Data Mining - Techniques and Process of Data Mining

Data mining as the name suggest is extracting informative data from a huge source of information. It is like segregating a drop from the ocean. Here a drop is the most important information essential for your business, and the ocean is the huge database built up by you.

Recognized in Business

Businesses have become too creative, by coming up with new patterns and trends and of behavior through data mining techniques or automated statistical analysis. Once the desired information is found from the huge database it could be used for various applications. If you want to get involved into other functions of your business you should take help of professional data mining services available in the industry

Data Collection

Data collection is the first step required towards a constructive data-mining program. Almost all businesses require collecting data. It is the process of finding important data essential for your business, filtering and preparing it for a data mining outsourcing process. For those who are already have experience to track customer data in a database management system, have probably achieved their destination.

Algorithm selection

You may select one or more data mining algorithms to resolve your problem. You already have database. You may experiment using several techniques. Your selection of algorithm depends upon the problem that you are want to resolve, the data collected, as well as the tools you possess.

Regression Technique

The most well-know and the oldest statistical technique utilized for data mining is regression. Using a numerical dataset, it then further develops a mathematical formula applicable to the data. Here taking your new data use it into existing mathematical formula developed by you and you will get a prediction of future behavior. Now knowing the use is not enough. You will have to learn about its limitations associated with it. This technique works best with continuous quantitative data as age, speed or weight. While working on categorical data as gender, name or color, where order is not significant it better to use another suitable technique.

Classification Technique

There is another technique, called classification analysis technique which is suitable for both, categorical data as well as a mix of categorical and numeric data. Compared to regression technique, classification technique can process a broader range of data, and therefore is popular. Here one can easily interpret output. Here you will get a decision tree requiring a series of binary decisions.



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How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.



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Startling Benefits Of Outsourcing Data Entry Services

It is essential for running the business successfully. Business organizations into insurance, medical, financial, banking, educational, commercial, and social are the most which require help of professional service providers. For proper management of information it is better to take help of professional outsourcing service.

In the current business world there are many companies providing outsourcing service at affordable rates. These companies providing customized solutions provide a wide range of services such as:

• Online/offline data outsourcing
• Image entry
• Copy typing
• Book typing
• Report copy typing
• Document and image processing
• Insurance claim entry
• Medical record entry, etc.

Few benefits of availing outsourcing are as follows:

Competent Services
Companies providing outsourcing services have well trained and experienced work force with updated technology to deliver accurate output in bare minimum time. Companies providing data outsourcing services invest on advanced infrastructure with upgraded technological instruments as well as secured systems, etc. to meet requirements of the clients.

Cutting down cost
Outsourcing your services saves up to 60% cost on total operations of the business. By outsourcing, you may cut down cost of capital incurred during in-house process. Additional benefit of outsourcing is saving cost on resources which could be invested in widening the business activity.

High Return on Investment
Outsourcing fetches standard agreement with the companies to provide maximum return on investment. Thus it is easier for companies to lower down expenditures on resources and improve the competence as well as output. Obviously the company will be yearning great profits on their investments.

Multiple Services
Outsourcing is the collection of connected areas of services which comprises: data processing, data conversion, word conversion, PDF conversion, PDF to DOC conversion, OCR clean up, etc.



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Offline Data Entry - 3 Ways of Offline Data Entry Solution

Your company can get out of critical situation only if you have right information on hand. This is one of the most common problems in most of the organizations. They do not understand the preciousness of the information. There is another barrier that companies are facing such as cost of storing and managing the information.

Offline data entry is the solution for organizing the information. By offline data typing, you can generate digital copy of important paper document. The digital format is very easy to manage. It also requires less storage space. So, offline data typing can solve your problem of storage space, time of management as well as the cost.

Most of the companies require following 3 ways of offline data entry solution:

Entering Information from web: This is related to research. It is merely a copy-past type of task. For instance, medical organization requires the data of doctor such as name, degree, address, phone number and other detail. So, coping from web and pasting in to require application. Generally, organizations are using such service to collect person/company related information. You can outsource detail requirements to some reputed company as offline data entry project.

Entering Information in Software: In this type, you have to provide software of program as well as the paper document. Data typing professional from entry firm will enter the information into your program from the paper document. Such type of task is helpful to generate big database or organizing the lacs of detail.

