Data Mining Tools - Understanding Data Mining

Data mining basically means pulling out important information from huge volume of data. Data mining tools are used for the purposes of examining the data from various viewpoints and summarizing it into a useful database library. However, lately these tools have become computer based applications in order to handle the growing amount of data. They are also sometimes referred to as knowledge discovery tools.

As a concept, data mining has always existed since the past and manual processes were used as data mining tools. Later with the advent of fast processing computers, analytical software tools, and increased storage capacities automated tools were developed, which drastically improved the accuracy of analysis, data mining speed, and also brought down the costs of operation. These methods of data mining are essentially employed to facilitate following major elements:

    Pull out, convert, and load data to a data warehouse system
    Collect and handle the data in a database system
    Allow the concerned personnel to retrieve the data
    Data analysis
    Data presentation in a format that can be easily interpreted for further decision making

We use these methods of mining data to explore the correlations, associations, and trends in the stored data that are generally based on the following types of relationships:

    Associations - simple relationships between the data
    Clusters - logical correlations are used to categorise the collected data
    Classes - certain predefined groups are drawn out and then data within the stored information is searched based on these groups
    Sequential patterns - this helps to predict a particular behavior based on the trends observed in the stored data

Industries which cater heavily to consumers in retail, financial, entertainment, sports, hospitality and so on rely on these data methods of obtaining fast answers to questions to improve their business. The tools help them to study to the buying patterns of their consumers and hence plan a strategy for the future to improve sales. For e.g. restaurant might want to study the eating habits of their consumers at various times during the day. The data would then help them in deciding on the menu at different times of the day. Data mining tools certainly help a great deal when drawing out business plans, advertising strategies, discount plans, and so on. Some important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required, usability and ease of operation, automation processes, and reporting methods.


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Business Intelligence Data Mining

Data mining can be technically defined as the automated extraction of hidden information from large databases for predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making.

Data mining requires the use of mathematical algorithms and statistical techniques integrated with software tools. The final product is an easy-to-use software package that can be used even by non-mathematicians to effectively analyze the data they have. Data Mining is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, fraud detection, web site personalization, e-commerce, healthcare, customer relationship management, financial services and telecommunications.

Business intelligence data mining is used in market research, industry research, and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. BI uses various technologies like data mining, scorecarding, data warehouses, text mining, decision support systems, executive information systems, management information systems and geographic information systems for analyzing useful information for business decision making.

Business intelligence is a broader arena of decision-making that uses data mining as one of the tools. In fact, the use of data mining in BI makes the data more relevant in application. There are several kinds of data mining: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining, that are all used in business intelligence applications.

Some data mining tools used in BI are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, Gaussian Baves classification, cross-validation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-means and hierarchical clustering, Markov models and so on.


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Enjoy Valuable Advantages of Finding Professional Online Data Entry Services

Outsourcing is eyed as a cost-effective means to make the business cycle run. The market consists of a lot of heartened buyers who have enjoyed the fruits of outsourcing by compensating a trivial sum to online data entry service providers. They have felt that the sum they shelled out to these services is quite insignificant when compared to the work they got completed by doing so. Of late, its effect among corporate people is so huge that even those who did not prefer to outsource their projects have embraced this practice realizing quite a few of the several advantages that it has in store. Online Data Entry Services is subcontracted to a lot of individuals and other smaller business units that take such projects as their prime source of occupation.

Many services are distributed to companies who approach these online data entry service providers. Some of the commonly used services are web research, mortgage research, product entry and lastly data mining and extraction services. Adept professionals are at your service in these service providers as those who run such units strongly believe in deploying a team of skilled professionals to help clients realize results as quick as possible. Moreover, the systems that are up for utilization in these units are technically advanced both in terms of utility and security hence you need not fear for having outsourced some crucial data sheets belonging to your company. These providers value your information as how they treasure you association and hence you need not actually care a lot about the confidentiality of your information.

Business firms can look forward to receiving high-class data entry from the hands of online data entry services that undertake such projects. Some of the below-mentioned points are a short listing of what interests business in subcontracting the work to professionals.

    Keying in the data happens to be the first phase at the end of which the companies get understandable information to make strategic decisions with. What appeared as raw data represented by mere numbers some time ago is a pointer or a guide, at present, to accelerate business progress.
    Systems being used for such processes offer complete protection to the information.
    As chances of obtaining high quality information rises, the company's business executive is expected to arrive at excellent decisions that reflect on the company's better performance in future.
    Turnaround time is considerably shortened.
    Cost-effective approach does hold a lot of substance since it considerably decreases the operational overheads related to data entry services within the business wing of the company itself.

