What Happens When Municipalities Use Rich Data Mining Against Home Businesses to Collect Tax?

Do you will realize how many Americans run a small home business? The number is staggering, and did you know that 10% of our population is self-employed, and that is something like 30 million Americans. That same 30 million Americans, also represents a group that hires over 65% of our population in their small businesses. Folks that started these little firms might expand their business and eventually hire someone, grow their business larger, actually make it into a real company. I'd say that's a good thing, and it shows that the entrepreneurial spirit in the US is alive and well.

Many people don't seem to be aware of these figures or how important they are. Did you know that 10% of our population is self-employed? Don't worry, you're not the only one who hasn't figured this out, even the President of the United States doesn't understand, or obviously he wouldn't have made that political faux pas telling small business people that they didn't build that, or that they couldn't have built their business had it not been for the government providing such a wonderful civilization and society for them to participate in.

Yes, I was a little miffed when he said that as well, because it isn't true, and I've been self-employed my entire life and I've loved my country my entire adult life as well, as have you. Now then, many municipalities are stretched thin with their budgets. Often they owe 60% of all the money they take in, in legacy cost, that is to say pensions, retirement, and health care for people who have already retired from their city employment. That means only 40% of all the money they take collect taxes actually goes to the current city services.

How can any business, much less a government operate on 40% of its income? It can't, and perhaps that's why three cities in California have filed for bankruptcy, along with a couple of other big bankruptcy municipality cases; Birmingham Alabama and Harrisburg Pennsylvania. With city budgets stretched thin they have no choice but to collect more money, and that means finding more ways to tax more people. Most cities require that if you start a business you have to get a business license, and it is considered a tax.

In some cities these taxes are only a $100 or less depending on the type of business you run, but in other cities they can run as much as $500. Most people that start a small business, especially a little home-based business don't bother to register for their business license. They don't make enough money to even afford that when they first start. But guess what? Soon I am almost positive that all these municipalities will be running rich data mining programs, and/or pay other companies to give them information about anyone who resides in their city was running a business.

They will then of course check this data and all these names against all their business licenses. If you run a business and you don't have a business license but you are doing business online, or it is mentioned on your Facebook page, you will not only have to pay the business license registration fee, you will also be charged with a penalty which could but be two or three times that amount. The cities will then have more revenue to spend by attacking small businesses just barely getting off the ground. Welcome to the future of data mining and your government. Please consider all this and think on it.


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Using Forensic Social Media Data Mining to Discover Work Comp Fraud

As an employer, most of your employee based work comp claims are completely legitimate and should be handled in the best interest of the injured employee. Unfortunately, some are also fraudulent, causing increasing costs on baseless claims. Historically, it's been challenging to contest some of these claims, though recently a new road has opened, allowing enlightened employers to more rapidly travel this road to a truthful outcome.

Employers should now consider the usefulness of Facebook, YouTube, LinkedIn and other social media sites which can contain posts negating the claims of allegedly injured workers participating in activities that are beyond the restrictions placed by the treating physician. These posts can happen on any given day, clearly elucidating a fraudulent claim. For example, let's say that an employee is out of work based on a "work comp" (workers compensation) claim which has restrictions, yet they post links, discussions, comments and photos that are clearly incriminating. This is an area in which companies should be mining regularly to protect your company against out of scope workers compensation claims.

Recently, a transportation attorney based in central Pennsylvania was a guest speaker at an insurance transportation web seminar. His topic was the aggressive defense of trucking lawsuits and he elaborated extensively on an example of forensic social media investigation to assist in the aggressive defense of frivolous lawsuits. I recall that the metrics were impressive; one example noted that a $250,000 claim which was reduced to $2,500 when forensic social media data mining found New Years Eve photos proving the claimant's mobility to be much greater than stipulated in the law suit.

Social media offers a surprising if not inadvertent glimpse into the nuances of the lifestyles of anyone using it, and in certain cases, it also offers important evidence into the veracity of work comp and work comp lawsuit based claims. Employers should be aware of this avenue and investigate accordingly.

The D'Camera Group http://www.dcameragroup.com partners with businesses, creating long range plans to manage their Total Cost of Risk. D'Camera Group's proprietary approach bridges the gap between the client and the insurance marketplace through a series of engagements in which we Discover, Design and Implement a Risk Reduction Plan™. Our specialized business insurance services include risk discovery and assessment, risk reduction strategies, insurance loss management, workers compensation, experience mod factors and improving marketplace competitiveness.


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Data Mining Process - Why Outsource Data Mining Service?

Overview of Data Mining and Process:
Data mining is one of the unique techniques for investigating information to extract certain data patterns and decide to outcome of existing requirements. Data mining is widely use in client research, services analysis, market research and so on. It is totally based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

Information mining is mostly used by financial analyzer, business and professional organization and also there are many growing area of business that are get maximum advantages of data extract with use of data warehouses in their small to large level of businesses.