Entering Information in word, excel and other application: If you have reports or huge documents and want to convert into digital format, this is the way. It is very hard to maintain the same quality of paper year by year. I am sure that the quality will degrade over a period of time. By entering the information in word, excel or other application, you can easily solve such problem.

The payment is the issue for any company. In such type of task companies are charging the money per entry. If you have descriptive offline data entry, they may charge per page or per word. These are the general formats of payment.

One Advice "To avoid scam; please outsource your offline data entry requirement to reputed company only."

Bea Arthur is a quality controller at Data Entry India, a well-known firm, accepting data entry projects, data conversion projects and data processing projects. They are having more than 17 years of experience in offline data entry.


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Top Data Mining Tools

Data mining is important because it means pulling out critical information from vast amounts of data. The key is to find the right tools used for the expressed purposes of examining data from any number of viewpoints and effectively summarize it into a useful data set.

Many of the tools used to organize this data have become computer based and are typically referred to as knowledge discovery tools.

Listed below are the top data mining tools in the industry:

    Insightful Miner - This tool has the best selection of ETL functions of any data mining tool on the market. This allows the merging, appending, sorting and filtering of data.
    SQL Server 2005 Data Mining Add-ins for Office 2007 - These are great add-ins for taking advantage of SQL Server 2005 predictive analytics in Office Excel 2007 and Office Visio 2007. The add-ins Allow you to go through the entire development lifecycle within Excel 2007 by using either a spreadsheet or external data accessible through your SQL Server 2005 Analysis Services instance.
    Rapidminder - Also known as YALE is a pretty comprehensive and arguably world-leading when it comes to an open-source data mining solution. it is widely used from a large number of companies an organizations. Even though it is open-source, this tool, out of the box provides a secure environment and provides enterprise capable support and services so you will not be left out in the cold.

The list is short but ever changing in order to meet the increasing demands of companies to provide useful information from years of data.

TonyRocks.com in Pittsburgh Pennsylvania is one of only a few companies in the region that offer data tools an strategies.

They also keep a nice and updated list of the the latest on new tools in integration strategies for your organization.


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Data Mining Questions? Some Back-Of-The-Envelope Answers

Data mining, the discovery and modeling of hidden patterns in large volumes of data, is becoming a mainstream technology. And yet, for many, the prospect of initiating a data mining (DM) project remains daunting. Chief among the concerns of those considering DM is, "How do I know if data mining is right for my organization?"

A meaningful response to this concern hinges on three underlying questions:

    Economics - Do you have a pressing business/economic need, a "pain" that needs to be addressed immediately?
    Data - Do you have, or can you acquire, sufficient data that are relevant to the business need?
    Performance - Do you need a DM solution to produce a moderate gain in business performance compared to current practice?

By the time you finish reading this article, you will be able to answer these questions for yourself on the back of an envelope. If all answers are yes, data mining is a good fit for your business need. Any no answers indicate areas to focus on before proceeding with DM.

In the following sections, we'll consider each of the above questions in the context of a sales and marketing case study. Since DM applies to a wide spectrum of industries, we will also generalize each of the solution principles.

To begin, suppose that Donna is the VP of Marketing for a trade organization. She is responsible for several trade shows and a large annual meeting. Attendance was good for many years, and she and her staff focused their efforts on creating an excellent meeting experience (program plus venue). Recently, however, there has been declining response to promotions, and a simultaneous decline in attendance. Is data mining right for Donna and her organization?

Economics - Begin with economics - Is there a pressing business need? Donna knows that meeting attendance was down 15% this year. If that trend continues for two more years, turnout will be only about 60% of its previous level (85% x 85% x 85%), and she knows that the annual meeting is not sustainable at that level. It is critical, then, to improve the attendance, but to do so profitably. Yes, Donna has an economic need.

Generally speaking, data mining can address a wide variety of business "pains". If your company is experiencing rapid growth, DM can identify promising new retail locations or find more prospects for your online service. Conversely, if your organization is facing declining sales, DM can improve retention or identify your best existing customers for cross-selling and upselling. It is not advisable, however, to start a data mining effort without explicitly identifying a critical business need. Vast sums have been spent wastefully on mining data for "nuggets" of knowledge that have little or no value to the enterprise.

Data - Next, consider your data assets - Are sufficient, relevant data available? Donna has a spreadsheet that captures several years of meeting registrations (who attended). She also maintains a promotion history (who was sent a meeting invitation) in a simple database. So, information is available about the stimulus (sending invitations) and the response (did/did not attend). This data is clearly relevant to understanding and improving future attendance.