Saving money and time holds a unique advantage and outsourcing of such online data entry services proffers these businesses this distinctive edge. Thriving companies intend to focus on their core operations instead of delving into such non-core activities, which do not weigh as good as other essential industrial operations that they need to look after. Why should one take and put these chores on themselves when some professionals who are capable of delivering effective results can be picked from the outsourcing market.



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Beneficial Data Collection Services

Internet is becoming the biggest source for information gathering. Varieties of search engines are available over the World Wide Web which helps in searching any kind of information easily and quickly. Every business needs relevant data for their decision making for which market research plays a crucial role. One of the services booming very fast is the data collection services. This data mining service helps in gathering relevant data which is hugely needed for your business or personal use.

Traditionally, data collection has been done manually which is not very feasible in case of bulk data requirement. Although people still use manual copying and pasting of data from Web pages or download a complete Web site which is shear wastage of time and effort. Instead, a more reliable and convenient method is automated data collection technique. There is a web scraping techniques that crawls through thousands of web pages for the specified topic and simultaneously incorporates this information into a database, XML file, CSV file, or other custom format for future reference. Few of the most commonly used web data extraction processes are websites which provide you information about the competitor's pricing and featured data; spider is a government portal that helps in extracting the names of citizens for an investigation; websites which have variety of downloadable images.

Aside, there is a more sophisticated method of automated data collection service. Here, you can easily scrape the web site information on daily basis automatically. This method greatly helps you in discovering the latest market trends, customer behavior and the future trends. Few of the major examples of automated data collection solutions are price monitoring information; collection of data of various financial institutions on a daily basis; verification of different reports on a constant basis and use them for taking better and progressive business decisions.

While using these service make sure you use the right procedure. Like when you are retrieving data download it in a spreadsheet so that the analysts can do the comparison and analysis properly. This will also help in getting accurate results in a faster and more refined manner.


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Data Mining and Financial Data Analysis

Introduction:

Most marketers understand the value of collecting financial data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining - technologies and techniques for recognizing and tracking patterns within data - helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs as well as financial need. In this accessible introduction, we provides a business and technological overview of data mining and outlines how, along with sound business processes and complementary technologies, data mining can reinforce and redefine for financial analysis.

Objective:

1. The main objective of mining techniques is to discuss how customized data mining tools should be developed for financial data analysis.

2. Usage pattern, in terms of the purpose can be categories as per the need for financial analysis.

3. Develop a tool for financial analysis through data mining techniques.

Data mining:

Data mining is the procedure for extracting or mining knowledge for the large quantity of data or we can say data mining is "knowledge mining for data" or also we can say Knowledge Discovery in Database (KDD). Means data mining is : data collection , database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in database, such as

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data source may be combined.)

3. Data selection. (Where data relevant to the analysis task are retrieved from the database.)

4. Data transformation. (Where data are transformed or consolidated into forms appropriate for mining by performing summary or aggregation operations, for instance)

5. Data mining. (An essential process where intelligent methods are applied in order to extract data patterns.)

6. Pattern evaluation. (To identify the truly interesting patterns representing knowledge based on some interesting measures.)

7. Knowledge presentation.(Where visualization and knowledge representation techniques are used to present the mined knowledge to the user.)

Data Warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema and which usually resides at a single site.

Text:

Most of the banks and financial institutions offer a wide verity of banking services such as checking, savings, business and individual customer transactions, credit and investment services like mutual funds etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give one analysis known as "Evolution Analysis".

Data evolution analysis is used for the object whose behavior changes over time. Although this may include characterization, discrimination, association, classification, or clustering of time related data, means we can say this evolution analysis is done through the time series data analysis, sequence or periodicity pattern matching and similarity based data analysis.

Data collect from banking and financial sectors are often relatively complete, reliable and high quality, which gives the facility for analysis and data mining. Here we discuss few cases such as,

Eg, 1. Suppose we have stock market data of the last few years available. And we would like to invest in shares of best companies. A data mining study of stock exchange data may identify stock evolution regularities for overall stocks and for the stocks of particular companies. Such regularities may help predict future trends in stock market prices, contributing our decision making regarding stock investments.

Eg, 2. One may like to view the debt and revenue change by month, by region and by other factors along with minimum, maximum, total, average, and other statistical information. Data ware houses, give the facility for comparative analysis and outlier analysis all are play important roles in financial data analysis and mining.

