Well, with all the wonders of data mining, who wouldn't?

Companies nowadays are quite eager and enthusiastic of this rapdily-cultivating concept because of the fact that extensive processes of research and development has transformed data mining drastically as diverse techniques have surfaced along. Among these techniques, the most frequently used are artificial neural networks, decision trees, genetic algorithms, nearest neighbor method, rule induction, to name a few.

But before going into unfathomable concepts, how is it imaginable that data mining has the ability to tell us things we do not know or what would happen within the week, the month or year after, having such probabilistic and unstable economic conditions? Answer? Read on down.

The food chain begins with data and information, which of course are essential to creating business intelligence. Business intelligence, according to SAS, is the technology and practice of implementing information to make decisions. Business intelligence is considered to be obtained when information shows its true worth. And subsequent to this, not only a window, but an infinite number of doors are opened.

The cycle continues with knowledge workers utilizing the adequate Information Technology tools in order to define and analyze correlation and logic that lies behind the information. Examples of these tools are are databases, database management systems, data warehouses and data mining tools.

According to Haag, Phillip and Cummings on Management Information Systems for The Information Age, data mining tools are the software utilized to query information in a data warehouse supported by online analytical processing, which is the manipulation of information to support decision-making tasks.
Data mining tools include query-and-reporting tools, intelligent agents, multidimensional analysis tools and statistical tools.

• Query-and-reporting tools are similar to Query-By-Example tools, Structured-Query-Language and report generators in the typical database environment.

• Intelligent agents use several artificial intelligence tools as are neural networks and fuzzy logic in order to mold the basis of "information discovery" and building business intelligence.

• Multidimensional analysis tools are slick-and-dice techniques that permit the viewing of multidimensional information from different viewpoints.

• Statistical tools aid in applying various mathematical models to the information stored in a data warehouse to discover new information.

But the road is long and broad. Possessing the right data mining tools only bring us a step further and closer to home run. Obviously, there exist diverse industries, dissimilar organizational structures, business processes. A company must then adapt the adequate data mining technique/s.

Data mining techniques, according to Kurt Thearling in An Overview of Data Mining Techniques, are classified into classical techniques and next generation techniques.

The classical techniques are the techniques used 99.9% of the time on existing business problems, mainly because industries rely on techniques that consistent, understandable and explainable. Among the classifcal techniques are the following:

• Statistics: statistical techniques have long been used and are not data mining techniques. Nonetheless, statistical techniques are dependable on data and are utilized to discover trends and build forecasting models. Being familiar or knowledgeable of how statistical techniques work and how they can be used is a big factor in this technique.

• Neighborhoods: among the first used techniques in data mining, it is a prediction technique that is similar to clustering. Its nature is that to forecast a prediction value in one record, it looks for records with similar predictor values in the historical database and utilizes the prediction value from the record that is closes to the unclassified record.

• Clustering: method through which similar records are grouped together in order to give a birds eye view of the business of what is happening within the database.

Trees, networks and rules are among the classified under the next generation techniques. These techniques are the most frequently used over the past two decades of research and can be used for discovering fresh information within large databases or for bulding predictive models.

• Trees: decision tree algorithms tend to automate the whole process of reating hypothesis and validate them in a more complete and integrated manner compared to any other data mining techniques. Trees are proficient in handling raw data with few or no pre-processing and have been applied for problems related to credit card attrition prediction to time series of exchange rate currencies.

• Networks: networks are computer programs that implement the detection of trend and pattern detection learning and machine learning algorithms to build predictive models from large historical databases.

• Rules: one of the key forms of data mining and perhaps may be of the most common for of knowledge discovery. Rule induction bears a resemblance to the process that people think of when they think about data mining, namely "mining", digging for gold through an immense database.

The business world constantly faces situations in which business intelligence plays a key role. Auspiciously, not only IT experts can data mine. As a matter of fact, mining data is made possible with everyday applications such as Microsoft Excel and Microsoft Access to SAS, Cognos, Informatica, among many others.

An industry that is better off or is ought to make use of data mining tools is the banking industry.
Companies want to comprehend the risks they are facing, they want to understand and relate to customers before their competitors do, they want to know what drives their costs, profits; they want to be in the know. And all these can and are done with the right information, the right tools, the right people... in short, data mining.

More and more companies are making use of this booming concept and with reasonable grounds: it can make significant and ample benefits. But what must be kept in mind is that there is a lot more to it than simply purchasing a toolkit.

Getting ahead with Information Technology.

On the sixth day, God created man... and nothing has ever been the same.

Evolution has zipped the human race, the business entity and everything surrounding us to a smaller, yet more intricate, borderless world dominated by constant transformation. To a world where success is temporary, measured by quarterly financial reports and where competition is intense and boundless.

Our data mining class with Mr. Ramon Duremdes Jr. would not be as promising nor would have much significance without the essentials of gaining competitive advantage with Information Technology.
Just the same, should it interest you to read more and/or further, my colleagues, Austin Alip, Miguel Ambrosio, Paolo Barcelon, Deedin Benig, Camille Caleon, Jeffrey Custodio, AV de Jesus, Sesi de la Cruz, Razilee Dizon, Aira Dy, Kesper Gatinao, Gwen Guerrero, Jamie Hao, Ikah Hemedez, Rafael Jouwena, Martin Lomeda, Reuben Mesa, Rinalyn Moreno, Julie Nolasco, Luis Tanjuatco, Charles Tugade, Joseph Woltz, have also put their thoughts and blogged regarding this topic.