Donna's multi-year registration spreadsheet contains about 10,000 names. The promotion history database is even larger because many invitations are sent for each meeting, both to prior attendees and to prospects who have never attended. Sounds like plenty of data, but to be sure, it is useful to think about the factors that might be predictive of future attendance. Donna consults her intuitive knowledge of the meeting participants and lists four key factors:

    attended previously
    age
    size of company
    industry

To get a reasonable estimate for the amount of data required, we can use the following rule of thumb, developed from many years of experience:

Number of records needed ≥ 60 x 2^N (where N is the number of factors)

Since Donna listed 4 key factors, the above formula estimates that she needs 960 records (60 x 2^4 = 60 x 16). Since she has more than 10,000, we conclude Yes, Donna has relevant and sufficient data for DM.

More generally, in considering your own situation, it is important to have data that represents:

    stimulus and response (what was done and what happened)
    positive and negative outcomes

Simply put, you need data on both what works and what doesn't.

Performance - Finally, performance - Is a moderate improvement required relative to current benchmarks? Donna would like to increase attendance back to its previous level without increasing her promotion costs. She determines that the response rate to promotions needs to increase from 2% to 2.5% to meet her goals. In data mining terms, a moderate improvement is generally in the range of 10% to 100%. Donna's need is in this interval, at 25%. For her, Yes, a moderate performance increase is needed.

The performance question is typically the hardest one to address prior to starting a project. Performance is an outcome of the data mining effort, not a precursor to it. There are no guarantees, but we can use past experience as a guide. As noted for Donna above, incremental-to-moderate improvements are reasonable to expect with data mining. But don't expect DM to produce a miracle.

Conclusion

Summarizing, to determine if data mining fits your organization, you must consider:

    your business need
    your available data assets
    the performance improvement required

In the case study, Donna answered yes to each of the questions posed. She is well-positioned to proceed with a data mining project. You, too, can apply the same thought process before you spend a single dollar on DM. If you decide there is a fit, this preparation will serve you well in talking with your staff, vendors, and consultants who can help you move a data mining project forward.



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The Truth Behind Data Mining Outsourcing Service

We have come to this what we call the information era where industries are craving for useful data needed for decision making, product creations - among other vital uses for business. Data mining and converting them to become useful information is part of this trend which makes businesses to grow to their optimum potentials. However, a lot of companies cannot handle by themselves alone the processes data mining involved as they are just overwhelmed by other important tasks. This is where data mining outsourcing comes into play.

There have been a lot of definitions introduced but it can simply be explained as a process that includes sorting through huge amounts of raw data to be able to extract valuable information needed by industries and businesses in various fields. In most cases, this is done by professionals, business organizations, and financial analysts. There has been a rapid growth in the number of sectors or groups who are getting into it though.

There are a number of reasons why there is a rapid growth in data mining outsourcing service subscriptions. Some of these are presented below:

Wide Array of services included

A lot of companies are turning to data mining outsourcing because it caters a lot of services. Such services include, but not limited to congregation data from websites into database applications, collecting contact information from various websites, extracting data from websites using software, sorting stories from news sources, and accumulating business information from competitors.

A lot of companies are benefiting

A lot of industries are benefiting from it because it is quick and feasible. Information extracted by data mining outsourcing service providers are used in crucial decision-making in the area of direct marketing, e-commerce, customer relation management, health care, scientific test and other experimental endeavor, telecommunications, financial services, and a whole lot more.

Have a lot of advantages

Subscribing for data mining outsourcing service offers many advantages because providers ensure clients of rendering services with global standards. They strive to work with improved technology scalability, advanced infrastructure resources, quick turnaround time, cost-effective prices, more secure network system to ensure information safety, and increased market coverage.

Outsourcing allows companies to concentrate in their core business operations and therefore can improve overall productivity. No wonder why data mining outsourcing has been a prime choice of many businesses - it propels business towards greater profits.


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Effectiveness of Web Data Mining Through Web Research

Web data mining is systematic approach to keyword based and hyperlink based web research for gaining business intelligence. It requires analytical skills to understand hyperlink structure of given website. Hyperlinks possess enormous amount of hidden human annotations that can help automatically understand the authority. If the webmaster provides a hyperlink pointing to another website or web page, this action is perceived as an endorsement to that webpage. Search engines highly focus on such endorsements to define the importance of the page and place them higher in organic search results.

