Why Data mining is still a powerful tool to help companies

The ability of Data mining technologies to sift through volumes of data and arrive at predictive information to empower businesses can in no way be undermined. The advent of new techniques and technologies has made the practice more affordable by organizations both big and small. The new technologies have not only helped in reducing the overhead costs of running the data mining exercise, but also simplified the practice making it more accessible for smaller and mid-size companies employ it in their organizational processes. In the current era, information is power and Web Data Mining Technologies are stretching the limits of their capabilities to help organizations acquire that power.

Data Mining Ensures Better Business Decisions

 Organizations usually have access to large databases which store millions of historical data record. Traditional practices of hands-on analysis of patterns and trends of all available data proved to be too cumbersome to be pursued and were soon replaced with shorter and more selective data sets. This caused hidden patterns to remain hidden thus blocking off possibilities for organizations to grow and evolve. However, the advent of Data Mining as a technology that automates the identification of complex patterns in those databases changed all that. Organizations, now, are engaging in a thorough analysis of massive data sets and are moving ahead to extracting meanings and patterns from them. The analysis helps to unlock the hidden patterns and enables organizations to predict future market behavior and be geared with proactive and knowledge driven decisions for the benefit of their business.

Data Mining provides Fraud Detection Capabilities

 Loss in Revenue has definite adverse impacts on a company’s morale. It slackens productivity and slows down their growth. Fraud is one of the common malpractices that eat into the organization’s revenue earning capability. Data Mining helps to prevent this and ensures a steady rise in their revenue graph. Data mining models can be built to predict consumer behavior patterns which help in effectively detecting fraud.

Data Mining Evolves to be Business Focused
 Traditional Data Mining technologies were focused more on algorithms and statistics on delivering results which, though good failed to address the business issues appropriately. The new age data mining technologies, however, have evolved to become business focused. They understand the needs that drive the business and utilize the strong statistical algorithms built into their system to explore, collect, analyze and summarize data that can be made to work for better health of the business.

Data Mining has become more Granular
 As technology evolves, organizations leverage the benefits it generates. Integration of fundamental data mining functionalists into database engines is one such innovation that has helped organizations to thoroughly benefit from its effect. Mining data from within the database instead of Web Data Extraction the data and then analyzing it saves valuable time for the organization. Moreover, as organizations can now drill down into more granular levels of the data therefore there is a higher possibility of ensuring accuracy. Moreover, as data mining software now have a more direct access to the data sets within the database, there is a higher possibility of ensuring a smoother workflow and hence a better performance.

Conclusion
 Data mining, though capable of helping organizations generate good things, however, needs to be used intelligently. It has to be strongly aligned with the organization’s goals and principles in order to ensure appropriate performance that would strengthen the organization adequately.

We are leading Webdatascraping.us company and enough capable to extract website information, review scraping, contact information scraping, business directory scraping, email list scraping etc.

The Great Advantages of Data Extraction Software – Why a Company Needs it?

Data extraction is being a huge problem for large corporate companies and businesses, which needs to be handled technically and safely. There are many different approaches used for data extraction from web and various tools have designed to solve certain problems.

Moreover, algorithms and advanced techniques were also developed for data extraction. In this array, the Data Extraction Software is widely used to extract information from web as designed.

Data Extraction Software:

 This is a program specifically designed to collect and organize the information or data from the website or webpage and reformat them.

Uses of Data Extraction Software:

Data extraction software can be used at various levels including social web and enterprise levels.

Enterprise Level: Data extraction techniques at the enterprise level are used as the prime tool to perform analysis of the data in business process re-engineering, business system and in competitive intelligence system.

Social Web Level: This type of web data extraction techniques is widely used for gathering structured data in large amount that are continuously generated by Web.2.0, online social network users and social media. 

To specify other uses of Data Extraction software:

•     It helps in assembling stats for the business plans
•     It helps to gather data from public or government agencies
•     It helps to collect data for legal needs

Does the Data Extraction Software make Your Job Simple?