Eg, 3. Loan payment prediction and customer credit analysis are critical to the business of the bank. There are many factors can strongly influence loan payment performance and customer credit rating. Data mining may help identify important factors and eliminate irrelevant one.

Factors related to the risk of loan payments like term of the loan, debt ratio, payment to income ratio, credit history and many more. The banks than decide whose profile shows relatively low risks according to the critical factor analysis.

We can perform the task faster and create a more sophisticated presentation with financial analysis software. These products condense complex data analyses into easy-to-understand graphic presentations. And there's a bonus: Such software can vault our practice to a more advanced business consulting level and help we attract new clients.

To help us find a program that best fits our needs-and our budget-we examined some of the leading packages that represent, by vendors' estimates, more than 90% of the market. Although all the packages are marketed as financial analysis software, they don't all perform every function needed for full-spectrum analyses. It should allow us to provide a unique service to clients.

The Products:

ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-size enterprises and can help make business-planning decisions by modeling the impact of various options. This is accomplished by demonstrating the what-if outcomes of small changes. A roll forward feature prepares budgets or forecast reports in minutes. The program also generates a financial scorecard of key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry by using the Risk Management Association (RMA) database. It also highlights key ratios that need improvement and year-to-year trend analysis. A unique function, Back Calculation, calculates the profit targets or the appropriate asset base to support existing sales and profitability. Its DuPont Model Analysis demonstrates how each ratio affects return on equity.

Financial Analysis CS reviews and compares a client's financial position with business peers or industry standards. It also can compare multiple locations of a single business to determine which are most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then lets them provide aggregated financial indicators of peers or industry standards, showing clients how their businesses compare.

iLumen regularly collects a client's financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client's financial performance with industry peers. The system is Web-based and can monitor a client's performance on a monthly, quarterly and annual basis. The network can upload a trial balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company's performance for the period. Analysis tools are viewed through customized dashboards.

PlanGuru by New Horizon Technologies can generate client-ready integrated balance sheets, income statements and cash-flow statements. The program includes tools for analyzing data, making projections, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and consultant editions. An add-on, called the Business Analyzer, calculates benchmarks.

ProfitCents by Sageworks is Web-based, so it requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also provides a wide variety of businesses analyses for nonprofits and sole proprietorships. The company offers free consulting, training and customer support. It's also available in Spanish.



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Preference to Offshore Document Data Entry Services

A number or business organizations if different industries are seeking competent and precise document data entry services to maintain their business records safe for future references. Document data entry has advanced as a quickly developing and active industry structure almost accept in all major companies of the world. The companies doing businesses these days are undergoing rapid changes and therefore the need for services is becoming all the more crucial.

To get success you need to accomplish more understanding about the market, your business, clients as well as the prevailing factors that influence your business. A considerable amount of document is in one or the other way included in this entire process. These services is helpful in taking crucial decisions for the organization. It also provides you a standard in understanding the current and future business status of your company.

In this information age data-entry from documents and data conversion have become important elements for most business houses. The requirement for document services has reached zenith since companies work on processes like business merger and acquisitions, as well as new technology developments. In such scenarios having access to the right kind of data at the right time is very crucial and that is why companies opt for reliable services.

These services covers a range of professional business oriented activities such as document plus image processing to image editing as well as catalog processing. A few noteworthy examples of from documents include: PDF document indexing, insurance claim entry, online data capture as well as creating new databases. These services are important in industries like insurance companies, banks, government departments and airlines.

Companies such as Offshore and outsource and others offer an entire gamut of first rate data services. Actually, getting services from documents offshore to developing yet competent countries like India has made the process highly economical plus quality driven too.

Business giants around the world have realized multiple advantages associated in Offshore-Data-Entry. Companies not only prosper because of quality services but are also benefited because of better turn around time, maintaining confidentiality of data as well as economic rates.

Though the company works in all form of documents, there are few below mentioned areas where it specializes:

• Document data entry
• Document data entry conversion
• Document data processing
• Document data capture services
• Web data extraction
• Document scanning indexing

Since reputable companies like Offshore Data-Entry hire only well qualified and trained candidates work satisfaction is guaranteed. There are several steps involved in the quality check (QC) process and therefore accuracy level is maintained to 99.995% ensuring that the end result is delivered to the client far beyond his expectation.


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Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

Basic process of CRM data mining includes:
1. Define business goal
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.