However every hyperlink does not refer to the endorsement since the webmaster may have used it for other purposes, such as navigation or to render paid advertisements. It is important to note that authoritative pages rarely provide informative descriptions. For an instant, Google's homepage may not provide explicit self-description as "Web search engine."

These features of hyperlink systems have forced researchers to evaluate another important webpage category called hubs. A hub is a unique, informative webpage that offers collections of links to authorities. It may have only a few links pointing to other web pages but it links to a collection of prominent sites on a single topic. A hub directly awards authority status on sites that focus on a single topic. Typically, a quality hub points to many quality authorities, and, conversely, a web page that many such hubs link to can be deemed as a superior authority.

Such approach of identifying authoritative pages has resulted in the development of various popularity algorithms such as PageRank. Google uses PageRank algorithm to define authority of each webpage for a relevant search query. By analyzing hyperlink structures and web page content, these search engines can render better-quality search results than term-index engines such as Ask and topic directories such as DMOZ.


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Data Mining: From Moore's Law to One Sale a Day

Today the internet is more customized than it ever has been before. This is largely because of data mining, which involves using patterns and records of how you use the internet, to anticipate how you will continue to use the internet. This is an application of data mining, however; more broadly, the term refers to how to analyze data to cut costs or increase revenue.

While the term data mining is new, the practice is not. Due to Moore's Law, which states that processing power and data storage double every 18 months, over the past five years, it has become significantly easier to access vast stores of data. People are also continuing to use the internet and explore the web at an exponential rate so that the effect of data mining by 2020 will mean that roughly five billion of the world's seven and a half billion people will be affected. After about 2020, integrate circuits will be so advanced and tiny, that many predict Moore's law will be inapplicable to circuitry, but will continue to dictate the conventions of nanotechnology and biochips.

Data mining has more practical examples, too. The products you've bought off Amazon, for example, are analyzed by data miners at that company, to show you similar products that you may be interested in. Applied more widely, a restaurant chain could determine what customers buy and when they visit in order to tailor their menu to fit the tastes of the public at large, as well as to invent and supply new dishes and offer specials. This is called class data mining. A deal of the day site could target its giveaway of the day to a certain segment of the population that visits its site. If it knows that most people visit its site searching for technology-related items, chances are it will offer more of those items instead of a clothing or travel deal of the day. This is called cluster data mining. Association mining is a logical rule followed by supermarkets such that if a customer buys bread and butter, he will is likely to also buy milk.

Data mining involves statistics which determine what customers will buy over the course of thousands and millions of interactions. In effect, this is what makes technology seem smarter. The logical and statistical formulae humans implement make these rules widely applicable and largely sensible. The applications of data mining are various and exciting. In the future, the internet will be that much closer to reading your mind.


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Data Extraction Software Explained in Plain English

Data Extraction Software is designed to automatically collect data from web pages. A lot of money can be made with Data Extraction Software, but there are two types of program - custom made and typical.

Custom made solutions are designed by developers to extract from one particular source and they can't automatically adjust to another. So for example, if we are to create a custom-build data extraction program for website A, it won't work for website B, because they have different structures. Such custom made solutions cost more money than the standard ones, but they are designed for more complicated and unique situations.

Every data extraction program is based on an algorithm that has to be programmed in such a way that it will collect all the needed data from a given website. The reason why data extraction is so popular is that it saves on manual labor which can become expensive when outsourced. Data extraction software automates repetitive operations. For example, if you want to extract just the emails of every user in a given website, then you will have to pay a person to repeat the same steps over and over again like a robot. Those steps will most likely include clicking on the same place, then copying to the clipboard a piece of data that always resides on the same place on the screen.

Data extraction software is based on certain constants. By constants, I mean certain facts about a given program that do not change, no matter what. This is perhaps the only drawback of this type of software. But for the time being, it's the only way. The other way is to use artificial intelligence and make software programs think and make decisions like humans. They would have to adapt to new systems and it's almost unthinkable to consider such complicated solutions unless you are working on a very large scale.

The Bottom line here is that data extraction software is able to automate cycled operations that are otherwise expensive if handled by humans. Although the initial investment of money and time might seem expensive, it's definitely worth it in the long run, because your customized software will do the job in much less time, without the need for any human intervention.