The usage of data extraction software has been widely appreciated by many large corporate companies. In this array, here are a few points to favor the usage of the software;

•     Data toolbar consists of web scraping tool to automate the process of web data extraction
•     Point data fields from which the data need to be collected and the tool will do the rest
•     There are no technical skills required to use data tool
•     It is possible to extract a huge number of data records in just a few seconds

Benefits of Data Extraction Software:

This data extraction software benefits many computer users. Here follows a few remarkable benefits of the software;

•     It can extract detailed data like description, name, price, image and more as defined from a website
•     It is possible to create projects in the extractor and extract required information automatically from the site without the user’s interference
•     The process saves huge effort and time
•     It makes extracting data from several websites easy like online auctions, online stores, real estate portal, business directories, shopping portals and more
•     It makes it possible to export extracted data to various formats like Microsoft Excel, HTML, SQL, XML, Microsoft Access, MySQL and more
•     This will allow processing and analyzing data in any custom format

Who majorly Benefits from Data Extraction Software?

Any computer user benefit from this data extraction software, however, it is majorly benefiting users like;

•     Business men to collect market figures, real estate data and product pricing data
•     Book lovers to extract information about titles, authors, images, descriptions prices and more
•     Collectors and hobbyists to extract auction and betting information
•     Journalists to extract article and news from new websites
•     Travelers to extract information about holiday places, vacations, prices, images and more
•     Job seekers to extract information about jobs available, employers and more

Websitedatascraping.com is enough capable to web data scraping, website data scraping, web scraping services, website scraping services, data scraping services, product information scraping and yellowpages data scraping.

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.

If you are interested to know something more on Web Data Mining and other details, you are welcome to the Screen Scraping Technology site.

Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

6 Benefits Associated with Data Mining

Data has been used from time immemorial by various companies to manage their operations.Data is needed by various organizations strategically aimed at expanding their business operations, reduction of costs, improve their marketing force and above all improve profitability. Data mining is aimed at the creation of information assets and uses them to leverage their objectives.

In this article, we discuss some of the common questions asked about the data mining technology. Some of the questions we have addressed include:

•    How can we define data mining?
•    How can data mining affect my organization?
•    How can my business get started with data mining?

Data Mining Defined

Data mining can be regarded as a new concept in the enterprise decision support system, usually abbreviated as DSS. It does more than complementing and interlocking with the DSS capabilities that may involve reporting and query. It can also be used in on-line analytical processing (OLAP), traditional statistical analysis and data visualization. The technology comes up with tables, graphs and reports of the past business history.

We may define data mining as modeling of hidden patterns and discovering data from large volumes of data.It is important to note that data mining is very different from other retrospective technologies because it involves the creation of models. By using this technology, the user can discover patterns and use them to build models without even understanding what you are after. It gives explanation why the past events happened and even predicting what is likely to happen.

Some of the information technologies that can be linked to data mining include neural networks, fuzzy logic, rule induction and genetic algorithms. In this article we do not cover those technologies but focus on how data mining can be used to meet your business needs and you can translate the solutions thereafter into dollars.

Setting Your Business Solutions and Profits

One of the common questions asked about this technology is; what role can data mining play for my organization? At the start of this article we described some of the opportunities that can be associated with the use of data. Some of those benefits include cost reduction, business expansion, sales and marketing and profitability. In the following paragraphs we look into some of the situations where companies have used data mining to their advantage.

Business Expansion

Equity Financial Limited wanted to expand their customer base and also attract new customers. They used the Loan Check offer to meet their objectives. Initiating the loan, a customer had to go to any branch of Equity branch and just cash the loan. Equity introduced a $6000 LoanCheck by just mailing the promotion to their existing customers. The equity database was able to track about 400 characteristics of every customer. The characteristics were about loan history of the customer, their active credit cards, current balance on the credit cards and if they could respond to the loan offer. Equity used data mining to shift through 400 customer features and also finding the significant ones. They used the data and build model based on the response to the Loan Check offer. They then integrated this model to 500,000 potential customers from credit bureau. They then selectively mailed the most potential customers that were determined by the data mining model.At the end of the process they were able to generate a tot
al of $2.1M in extra net income from 15,000 new customers.

Reduction of Operating Costs
Empire is one of the largest insurance companies in the country. In order to compete with other insurance companies, it has to offer quality services and at the same time reducing costs.Therefore it has to attack costs that may in form of fraud and abuse. This demands a considerable investigation skills and use of data management technology. The latter calls for data mining application that can profile every physician in their network based on claims records of every patient in their data warehouse. The application is able to detect subtle deviations on the physician behavior that are linked to her/her peer group. The deviations are then reported to the intelligence and fraud investigators as “suspicion index.” With this effort derived from data mining, the company was able to save $31M, $37M, and $41M in the first three years respectively from frauds.

