Sunday, 8 September 2013

Data Conversion Services

Data conversion services have a unique place in this internet driven, fast-growing business world. Whatever be the field - educational, health, legal, research or any other - data conversion services play a crucial role in building and maintaining the records, directories and databases of a system. With this service, firms can convert their files and databases from one format or media to another.

Data conversion services help firms to convert their valuable data and information stored and accumulated in papers into digital format for long-term storage - for the purpose of archiving, easy searching, accessing and sharing.

Now there are many big and small highly competent business process outsourcing (BPO) companies providing a full range of reliable and trustworthy data conversion services to the clients worldwide. Most of these BPO firms are fully equipped with excellent infrastructural facilities and skilled manpower to provide data conversion services catering to the clients' expectations and specifications. These firms can effectively play an important role in improving a company's document/data lifecycle management. With the application of high speed scanners and data processors, these firms can expertly and accurately convert any voluminous and complex data into digital formats, all within the specified time and budget. Moreover, they use state-of-the-art encryption techniques to ensure privacy and security of data transmission over the Internet. The following are the important services offered by the companies in this area:

o Document scanning and conversion
o File format conversion
o XML conversion
o SGML conversion
o CAD conversion
o OCR clean up, ICR, OMR
o Image Conversion
o Book conversion
o HTML conversion
o PDF conversion
o Extracting data from catalog
o Catalog conversion
o Indexing
o Scanning from hard copies, microfilms, microfiche, aperture cards, and large-scale drawings

Thus, by entrusting a data conversion project to an expert outsourcing company, firms can enjoy numerous advantages in terms of quality, efficiency and cost. Some of its key benefits are:

o Avoids paper work
o Cuts down operating expenses and excessive staffing
o Helps to rely on core business activities
o Promotes business as effectively as possible
o Systemizes company's data in simpler format
o Eliminates data redundancy
o Easy accessibility of data at any time

If you are planning to outsource your data conversion work, then you must choose the provider carefully in order to reap the fullest benefits of the services.

Data conversion experts at Managed Outsource Solutions (MOS) provides full conversion services of paper, microfilm, aperture cards, and large-scale drawings, through scanning, indexing, OCR, quality control and export of the archive and books to electronic formats or the final imaging solution. MOS is a US company providing managed outsource solutions that are focused on several industries, including medical, legal, information technology and media.



Source: http://ezinearticles.com/?Data-Conversion-Services&id=1523382

Friday, 6 September 2013

Digging Up Dollars With Data Mining - An Executive's Guide

Introduction

Traditionally, organizations use data tactically - to manage operations. For a competitive edge, strong organizations use data strategically - to expand the business, to improve profitability, to reduce costs, and to market more effectively. Data mining (DM) creates information assets that an organization can leverage to achieve these strategic objectives.

In this article, we address some of the key questions executives have about data mining. These include:

    What is data mining?
    What can it do for my organization?
    How can my organization get started?

Business Definition of Data Mining

Data mining is a new component in an enterprise's decision support system (DSS) architecture. It complements and interlocks with other DSS capabilities such as query and reporting, on-line analytical processing (OLAP), data visualization, and traditional statistical analysis. These other DSS technologies are generally retrospective. They provide reports, tables, and graphs of what happened in the past. A user who knows what she's looking for can answer specific questions like: "How many new accounts were opened in the Midwest region last quarter," "Which stores had the largest change in revenues compared to the same month last year," or "Did we meet our goal of a ten-percent increase in holiday sales?"

We define data mining as "the data-driven discovery and modeling of hidden patterns in large volumes of data." Data mining differs from the retrospective technologies above because it produces models - models that capture and represent the hidden patterns in the data. With it, a user can discover patterns and build models automatically, without knowing exactly what she's looking for. The models are both descriptive and prospective. They address why things happened and what is likely to happen next. A user can pose "what-if" questions to a data-mining model that can not be queried directly from the database or warehouse. Examples include: "What is the expected lifetime value of every customer account," "Which customers are likely to open a money market account," or "Will this customer cancel our service if we introduce fees?"

The information technologies associated with DM are neural networks, genetic algorithms, fuzzy logic, and rule induction. It is outside the scope of this article to elaborate on all of these technologies. Instead, we will focus on business needs and how data mining solutions for these needs can translate into dollars.

