Information About Data Mining

The potential offered by data mining can be included in the category of the processes of the commercial enterprises and looking for information is not a purpose itself, but it is a very useful process if it is transformed into a real action. Thus, enterprises can choose to react to the different situations created by reality, such as the reduction of the number of customers, the loss of certain markets and so on. The next step after making this choice is the proper exploitation of the data, using different algorithms.

Very often, data mining turns out to be a complete failure and not a success, the measures adopted bot always being appropriate for the information obtained. All these elements which are mentioned above lead to the idea that there is a cycle with data mining and that there are four stages when it comes to this process.

First of all, you have to define the commercial possibilities and the data. Then, you have to get information from the existent data collections using data mining techniques, after which you have to make decisions referring to the subsequent actions using the results you obtain. Last but not least, you have to measure your results properly in order to identify other ways of exploiting the data, too. Of course, you should only be looking at the concrete results because the rest of them can meddle with the outcomes and can alter the quality of the ones you should be getting. Therefore, if you take these steps into consideration, you should be properly using data mining in administrating the activity of your company.


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Limitations and Challenges in Effective Web Data Mining

Web data mining and data collection is critical process for many business and market research firms today. Conventional Web data mining techniques involve search engines like Google, Yahoo, AOL, etc and keyword, directory and topic-based searches. Since the Web's existing structure cannot provide high-quality, definite and intelligent information, systematic web data mining may help you get desired business intelligence and relevant data.

Factors that affect the effectiveness of keyword-based searches include:
• Use of general or broad keywords on search engines result in millions of web pages, many of which are totally irrelevant.
• Similar or multi-variant keyword semantics my return ambiguous results. For an instant word panther could be an animal, sports accessory or movie name.
• It is quite possible that you may miss many highly relevant web pages that do not directly include the searched keyword.

The most important factor that prohibits deep web access is the effectiveness of search engine crawlers. Modern search engine crawlers or bot can not access the entire web due to bandwidth limitations. There are thousands of internet databases that can offer high-quality, editor scanned and well-maintained information, but are not accessed by the crawlers.

Almost all search engines have limited options for keyword query combination. For example Google and Yahoo provide option like phrase match or exact match to limit search results. It demands for more efforts and time to get most relevant information. Since human behavior and choices change over time, a web page needs to be updated more frequently to reflect these trends. Also, there is limited space for multi-dimensional web data mining since existing information search rely heavily on keyword-based indices, not the real data.

Above mentioned limitations and challenges have resulted in a quest for efficiently and effectively discover and use Web resources. Send us any of your queries regarding Web Data mining processes to explore the topic in more detail.



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Data Entry Services Help Your Business Flow Smoothly

A business comes into existence with the sole motive of earning profits and a business owner will take all steps within his means to ensure that work keeps on flowing smoothly and the optimum utilization of resources takes place. Every division in the organization is created with the objective of catalyzing the growth and not causing a hindrance to the progress of the business. Hence it is important to consider each division carefully and analyze if any further optimization can be undertaken at any level. The finance division of a business is one of the most crucial aspects of any organization. It is responsible for maintaining a check and keeping a record of each and every transaction that takes place in the day to day running of the business by data entry services provided by professionals or in-house accounts personnel. This ensures that necessary information regarding the plans; strategies and policies of the organization are available at a moment's notice to facilitate decision-making by the senior management.

Data entry services by professionals appointed for this task play a crucial role in running a business successfully. It makes a major difference in the performance standards of any business. Outsourcing a competent firm for providing your business with data entry services helps you in optimization of resources that were earlier being invested in the accounts department to take care of this crucial need of the business. Data entry services provided by experienced professionals help your business to save time and money and help the organization to increase the pace of regular business activities. The other competitive advantage provided by the data entry services include the ready availability of accurate and authentic at any given point that helps to facilitate decision making for profit creation and expansion of the business. Accurate data maintained on a daily basis and transferred online to the organization help the business to keep track of each expense incurred and profit gained thereby enabling the business to chart out the next course of action.

Data entry services are provided by professionally competent firms who hire experienced individuals to cater to the requirements of every individual client. The data entry services are usually provided round the clock to ensure that the client does not have to wait or face delays when the data is urgently required. The data entry services are provided by vendors who have years of experience, advanced technology and software to carry out the work and required flexibility to accommodate the needs of the client. It is therefore a viable option for any business irrespective of whether it is small or a big corporation. Data entry services, though not complex in nature, but are highly time consuming and this is the prime reason why companies need to outsource this service to cut down on the cost spend on hiring data entry professionals on the company payroll. The data entry services provided by a reputed vendor will ensure that you have highly accurate data properly accumulated for your reference while the confidentiality of your data is also assured. Hence outsourcing data entry services might be the best option for any business in this competitive world.



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Optimizing Your Business With A Virtual Assistant - Data Entry

The term 'data entry' is not one that gets heads craning when you drop it in conversation at a party, but did you know that this under valued (and under-utilised!) clerical duty can add some real power to the marketing campaigns and performance measures used by your business?

Database? What Database?

When someone mentions a database it often conjures up an image of an expensive, customized software program with all the bells and whistles. While these programs are terrific if you have them, they can be really expensive to purchase and implement. If you have an immediate need for a database, your Virtual Assistant can develop one utilizing your current office software, such as Excel or Access. Most people don't realize that even Excel can provide you with many functions that make for a user friendly, flexible database, which anybody can enter data into and manipulate.