It was Charles Darwin who said, it is not the strongest of the species that survive nor the most intelligent, but the one most responsive to change. True enough, all those who fail to tag along run the risk of being left behind, battered by change in the process.

But the ability to respond to change is not enough these days. As Haag, Cummings and Phillips stated in Management Information Systems for the Information Age, it is the information age, a time when knowledge is power. And this has made and can make all the difference.

As human beings, it may perhaps be in our nature to overrate change. Almost certainly, the term disruptive innovations may alarm many of us at first glance. As Clayton Christensen mentioned on Interview on Disruption with CIO's Edward Prewitt, one of the scariest things is it's not yet clear that knowing disruption is happening to you may not make a big difference.

As pessimistic as it may seem to sound, disruptive innovations are nonetheless but products or services that craft wholly untapped, untouched markets. Christian Christensen also mentioned that one must look at disruptive technology as a growth and not as a threat.
Beyond doubt, under whichever circumstances, this is something easier said than done.

In response to the so-called disruptive innovations, the way companies function these days have drastically shifted, specifically in relation to their competitive advantages.

According to Thomas H. Davenport's Competing on Analytics, organizations these days must compete on analytics not because they can but because they should. At a time when firms in many industries offer similar products and use comparable technologies, business processes are among the last remaining points of differentiation.

The following equation may perhaps put all this into simpler, more visual terms:
Information Technology
+ __________ =
Competitive Advantage;
in which we define our variables as:

• Information Technology: any computer-based tool that people use to work with information and support the information and information processing needs of an organization.

• Competitive Advantage: a product or service in way that customers value more than waht the competition is able to do.

• __________: may consist of either, any or all of the following:

- Supply Chain Management system: IT system that facilitates supply chain management activities by automating the tracking of inventory and information amid business processes and between companies.

With a proficient Supply Chain Management system, an organization is able to get most out of its fulfillment by guaranteeing the timely arrival of necessary amount of parts for production or products for sale; logistics, by minimizing costs of transporting materials and safe and dependable delivery; production, by making sure production lines function efficiently; revenue and profit, by ensuring no sales are lost because shelves are empty and costs and price, by sustaining costs and product/service prices at adequate levels.

- Customer Relation Management system: utilizes information about customers in order to have insights into their needs, wants and behaviors in order to provide them a better service.
A well-designed Customer Relation Management system will be able to treat customers better, comprehend their needs, wants and behaviors, adapt to product offerings in response, conduct more effective marketing campaigns, make sure that the sales process is efficiently managed and offer superior after-sale service and support.

- Business Intelligence system: IT applications and tools that support knowledge about a company's customers, competitors, business partners, competitive environment and own internal operations that gives the ability to make effective, important and often strategic business decisions.
A competent Business Intelligence system is able to enhance the timeliness and quality of input to the decision process by providing the company with actionable information and knowledge at the right time, in the right location and in the right form.

- Integrated Collaboration Environments: environment in which teams whose memers are located in aried geographic locations do their work.
A well established Integrated Collaboration Environment can have huge payoffs through the automation of workflows, allowing geographically-challenged team memers to work collaboratively, document management, among others.

As competition toughens in almost just about every industry, companies must build up innovative products, services and business processes in order to stay on course and prosper and that Information Technology is a compelling gizmo to do such.

Having in mind that technology is not a universal remedy, a company must first find certain focus in the context within its goals and strategies. in order to effectively determine where and how to use technology to support major business initiatives.

An article compiled by Ryan Mulcahy of CIO, entitled ABC: An Introduction to Business Intelligence, speaks of companies using Business Intelligence tools, business decisions should be based with facts and hard numbers than only on gut feelings, opinions, conjectures and anecdotes.

In order for a company to truly nurture, organizations require an appropriate focus, a suitable culture, the right people and an apt technology.

The benefits that well-implemented decisions and/or business strategies can go beyond limits.
The effectiveness of such implementations depend on unyielding collaboration amid the business unit and the Information Technology division. Organizations are able to reduce their costs by optimizing resources and enhancing business processes, respond timely and accordingly to their customers’ and their needs by several means. And with all of these under control, an organization is able to focus and innovate on new business ventures.

Within the banking and finance industry, gaining competitive advantage with the use of Information Technology is vital. Being heavy users of Information Technology, companies are aiming to sustain with its clients' expectations by constantly enhancing and integrating innovation to its provided services.

Values being provided to the industry members and its clients are convenience, efficiency, effectiveness, reliability, just to name a few. With Information Technology, alongside the components that may be complemented with it in order to gain competitive advantage significantly diminishes banking hazards, inaccuracies and blunders, in addition to enhancing and augmenting banking experience to endow with superior customer relations.

As Dan Tapscott mentioned in Business Intelligence: Actionable Rights for Business Decision Makers, it makes sense that organizations that choose simple, relevant and agile business intelligence solutions are more likely to sustain competitive advantage in a constantly changing world.

Indeed, the forces of globalization -instant communications, free trade, outsourcing and off-shoring- place premium on the ability to analyze information and make rapid and informed deicions. Simple and relevant business intelligence tools can empower employees to make effective decisions more quickly. By integrating real-time decision-making with mission critical business processes, companies can ensure that they are serious contenders within the innovation-driven world of the 21st century.

All of which are simplified in entire agreement with what Jack Welch once said, an organization's ability to learn and translate that learning into action rapidly, is the ultimate competitive advantage.