Mapping Business Needs to Solutions and Profits

What can data mining do for your organization? In the introduction, we described several strategic opportunities for an organization to use data for advantage: business expansion, profitability, cost reduction, and sales and marketing. Let's consider these opportunities very concretely through several examples where companies successfully applied DM.

Expanding your business: Keystone Financial of Williamsport, PA, wanted to expand their customer base and attract new accounts through a LoanCheck offer. To initiate a loan, a recipient just had to go to a Keystone branch and cash the LoanCheck. Keystone introduced the $5000 LoanCheck by mailing a promotion to existing customers.

The Keystone database tracks about 300 characteristics for each customer. These characteristics include whether the person had already opened loans in the past two years, the number of active credit cards, the balance levels on those cards, and finally whether or not they responded to the $5000 LoanCheck offer. Keystone used data mining to sift through the 300 customer characteristics, find the most significant ones, and build a model of response to the LoanCheck offer. Then, they applied the model to a list of 400,000 prospects obtained from a credit bureau.

By selectively mailing to the best-rated prospects determined by the DM model, Keystone generated $1.6M in additional net income from 12,000 new customers.

Reducing costs: Empire Blue Cross/Blue Shield is New York State's largest health insurer. To compete with other healthcare companies, Empire must provide quality service and minimize costs. Attacking costs in the form of fraud and abuse is a cornerstone of Empire's strategy, and it requires considerable investigative skill as well as sophisticated information technology.

The latter includes a data mining application that profiles each physician in the Empire network based on patient claim records in their database. From the profile, the application detects subtle deviations in physician behavior relative to her/his peer group. These deviations are reported to fraud investigators as a "suspicion index." A physician who performs a high number of procedures per visit, charges 40% more per patient, or sees many patients on the weekend would be flagged immediately from the suspicion index score.

What has this DM effort returned to Empire? In the first three years, they realized fraud-and-abuse savings of $29M, $36M, and $39M respectively.

Improving sales effectiveness and profitability: Pharmaceutical sales representatives have a broad assortment of tools for promoting products to physicians. These tools include clinical literature, product samples, dinner meetings, teleconferences, golf outings, and more. Knowing which promotions will be most effective with which doctors is extremely valuable since wrong decisions can cost the company hundreds of dollars for the sales call and even more in lost revenue.

The reps for a large pharmaceutical company collectively make tens of thousands of sales calls. One drug maker linked six months of promotional activity with corresponding sales figures in a database, which they then used to build a predictive model for each doctor. The data-mining models revealed, for instance, that among six different promotional alternatives, only two had a significant impact on the prescribing behavior of physicians. Using all the knowledge embedded in the data-mining models, the promotional mix for each doctor was customized to maximize ROI.

Although this new program was rolled out just recently, early responses indicate that the drug maker will exceed the $1.4M sales increase originally projected. Given that this increase is generated with no new promotional spending, profits are expected to increase by a similar amount.

Looking back at this set of examples, we must ask, "Why was data mining necessary?" For Keystone, response to the loan offer did not exist in the new credit bureau database of 400,000 potential customers. The model predicted the response given the other available customer characteristics. For Empire, the suspicion index quantified the differences between physician practices and peer (model) behavior. Appropriate physician behavior was a multi-variable aggregate produced by data mining - once again, not available in the database. For the drug maker, the promotion and sales databases contained the historical record of activity. An automated data mining method was necessary to model each doctor and determine the best combination of promotions to increase future sales.

Getting Started

In each case presented above, data mining yielded significant benefits to the business. Some were top-line results that increased revenues or expanded the customer base. Others were bottom-line improvements resulting from cost-savings and enhanced productivity. The natural next question is, "How can my organization get started and begin to realize the competitive advantages of DM?"

In our experience, pilot projects are the most successful vehicles for introducing data mining. A pilot project is a short, well-planned effort to bring DM into an organization. Good pilot projects focus on one very specific business need, and they involve business users up front and throughout the project. The duration of a typical pilot project is one to three months, and it generally requires 4 to 10 people part-time.

The role of the executive in such pilot projects is two-pronged. At the outset, the executive participates in setting the strategic goals and objectives for the project. During the project and prior to roll out, the executive takes part by supervising the measurement and evaluation of results. Lack of executive sponsorship and failure to involve business users are two primary reasons DM initiatives stall or fall short.