So, if you are working on any task on the Internet, and you feel that task could be automated, then data extraction software maybe the solution you have been looking for.



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Online Data Entry Services

Online data entry services are now commonly used by businesses and these services are generally offered by outsourcing companies with the required standards and specifications. As everything is becoming global, business entities need to manage their valuable and critical data in an accurate and organized manner in order to maintain their competitiveness in the global marketplace. They usually entrust their non core, repetitive and other support tasks to BPO firms who can offer affordable, reliable and trustworthy documentation services online.

Online data entry services have become immensely helpful in all fields where the data needs to be stored, maintained and used for future applications. Today, many firms have partnered with business process outsourcing companies to have an excellent data management system in their facilities. By integrating state-of-the-art technologies, unique processes and skilled data entry specialists, these firms deliver data entry services with accuracy, efficiency and effectiveness. They offer their services through safe and secure online platform. They deliver the final outputs in encrypted FTP upload, CD-R or CD-W or email. Thus, clients are assured that their data or information is free from unauthorized access, copying or downloading.

Business process outsourcing companies specializing in online data entry services offer a wide spectrum of services, tailored to the particular needs of each client. Some of them are listed below:

o Text, numeric or alphanumeric, image or hardcopy date entry
o Data entry from handwritten or printed materials such as books, newspapers, magazines
o Catalog and business card documentation
o E-books and e-magazines
o Data entry from insurance claims and property tax records
o Online listing of yellow pages
o For website content
o Documentation of surveys, questionnaires, company reports and airway bill entries
o Data capture/collection
o Online form processing and submission
o For mailing list/mailing label
o Email mining
o Typing manuscript into MS Word
o Online copying, pasting, editing, sorting, and indexing data
o Online medical and legal data entry
o Data entry of historical data

Outsourcing your documentation task to a BPO firm is a viable and economical choice. You can eliminate tedious and time consuming tasks from your regular routine. As data entry services are developing in tune with the giant leaps in technology, your firm can also utilize these services and stay competitive in the field. Moreover, you can reduce costs, improve productivity and give more importance to core and revenue generating functions.



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Can You Use Data Mining to Determine What Internet Marketing Tactic Works the Best?

Data mining in general is a sequence that analyzes and collects data from people about something that they are already doing. In essence it collects information from people about things that they normally do, for instance you can do a survey on how many people enjoy making money on the internet. In depth you can collect the demographics on how great a marketing method is preforming for other marketers that are using that same method fir there businesses and see if you should get involved with it as well.

You can also use data mining to collect intel on products that are out there in the market, and you can use the results to compare to your products, if you have any. Data mining can be used as a tool that can help you analyze information that you are already accessing, but with this tool you can funnel it in the right direction. This direction is to help depict information that you are going to need to strategically market your business on the internet or maybe target a specific group in which you can generate sales from.

How can a aspiring entrepreneur in the network marketing industry apply data mining in there small business?

First off, for any new marketer entering the industry there is a series of questions that the marketer have to ask in order for he or she can do a synopsis for his niche. Questions marketers can go out and ask in a survey is, What are your interests? Or what do you do for a living? Do you like what you do for a living? He or she can go as far as, Have you ever thought of owning your business? or How many people are interested being financially independent? These question are to basically give the marketer feel for what there niche is looking for, and how he can position the business, in a strategic way.

Many top marketers use data mining to compare tactics to see what would be a smarter way to promote there businesses. I'm sure you've those annoying pop up promotions that are all over the internet, that say " Get paid to do this survey " Well those are marketers out there that are using data mining to get information for there business. Now I'm not saying go out there and begin spamming everyone that comes on your website your products, because at the end of the day, spam is spam, I do not recommend spamming. But I do recommend using data mining to your advantage.

The 7 Figure Networker [http://www.earnwithlouis.com/] Is dedicated to helping struggling and new internet marketers into becoming top earners in the network marketing industry. We provide people with the tools and the cutting edge key strategies to totally dominate the existing competition in internet marketing. Visit us today to learn more


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Data Mining in the 21st Century: Business Intelligence Solutions Extract and Visualize

When you think of the term data mining, what comes to mind? If an image of a mine shaft and miners digging for diamonds or gold comes to mind, you're on the right track. Data mining involves digging for gems or nuggets of information buried deep within data. While the miners of yesteryear used manual labor, modern data minors use business intelligence solutions to extract and make sense of data.