Most of functionalities which are used in information collecting process define as under:

* Retrieving Data

* Analyzing Data

* Extracting Data

* Transforming Data

* Loading Data

* Managing Databases

Most of small, medium and large levels of businesses are collect huge amount of data or information for analysis and research to develop business. Such kind of large amount will help and makes it much important whenever information or data required.

Why Outsource Data Online Mining Service?

Outsourcing advantages of data mining services:
o Almost save 60% operating cost
o High quality analysis processes ensuring accuracy levels of almost 99.98%
o Guaranteed risk free outsourcing experience ensured by inflexible information security policies and practices
o Get your project done within a quick turnaround time
o You can measure highly skilled and expertise by taking benefits of Free Trial Program.
o Get the gathered information presented in a simple and easy to access format

Thus, data or information mining is very important part of the web research services and it is most useful process. By outsource data extraction and mining service; you can concentrate on your co relative business and growing fast as you desire.

Outsourcing web research is trusted and well known Internet Market research organization having years of experience in BPO (business process outsourcing) field.

If you want to more information about data mining services and related web research services, then contact us.


Source: http://ezinearticles.com/?Data-Mining-Process---Why-Outsource-Data-Mining-Service?&id=3789102

One of the Main Differences Between Statistical Analysis and Data Mining

Two methods of analyzing data that are common in both academic and commercial fields are statistical analysis and data mining. While statistical analysis has a long scientific history, data mining is a more recent method of data analysis that has arisen from Computer Science. In this article I want to give an introduction to these methods and outline what I believe is one of the main differences between the two fields of analysis.

Statistical analysis commonly involves an analyst formulating a hypothesis and then testing the validity of this hypothesis by running statistical tests on data that may have been collected for the purpose. For example, if an analyst was studying the relationship between income level and the ability to get a loan, the analyst may hypothesis that there will be a correlation between income level and the amount of credit someone may qualify for.

The analyst could then test this hypothesis with the use of a data set that contains a number of people along with their income levels and the credit available to them. A test could be run that indicates for example that there may be a high degree of confidence that there is indeed a correlation between income and available credit. The main point here is that the analyst has formulated a hypothesis and then used a statistical test along with a data set to provide evidence in support or against that hypothesis.

Data mining is another area of data analysis that has arisen more recently from computer science that has a number of differences to traditional statistical analysis. Firstly, many data mining techniques are designed to be applied to very large data sets, while statistical analysis techniques are often designed to form evidence in support or against a hypothesis from a more limited set of data.

Probably the mist significant difference here, however, is that data mining techniques are not used so much to form confidence in a hypothesis, but rather extract unknown relationships may be present in the data set. This is probably best illustrated with an example. Rather than in the above case where a statistician may form a hypothesis between income levels and an applicants ability to get a loan, in data mining, there is not typically an initial hypothesis. A data mining analyst may have a large data set on loans that have been given to people along with demographic information of these people such as their income level, their age, any existing debts they have and if they have ever defaulted on a loan before.

A data mining technique may then search through this large data set and extract a previously unknown relationship between income levels, peoples existing debt and their ability to get a loan.

While there are quite a few differences between statistical analysis and data mining, I believe this difference is at the heart of the issue. A lot of statistical analysis is about analyzing data to either form confidence for or against a stated hypothesis while data mining is often more about applying an algorithm to a data set to extract previously unforeseen relationships.


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Data Recovery 101

Almost all computer users have experienced this at least once - the need to get back a deleted /lost data file. This could happen as a result of a software failure, hardware failure, human error, power related problems, damage caused by flood / water, vandalism, virus damage, damage by fire / heat / smoke and sabotage. Whatever the cause and reason that you need data recovery there is no reason to panic, for help is at hand. The need and urgency to recover data has resulted in a plethora of data recovery software to rescue you from a crisis like situation.

Unless the hard disk is not working normally, the need for professional service is almost rendered unnecessary. If the hard disk is not making any weird noise like scratching, scraping or ticking (which means it is in good condition) data recovery can be done with the use of proper data recovery software, without the help of any technical personnel. The data recovery software that is available can be used for Mac, NT/2000/XP and RAID data recovery. The data recovery software is also FAT and MFT compliant.

Hard drive data recovery is possible from small hard drives of 2 GBs to big hard drives of 120 GBs. Hard drive data recovery requires the presence of technicians if there is a hard drive crash.

Data recovery software used for NT data recovery provides recovery of deleted files from the recycle bin, partition recovery from deleted partition or formatted logical drives, from lost folders and performs data recovery even if MFT is severely corrupted. NT data recovery software also recovers emails and all forms of files. Mac data recovery software recovers HFS and HFS+ File System Data. Mac data recovery software also recovers partition if partitions are deleted or formatted, files from Lost or Missing Mac folders. Mac data recovery software recognizes and preserves long file names when recovering Mac files and folders as well as provides full support for IDE, EIDE, SCSI and SATA drives.