In reading this article, perhaps you've developed a vision and want to proceed - to address a pressing business problem by sponsoring a data mining pilot project. Twisting the old adage, we say "just because you should doesn't mean you can." Be aware that a capability assessment needs to be an integral component of a DM pilot project. The assessment takes a critical look at data and data access, personnel and their skills, equipment, and software. Organizations typically underestimate the impact of data mining (and information technology in general) on their people, their processes, and their corporate culture. The pilot project provides a relatively high-reward, low-cost, and low-risk opportunity to quantify the potential impact of DM.

Another stumbling block for an organization is deciding to defer any data mining activity until a data warehouse is built. Our experience indicates that, oftentimes, DM could and should come first. The purpose of the data warehouse is to provide users the opportunity to study customer and market behavior both retrospectively and prospectively. A data mining pilot project can provide important insight into the fields and aggregates that need to be designed into the warehouse to make it really valuable. Further, the cost savings or revenue generation provided by DM can provide bootstrap funding for a data warehouse or related initiatives.

Recapping, in this article we addressed the key questions executives have about data mining - what it is, what the benefits are, and how to get started. Armed with this knowledge, begin with a pilot project. From there, you can continue building the data mining capability in your organization; to expand your business, improve profitability, reduce costs, and market your products more effectively.



Source: http://ezinearticles.com/?Digging-Up-Dollars-With-Data-Mining---An-Executives-Guide&id=6052872

Thursday, 5 September 2013

PDF Scraping - Make Your Files Easily Accessible

What do you mean by PDF Scraping?

PDF Scraping refers to the process of mechanically sorting of information. This information is displayed on the Internet on PDF file and other such documents. The main purpose of this process is to assimilate the desired information into spreadsheets and databases. This process retrieves information from the PDF files and it is done with the help of various tools. It does not violate copyright laws. It retrieves information or contents from the files displayed on the World Wide Web.

Why does most of the information displayed on Internet in PDF format?

Many entrepreneurs are exhibiting their company information on their website in the form of PDF files. These PDF files are secure and portable in nature. A user can have access to this format on any type of system with different configuration. These files are also secure as they have less chances of getting infected from computer virus. The format of PDF files also remains intact on viewing the document. Due to the advantages of PDF document many entrepreneurs display their information on PDF files.

How to use the process of PDF Scraping?

There are various ways to retrieve vital information from the PDF files. PDF Scraping is one of such effective techniques. Information can be saved in PDF format either in the form of text or image. You can use many tools to extract information from such files. The textual information can be retrieved from Adobe's own computer program. You can deploy special tools to extract information from the PDF image files. After the tool finishes scraping the document a user can scan the document searching for desired information. You can then select the information that you want and save it any database or any other file. There are many tools available that can personalize the information that you select. These tools can save the selected data the way you desire. To make the documents in PDF document, use Word to PDF converter software.

What is the importance of PDF Scraping?

The process of PDF Scraping saves plenty of time and energy of a user in collecting vital information from PDF files on the Internet. It reduces the workload of a computer user. This process enables you to concentrate on creating documents like newsletters, contracts, invoices and much more. You can create numerous types of documents easily and swiftly.



Source: http://ezinearticles.com/?PDF-Scraping---Make-Your-Files-Easily-Accessible&id=3211584

Wednesday, 4 September 2013

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.



Source: http://ezinearticles.com/?Preference-to-Offshore-Document-Data-Entry-Services&id=5570327

How Can We Ensure the Accuracy of Data Mining - While Anonymizing the Data?

Okay so, the topic of this question is meaningful and was recently asked in a government publication on Internet Privacy, Smart Phone Personal Data, and Social Online Network Security Features. And indeed, it is a good question, in that we need the bulk raw data for many things such as; planning for IT backbone infrastructure, allotting communication frequencies, tracking flu pandemics, chasing cancer clusters, and for national security, etc, on-and-on, this data is very important.

Still, the question remains; "How Can We Ensure the Accuracy of Data Mining - While Anonymizing the Data?" Well, if you don't collect any data in the first place, you know what you've collected is accurate right? No data collected = No errors! But, that's not exactly what everyone has in mind of course. Now then if you don't have sources for the data points, and if all the data is a anonymized in advance, due to the use of screen names in social networks, then none of the accuracy of any of the data can be taken as truthful.