As businesses have become more complex and more reliant on data, the sheer volume of data has exploded. The term "big data" is used to describe the massive amounts of data enterprises must dig through in order to find those golden nuggets. For example, imagine a large retailer with numerous sales promotions, inventory, point of sale systems, and a gift registry. Each of these systems contains useful data that could be mined to make smarter decisions. However, these systems may not be interlinked, making it more difficult to glean any meaningful insights.

Data warehouses are used to extract information from various legacy systems, transform the data into a common format, and load it into a data warehouse. This process is known as ETL (Extract, Transform, and Load). Once the information is standardized and merged, it becomes possible to work with that data.

Originally, all of this behind-the-scenes consolidation took place at predetermined intervals such as once a day, once a week, or even once a month. Intervals were often needed because the databases needed to be offline during these processes. A business running 24/7 simply couldn't afford the down time required to keep the data warehouse stocked with the freshest data. Depending on how often this process took place, the data could be old and no longer relevant. While this may have been fine in the 1980s or 1990s, it's not sufficient in today's fast-paced, interconnected world.

Real-time EFL has since been developed, allowing for continuous, non-invasive data warehousing. While most business intelligence solutions today are capable of mining, extracting, transforming, and loading data continuously without service disruptions, that's not the end of the story. In fact, data mining is just the beginning.

After mining data, what are you going to do with it? You need some form of enterprise reporting in order to make sense of the massive amounts of data coming in. In the past, enterprise reporting required extensive expertise to set up and maintain. Users were typically given a selection of pre-designed reports detailing various data points or functions. While some reports may have had some customization built in, such as user-defined date ranges, customization was limited. If a user needed a special report, it required getting someone from the IT department skilled in reporting to create or modify a report based on the user's needs. This could take weeks - and it often never happened due to the hassles and politics involved.

Fortunately, modern business intelligence solutions have taken enterprise reporting down to the user level. Intuitive controls and dashboards make creating a custom report a simple matter of drag and drop while data visualization tools make the data easy to comprehend. Best of all, these tools can be used on demand, allowing for true, real-time ad hoc enterprise reporting.


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Data Mining As a Process

The data mining process is also known as knowledge discovery. It can be defined as the process of analyzing data from different perspectives and then summarizing the data into useful information in order to improve the revenue and cut the costs. The process enables categorization of data and the summary of the relationships is identified. When viewed in technical terms, the process can be defined as finding correlations or patterns in large relational databases. In this article, we look at how data mining works its innovations, the needed technological infrastructures and the tools such as phone validation.

Data mining is a relatively new term used in the data collection field. The process is very old but has evolved over the time. Companies have been able to use computers to shift over the large amounts of data for many years. The process has been used widely by the marketing firms in conducting market research. Through analysis, it is possible to define the regularity of customers shopping. How the items are bought. It is also possible to collect information needed for the establishment of revenue increase platform. Nowadays, what aides the process is the affordable and easy disk storage, computer processing power and applications developed.

Data extraction is commonly used by the companies that are after maintaining a stronger customer focus no matter where they are engaged. Most companies are engaged in retail, marketing, finance or communication. Through this process, it is possible to determine the different relationships between the varying factors. The varying factors include staffing, product positioning, pricing, social demographics, and market competition.

A data-mining program can be used. It is important note that the data mining applications vary in types. Some of the types include machine learning, statistical, and neural networks. The program is interested in any of the following four types of relationships: clusters (in this case the data is grouped in relation to the consumer preferences or logical relationships), classes (in this the data is stored and finds its use in the location of data in the per-determined groups), sequential patterns (in this case the data is used to estimate the behavioral patterns and patterns), and associations (data is used to identify associations).

In knowledge discovery, there are different levels of data analysis and they include genetic algorithms, artificial neural networks, nearest neighbor method, data visualization, decision trees, and rule induction. The level of analysis used depends on the data that is visualized and the output needed.

Nowadays, data extraction programs are readily available in different sizes from PC platforms, mainframe, and client/server. In the enterprise-wide uses, size ranges from the 10 GB to more than 11 TB. It is important to note that two crucial technological drivers are needed and are query complexity and, database size. When more data is needed to be processed and maintained, then a more powerful system is needed that can handle complex and greater queries.

With the emergence of professional data mining companies, the costs associated with process such as web data extraction, web scraping, web crawling and web data mining have greatly being made affordable.


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Data Mining and Financial Data Analysis

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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