'Redundant Array of Inexpensive Disks' or RAIDS offers better data recovery chances as long as the drives are cloned. RAID is a collection of hard disks that act as a single better hard disk than the individual ones. The hard disks of RAID operate independent of each other. A single drive failure is absorbed by RAID and does not result in loss of data. However, when RAID fails, it fails big time and then RAID data recovery software is used to retrieve data. Raid data recovery software recovers both RAID software and hardware.

Natalie Aranda writes about Internet [http://www.rectonet.com/Internet-24/], information technology and computers. Data recovery software used for NT data recovery provides recovery of deleted files from the recycle bin, partition recovery from deleted partition or formatted logical drives, from lost folders and performs data recovery even if MFT is severely corrupted. NT data recovery software also recovers emails and all forms of files. Mac data recovery software recovers HFS and HFS+ File System Data. Mac data recovery software also recovers partition if partitions are deleted or formatted, files from Lost or Missing Mac folders.


Source: http://ezinearticles.com/?Data-Recovery-101&id=149174

Online Data Entry and Data Mining Services

Data entry job involves transcribing a particular type of data into some other form. It can be either online or offline. The input data may include printed documents like Application forms, survey forms, registration forms, handwritten documents etc.

Data entry process is an inevitable part of the job to any organization. One way or other each organization demands data entry. Data entry skills vary depends upon the nature of the job requirement, in some cases data to be entered from a hard copy formats and in some other cases data to be entered directly into a web portal. Online data entry job generally requires the data to be entered in to any online data base.

For a super market, data associate might be required to enter the goods which have sold in a particular day and the new goods received in a particular day to maintain the stock well in order. Also, by doing this the concerned authorities will get an idea about the sale particulars of each commodity as they requires. In another example, an office the account executive might be required to input the day to day expenses in to the online accounting database in order to keep the account well in order.

The aim of the data mining process is to collect the information from reliable online sources as per the requirement of the customer and convert it to a structured format for the further use. The major source of data mining is any of the internet search engine like Google, Yahoo, Bing, AOL, MSN etc. Many search engines such as Google and Bing provide customized results based on the user's activity history. Based on our keyword search, the search engine lists the details of the websites from where we can gather the details as per our requirement.

Collect the data from the online sources such as Company Name, Contact Person, Profile of the Company, Contact Phone Number of Email ID Etc. are doing for the marketing activities. Once the data is gathered from the online sources into a structured format, the marketing authorities will start their marketing promotions by calling or emailing the concerned persons, which may result to create a new customer. So basically data mining is playing a vital role in today's business expansions. By outsourcing the data entry and its related works, you can save the cost that would be incurred in setting up the necessary infrastructure and employee cost.


Source: http://ezinearticles.com/?Online-Data-Entry-and-Data-Mining-Services&id=7713395

Data Mining for Dollars

The more you know, the more you're aware you could be saving. And the deeper you dig, the richer the reward.

That's today's data mining capsulation of your realization: awareness of cost-saving options amid logistical obligations.

According to global trade group Association for Information and Image Management (AIIM), fewer than 25% of organizations in North America and Europe are currently utilizing captured data as part of their business process. With high ease and low cost associated with utilization of their information, this unawareness is shocking. And costly.

Shippers - you're in prime position to benefit the most by data mining and assessing your electronically-captured billing records, by utilizing a freight bill processing provider, to realize and receive significant savings.

Whatever your volume, the more you know about your transportation options, throughout all modes, the easier it is to ship smarter and save. A freight bill processor is able to offer insight capable of saving you 5% - 15% annually on your transportation expenditures.

The University of California - Los Angeles states that data mining is the process of analyzing data from different perspectives and summarizing it into useful information - knowledge that can be used to increase revenue, cuts costs, or both. Data mining software is an analytical tool that allows investigation of data from many different dimensions, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations among dozens of fields in large relational databases. Practically, it leads you to noticeable shipping savings.

Data mining and subsequent reporting of shipping activity will yield discovery of timely, actionable information that empowers you to make the best logistics decisions based on carrier options, along with associated routes, rates and fees. This function also provides a deeper understanding of trends, opportunities, weaknesses and threats. Exploration of pertinent data, in any combination over any time period, enables you the operational and financial view of your functional flow, ultimately providing you significant cost savings.

With data mining, you can create a report based on a radius from a ship point, or identify opportunities for service or modal shifts, providing insight regarding carrier usage by lane, volume, average cost per pound, shipment size and service type. Performance can be measured based on overall shipping expenditures, variances from trends in costs, volumes and accessorial charges.

The easiest way to get into data mining of your transportation information is to form an alliance with a freight bill processor that provides this independent analytical tool, and utilize their unbiased technologies and related abilities to make shipping decisions that'll enable you to ship smarter and save.


Source: http://ezinearticles.com/?Data-Mining-for-Dollars&id=7061178