Okay, but that doesn't mean some of the data isn't correct right? And if you know the percentage of data you cannot trust, you can get better results. How about an example, during the campaign of Barak Obama there were numerous polls in the media, of course, many of the online polls showed a larger percentage, land-slide-like, which never materialized in the actual election; why? Simple, there were folks gaming the system, and because the online crowd, younger group participating was in greater abundance.

Back to the topic; perhaps what's needed is for someone less qualified as a trusted source with their information could be sidelined and identified as a question mark and within or adding to the margin of error. And, if it appears to be fake, a number next to that piece of data, and that identification can then be deleted, when doing the data mining.

Although, perhaps a subsystem could allow for tracing and tracking, but only if it was at the national security level, which could take the information all the way down to the individual ISP and actual user identification. And if data was found to be false, it could merely be red flagged, as unreliable.

The reality is you can't trust sources online, or any of the information that you see online, just like you cannot trust word-for-word the information in the newspapers, or the fact that 95% of all intelligence gathered is junk, the trick is to sift through and find the 5% that is reality based, and realize that even the misinformation, often has clues.

Thus, if the questionable data is flagged prior to anonymizing the data, then you can increase your margin for error without ever having the actual identification of any one-piece of data in the whole bulk of the database or data mine. Margins for error are often cut short, to purport better accuracy, usually to the detriment of the information or the conclusions, solutions, or decisions made from that data.

And then there is the fudge factor, when you are collecting data to prove yourself right? Okay, let's talk about that shall we? You really can't trust data as unbiased if the dissemination, collection, processing, and accounting was done by a human being. Likewise, we also know we cannot trust government data, or projections.

Consider if you will the problems with trusting the OMB numbers and economic data on the financial bill, or the cost of the ObamaCare healthcare bill. Also other economic data has been known to be false, and even the bank stress tests in China, the EU, and the United States is questionable. For instance consumer and investor confidence is very important therefore false data is often put out, or real data is manipulated before it's put on the public. Hey, I am not an anti-government guy, and I realize we need the bureaucracy for some things, but I am wise enough to realize that humans run the government, and there is a lot of power involved, humans like to retain and get more of that power. We can expect that.

And we can expect that folks purporting information under fake screen names, pen names to also be less-than-trustworthy, that's all I am saying here. Look, it's not just the government, corporations do it too as they attempt to put a good spin on their quarterly earnings, balance sheet, move assets around, or give forward looking projections.

Even when we look at the data from the FED's Beige Sheet we could say that most all of that is hearsay, because generally the FED Governors of the various districts do not indicate exactly which of their clients, customers, or friends in industry gave them which pieces of information. Thus we don't know what we can trust, and we thus must assume we can't trust any of it, unless we can identify the source prior to its inclusion in the research, report, or mined data query.

This is nothing new, it's the same for all information, whether we read it in the newspaper or our intelligence industry learns of new details. Check sources and if we don't check the sources in advance, the correct thing to do is to increase the probability that the information is indeed incorrect, and/or the margin for error at some point ends up going hyperbolic on you, thus, you need to throw the whole thing out, but then I ask why collect it in the first place.

Ah hell, this is all just philosophy on the accuracy of data mining. Grab yourself a cup of coffee, think about it and email your comments and questions.




Source: http://ezinearticles.com/?How-Can-We-Ensure-the-Accuracy-of-Data-Mining---While-Anonymizing-the-Data?&id=4868548

Monday, 2 September 2013

Has It Been Done Before? Optimize Your Patent Search Using Patent Scraping Technology

Since the US patent office opened in 1790, inventors across the United States have been submitting all sorts of great products and half-baked ideas to their database. Nowadays, many individuals get ideas for great products only to have the patent office do a patent search and tell them that their ideas have already been patented by someone else! Herin lies a question: How do I perform a patent search to find out if my invention has already been patented before I invest time and money into developing it?

The US patent office patent search database is available to anyone with internet access.