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True Data Recovery Horror Stories

When you lose data, you would want to recover it as quickly as possible. Our financial constraints inevitably play a major part in our decisions, and balancing the two factors makes for a difficult decision making process.

However, if you bungle in your choice of data recovery centre, the results can be deadly. Data which was once recoverable can be lost forever, and literally be ground to dust. And if the data is extremely vital, the consequences can be extremely detrimental.

From recoverable to unrecoverable

A customer had a crashed hard disk from his Apple Computer. He sent in the hard disk to a service provider in a well known electronics centre in Singapore. He was then made to believe that the vendor was one of the authorized Apple Service Centre. He was then quoted around S$1500 and also being promised that he would get back the data in 3 day's time.

On the day he went to collect the data, he was told there and then that the data was "suddenly" not recoverable. As soon as the anxious customer asked for more details of the job, he was told that the disk was serviced by an expert and such professionalism should not be doubted. The vendor further told the customer that the laboratory report was only for internal usage and would not be disclosed, not even the name of the "data recovery expert".

The customer then sent the disk to us. Upon evaluation, it immediately confirmed that the disk was serviced in some "carpeted" office as we saw traces of minute carpet fibres on disk platter, not to mention the dust contaminants. The disk read-write head crashed badly and damaged the platter completely. The head crash might have happened before the service or could have been caused by the contamination of data platter. As far as we could see, such work quality is unacceptable. We had to relate the sad findings to the customer.

We were equally puzzled as the Apple Service Centres will normally direct the customers to us for recovery job. We then contacted the Manager in Apple Service Centre and were surprised to learn that there was no authorized Apple Care Centre around that area.

In this case, a hard disk crash had caused the read/write head of the hard disk to crash onto the platter. It scrapes the magnetic material on the platter (which is where your data is written to by the way) off and takes your data along with it. To know more read this article about hard disk crash, which details the occurrences during a hard disk crash)

Data security worries

The cheap alternative is always enticing. However there are consequences which can jeopardise not only the recovery of your data, but also the privacy and confidentiality of your data. And as a long time data recovery service provider, we have seen quite a number of cases which demonstrates the dangers of sending to unscrupulous 'data recovery' companies.

A customer sent in a crashed hard disk to a computer vendor for recovery. However, he was then told that the data was unrecoverable. Urgently in need of the data, the customer then retrieved the disk from the vendor and sent to us.

We finally rescued all data from the damaged disk. We told the good news to the customer who then rushed to our office to review the data. However, upon further checking, the customer realized that all the data recovered was not his. In fact belonged to some one else! The vendor had returned the wrong disk to the customer probably due to poor logistic control. The original damaged disk is now long gone.

The furious customer cannot do anything. Data confidentiality is an issue as not only has he almost certainly lost his data for good, there is a high chance that someone else posses his disk and can recover his data on it.

Hopefully you can understand the importance of choosing a proper data recovery service provider. The wrong choice can lead to disaster as it can affect not only the recoverability of the data but also can lead you to losing data to unwanted hands.

Suhaimi Baruddin is currently employed as a writer, designer,researcher and data recovery engineer at Adroit Data Recovery Centre's laboratory, which is located in Singapore's Science Hub.



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Is Web Scraping Relevant in Today's Business World?

Different techniques and processes have been created and developed over time to collect and analyze data. Web scraping is one of the processes that have hit the business market recently. It is a great process that offers businesses with vast amounts of data from different sources such as websites and databases.

It is good to clear the air and let people know that data scraping is legal process. The main reason is in this case is because the information or data is already available in the internet. It is important to know that it is not a process of stealing information but rather a process of collecting reliable information. Most people have regarded the technique as unsavory behavior. Their main basis of argument is that with time the process will be over flooded and therefore lead to parity in plagiarism.

We can therefore simply define web scraping as a process of collecting data from a wide variety of different websites and databases. The process can be achieved either manually or by the use of software. The rise of data mining companies has led to more use of the web extraction and web crawling process. Other main functions such companies are to process and analyze the data harvested. One of the important aspects about these companies is that they employ experts. The experts are aware of the viable keywords and also the kind of information which can create usable statistic and also the pages that are worth the effort. Therefore the role of data mining companies is not limited to mining of data but also help their clients be able to identify the various relationships and also build the models.

Some of the common methods of web scraping used include web crawling, text gripping, DOM parsing, and expression matching. The latter process can only be achieved through parsers, HTML pages or even semantic annotation. Therefore there are many different ways of scraping the data but most importantly they work towards the same goal. The main objective of using web scraping service is to retrieve and also compile data contained in databases and websites. This is a must process for a business to remain relevant in the business world.