Sales Effectiveness and Profitability

In this case we look into pharmaceutical sector. Their sales representatives have wide range of assortment tools they use in promoting various products to physicians. Some of the tools include product samples, clinical literature, dinner meetings, golf outings, teleconferences and many more. Therefore getting to know the promotions methods that are ideal for particular physician is of valuable importance and it is likely to cost the company a lot of dollars in sales call and thereby more lost revenue.

Through data mining, a drug maker was able to link eight months of promotional activity based on corresponding sales found in their database. They then used this information to build a predictive model for each physician.The model revealed that for the six promotional alternatives, only three had a significant impact. Then they used the knowledge found in the data mining models and thereby customizing the ROI.

Looking at those two case studies, then ask yourself, was data mining necessary?

Getting Started

All the cases presented above have revealed how data mining was used to yield results to the various businesses. Some of the results led to increased revenue and increased customer base. Others can be regarded as bottom-line improvements that impacted on cost savings and also improved productivity.In the next few paragraphs we try to answer the question; how can my company get started and start realizing the benefits of data mining.

The right time to start your data mining project is now. With the emergence of specialized data mining companies, starting the process has been simplified and the costs greatly reduced. Data mining project can offer important insights into the field and also aggregate the idea of creating a data warehouse.

In this article we have addressed some of the common questions regarding data mining, what are the benefits associated with the process and how a company can get started. Now, with this knowledge your company should start with a pilot project and then continue building a data mining capability in your company; to improve profitability, market your products more effectively, expand your business and also reduce costs.

Source: http://www.loginworks.com/blogs/web-scraping-blogs/255-benefits-associated-with-data-mining/

Data Discovery vs. Data Extraction

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the "details" links within the search results pages to get to the data you're actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.

Source:http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.

If you are interested to know something more on Web Data Mining and other details, you are welcome to the Screen Scraping Technology site.

Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

Why Outsourcing Data Mining Services?

Are huge volumes of raw data waiting to be converted into information that you can use? Your organization's hunt for valuable information ends with valuable data mining, which can help to bring more accuracy and clarity in decision making process.

Nowadays world is information hungry and with Internet offering flexible communication, there is remarkable flow of data. It is significant to make the data available in a readily workable format where it can be of great help to your business. Then filtered data is of considerable use to the organization and efficient this services to increase profits, smooth work flow and ameliorating overall risks.

Data mining is a process that engages sorting through vast amounts of data and seeking out the pertinent information. Most of the instance data mining is conducted by professional, business organizations and financial analysts, although there are many growing fields that are finding the benefits of using in their business.

Data mining is helpful in every decision to make it quick and feasible. The information obtained by it is used for several applications for decision-making relating to direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities.

Data mining services include:

•    Congregation data from websites into excel database

•    Searching & collecting contact information from websites

•    Using software to extract data from websites

•    Extracting and summarizing stories from news sources

•    Gathering information about competitors business

In this globalization era, handling your important data is becoming a headache for many business verticals. Then outsourcing is profitable option for your business. Since all projects are customized to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure can be realized.

Advantages of Outsourcing Data Mining Services:

•    Skilled and qualified technical staff who are proficient in English

•    Improved technology scalability

•    Advanced infrastructure resources

•    Quick turnaround time

•    Cost-effective prices

•    Secure Network systems to ensure data safety

•    Increased market coverage

Outsourcing will help you to focus on your core business operations and thus improve overall productivity. So data mining outsourcing is become wise choice for business. Outsourcing of this services helps businesses to manage their data effectively, which in turn enable them to achieve higher profits.

This article is courtesy of Flori Lee - an executive at Outsourcing Web Research offer high quality and time bound comprehensive range of data mining services at affordable rates. We are specialized in providing data mining services at 60% less data mining rates.

Source: http://ezinearticles.com/?Why-Outsourcing-Data-Mining-Services?&id=3066061

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.

ProfitSystem fx Profit Driver by CCH Tax and Accounting provides a wide range of financial diagnostics and analytics. It provides data in spreadsheet form and can calculate benchmarking against industry standards. The program can track up to 40 periods.

Source: http://ezinearticles.com/?Data-Mining-and-Financial-Data-Analysis&id=2752017