US Patent Search Homepage

Performing a patent search with the patent searching tools on the US Patent office webpage can prove to be a very time consuming process. For example, patent searching the database for "dog" and "food" yields 5745 patent search results. The straight-forward approach to investigating the patent search results for your particular idea is to go through all 5745 results one at a time looking for yours. Get some munchies and settle in, this could take a while! The patent search database sorts results by patent number instead of relevancy. This means that if your idea was recently patented, you will find it near the top but if it wasn't, you could be searching for quite a while. Also, most patent search results have images associated with them. Downloading and displaying these images over the internet can be very time consuming depending on you internet connection and the availability of the patent search database servers.

Because patent searches take such a long time, many companies and organizations are looking ways to improve the process. Some organizations and companies will hire employees for the sole purpose of performing patent searches for them. Others contract out the job to small business that specialize in patent searches. The latest technology for performing patent searches is called patent scraping.

Patent scraping is the process of writing computer automated scripts that analyze a website and copy only the content you are interested in into easily accessible databases or spreadsheets on your computer. Because it is a computerized script performing the patent search, you don't need a separate employee to get the data, you can let it run the patent scraping while you perform other important tasks! Patent scraping technology can also extract text content from images. By saving the images and textual content to your computer, you can then very efficiently search them for content and relevancy; thus saving you lots of time that could be better spent actually inventing something!

To put a real-world face on this, let us consider the pharmaceutical industry. Many different companies are competing for the patent on the next big drug. It has become an indispensible tactic of the industry for one company to perform patent searches for what patents the other companies are applying for, thus learning in which direction the research and development team of the other company is taking them. Using this information, the company can then choose to either pursue that direction heavily, or spin off in a different direction. It would quickly become very costly to maintain a team of researchers dedicated to only performing patent searches all day. Patent scraping technology is the means for figuring out what ideas and technologies are coming about before they make headline news. It is by utilizing patent scraping technology that the large companies stay up to date on the latest trends in technology.

While some companies choose to hire their own programming team to do their patent scraping scripts for them, it is much more cost effective to contract out the job to a qualified team of programmers dedicated to performing such services.



Source: http://ezinearticles.com/?Has-It-Been-Done-Before?-Optimize-Your-Patent-Search-Using-Patent-Scraping-Technology&id=171000

Sunday, 1 September 2013

Data Management Services

In recent studies it has been revealed that any business activity has astonishing huge volumes of data, hence the ideas has to be organized well and can be easily gotten when need arises. Timely and accurate solutions are important in facilitating efficiency in any business activity. With the emerging professional outsourcing and data organizing companies nowadays many services are offered that matches the various kinds of managing the data collected and various business activities. This article looks at some of the benefits that accrue of offered by the professional data mining companies.

Entering of data

These kinds of services are quite significant since they help in converting the data that is needed in high ideal and format that is digitized. In internet some of this data can found that is original and handwritten. In printed paper documents and or text are not likely to contain electronic or needed formats. The best example in this context is books that need to be converted to e-books. In insurance companies they also depend on this process in processing the claims of insurance and at the same time apply to the law firms that offer support to analyze and process legal documents.

EDC

That is referred to as electronic data. This method is mostly used by clinical researchers and other related organization in medical. The electronic data and capture methods are used in the utilization in managing trials and research. The data mining and data management services are given in upcoming databases for studies. The ideas contained can easily be captured, other services being done and the survey taken.

Data changing

This is the process of converting data found in one format to another. Data extraction process often involves mining data from an existing system, formatting it, cleansing it and can be installed to enhance both availability and retrieving of information easily. Extensive testing and application are the requirements of this process. The service offered by data mining companies includes SGML conversion, XML conversion, CAD conversion, HTML conversion, image conversion.

Managing data service

In this service it involves the conversion of documents. It is where one character of a text may need to be converted to another. If we take an example it is easy to change image, video or audio file formats to other applications of the software that can be played or displayed. In indexing and scanning is where the services are mostly offered.

Data extraction and cleansing

Significant information and sequences from huge databases and websites extraction firms use this kind of service. The data harvested is supposed to be in a productive way and should be cleansed to increase the quality. Both manual and automated data cleansing services are offered by data mining organizations. This helps to ensure that there is accuracy, completeness and integrity of data. Also we keep in mind that data mining is never enough.

Web scraping, data extraction services, web extraction, imaging, catalog conversion, web data mining and others are the other management services offered by data mining organization. If your business organization needs such services here is one that can be of great significance that is web scraping and data mining



Source: http://ezinearticles.com/?Data-Management-Services&id=7131758