The main questions asked about web scraping touch on relevance. Is the process relevant in the business world? The answer to this question is yes. The fact that it is employed by large companies in the world and has derived many rewards says it all. It is important to note that many people regarded this technology as a plagiarism tool and others consider it as a useful tool that harvests the data required for the business success.

Using of web scraping process to extract data from the internet for competition analysis is highly recommended. If this is the case, then you must be sure to spot any pattern or trend that can work in a given market.



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Data Scraping and Its Software

Have you ever heard of “data scraping?” Data scraping Data scraping technique utilizes technology is a successful businessman who made his fortune and is not new.

Fortunately, modern solution to the problem. Proxy data scraping technology solves this problem by using a proxy IP address. Scrape your details each time you run the program the output of a website, the website will think that it will be a different IP address. Site owners, increased scrap proxy bus services around the world shows a short period of time. They are very limited and boring ways to prevent the script, but more importantly – most of the time, they just do not know they are scraped.

Now the “Proxy data scraping technology project to him,” You may ask yourself: “Do it yourself” solution is not so simple, but unfortunately it requires a bunch of self-is that you should consider. Hire the selected proxy servers hosting providers, but it is pretty pricey option, but it will definitely be a better alternative: dangerous and unreliable (but) free public proxy servers.

It’s pretty easy to find free proxy servers located all over the world use; there are literally thousands of them. But the trick is to find them. Many sites list hundreds of servers; however, open to the work, and the type of protocol, perseverance, trial and error is needed to support teaching. First, the server is in, or what activities are going on somewhere on the server does not know. Calls for a public proxy or sensitive information to be sent are a bad idea.

Tons of information, but the information is difficult to manage and deal with the company. The wrong strategic decision of the company without the right information at the right time at idle and accurate information for decision-makers on the basis of a half. It cannot edit that can help make strategic decisions.

Outsourcing companies provide services tailored to your specifications. It is better to extract financial data collection and harvest product pricing data, real estate data, conduct market research, studies and analyzes on the basis of product research and analysis conducted for the acquisition and can be played to sell produce online database where some of the areas .

Business outsourcing services so that they can be realized reap huge profits. Outsourcing business is profitable. By outsourcing, you can definitely increase your competitive advantage.

Advantages of Outsourcing Data Extraction Services:
1. Advanced Technology Scalability
2. Proficient in English, skilled technical staff
3. Modernization of infrastructure resources
4. Fast turnaround time
5. Cheap Price
6. Secure Network systems to ensure data security
7. Increased market coverage

Screen scraping software

Benefits:

- Most of the complicated things out of the Abstracts. Regular expression, HTTP cookies without knowing anything about screen scraping applications can do some very sophisticated things.

- In order to scale up the place drastically reduces the time required.

- Support for a commercial enterprise.

Disadvantages:

- The learning curve. Each screen scraping application has its own way to go about things. As the core of the application, to explore how this works for a new scripting language learning can be notified.

- Any costs.

- A different approach.


Source: http://phone-service.org/data-scraping-and-its-software/

Importance of Data Mining Services in Business

Data mining is used in re-establishment of hidden information of the data of the algorithms. It helps to extract the useful information starting from the data, which can be useful to make practical interpretations for the decision making.
It can be technically defined as automated extraction of hidden information of great databases for the predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making. Although data mining is a relatively new term, the technology is not. It is thus also known as Knowledge discovery in databases since it grip searching for implied information in large databases.
It is primarily used today by companies with a strong customer focus - retail, financial, communication and marketing organizations. It is having lot of importance because of its huge applicability. It is being used increasingly in business applications for understanding and then predicting valuable data, like consumer buying actions and buying tendency, profiles of customers, industry analysis, etc. It is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, e-commerce, customer relationship management and financial services.

However, the use of some advanced technologies makes it a decision making tool as well. It is used in market research, industry research and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, scientific tests, genetics, financial services and utilities.

Data mining consists of major elements:

    Extract and load operation data onto the data store system.
    Store and manage the data in a multidimensional database system.
    Provide data access to business analysts and information technology professionals.
    Analyze the data by application software.
    Present the data in a useful format, such as a graph or table.

The use of data mining in business makes the data more related in application. There are several kinds of data mining: text mining, web mining, relational databases, graphic data mining, audio mining and video mining, which are all used in business intelligence applications. Data mining software is used to analyze consumer data and trends in banking as well as many other industries.


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