How Much Data Is Too Much Data?

I find that it is usually best to put a little more information in than you think you will need. While you have your Virtual Assistant entering the data, it would be prudent to add a couple of seconds to each entry with those few extra snippets of information, rather than dredge out the files all over again and go through the whole database once more. For example, if you are creating a customer database that will be used mainly for mail merges, it would be a good idea to add some extra fields such as 'Marketing Campaign' (data on what marketing strategy lead them to you, i.e. Yellow Pages, Google, print media, radio, etc), or 'Date of Birth' (allowing you to form a demographic of your clients at a later stage, or to contact them on their birthday). The old saying holds true "an ounce of prevention is better than a pound of cure".

Data From Unlikely Places

If you are thinking about having a database created, you probably already have the pile of paperwork waiting to be entered. But sometimes it can be a good idea to think outside the square as to where your data will come from. We all have a stack of business cards that lie around our office or home collecting dust. We collect them from seminars, expos, business networking opportunities, and so on. There is a tremendous amount of information, potential leads, customers and resources waiting to be put to good use! Recently, a client who owns a restaurant gave me a large amount of business cards with which to create a database.

We have all been to restaurants and cafes where they have the large glass bowl filled with business cards and they draw out 1 lucky person per month. Deep down we all realize they are not doing this simply to be generous, but are collecting a customer base. But how many of you have actually gone on to receive correspondence from the restaurant after leaving your card? Not many I imagine! Here is a huge marketing opportunity gone begging; restaurants not usually having clerical staff simply don't have someone to create and maintain a database - another great reason to use a Virtual Assistant! However your data is stored (scraps of paper, enquiry sheets, newsletter sign-up sheets, order forms, etc) you can give your Virtual Assistant that pile of paper work and they can turn it into a database that works for you.

Tending The Database Garden

It is an absolute joy to stand back and look at a garden after a wonderful landscaping job has been completed. But, how long will it stay a joy if nobody tends it? Think of your database as this beautiful garden. You have spent good money having a database designed, created and filled with information, but if it is not kept current, new clients not added and data fields added/changed to reflect your changing business needs, it tends to lose its gloss and usefulness. Why not put a plan in place that ensures regular maintenance of your database - your Virtual Assistant can perform updates and maintenance at planned, regular intervals. This will keep you in control and on top of your business.

Claire Dening is a Virtual Assistant and Office Support Specialist, offering professional assistance on demand, to Entrepreneurs and Businesses worldwide.



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

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.


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Understanding Data Mining

Well begun is half done. We can say that the invention of Internet is the greatest invention of the century which allows for quick information retrieval. It also has negative aspects, as it is an open forum therefore differentiating facts from fiction seems tough. It is the objective of every researcher to know how to perform mining of data on the Internet for accuracy of data. There are a number of search engines that provide powerful search results.

Knowing File Extensions in Data Mining

For mining data the first thing is important to know file extensions. Sites ending with dot-com are either commercial or sales sites. Since sales is involved there is a possibility that the collected information is inaccurate. Sites ending with dot-gov are of government departments, and these sites are reviewed by professionals. Sites ending with dot-org are generally for non-profit organizations. There is a possibility that the information is not accurate. Sites ending with dot-edu are of educational institutions, where the information is sourced by professionals. If you do not have an understanding you may take help of professional data mining services.

Knowing Search Engine Limitations for Data Mining

Second step is to understand when performing data mining is that majority search engines have filtering, file extension, or parameter. These are restrictions to be typed after your search term, for example: if you key in "marketing" and click "search," every site will be listed from dot-com sites having the term "marketing" on its website. If you key in "marketing site.gov," (without the quotation marks) only government department sites will be listed. If you key in "marketing site:.org" only non-profit organizations in marketing will be listed. However, if you key in "marketing site:.edu" only educational sites in marketing will be displayed. Depending on the kind of data that you want to mine after your search term you will have to enter "site.xxx", where xxx will being replaced by.com,.gov,.org or.edu.

Advanced Parameters in Data Mining

When performing data mining it is crucial to understand far beyond file extension that it is even possible to search particular terms, for example: if you are data mining for structural engineer's association of California and you key in "association of California" without quotation marks the search engine will display hundreds of sites having "association" and "California" in their search keywords. If you key in "association of California" with quotation marks, the search engine will display only sites having exactly the phrase "association of California" within the text. If you type in "association of California" site:.com, the search engine will display only sites having "association of California" in the text, from only business organizations.

If you find it difficult it is better to outsource data mining to companies like Online Web Research Services


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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 Mining And Importance to Achieve Competitive Edge in Business

What is data mining? And why it is so much importance in business? These are simple yet complicated questions to be answered, below is brief information to help understanding data and web mining services.

Mining of data in general terms can be elaborated as retrieving useful information or knowledge for further process of analyzing from various perspectives and summarizing in valuable information to be used for increasing revenue, cut cost, to gather competitive information on business or product. And data abstraction finds a great importance in business world as it help business to harness the power of accurate information thus providing competitive edge in business. May business firms and companies have their own warehouse to help them collect, organize and mine information such as transactional data, purchase data etc.

But to have a mining services and warehouse at premises is not affordable and not very cost effective to solution for reliable information solutions. But as if taking out of information is the need for every business now days. Many companies are providing accurate and effective data and web data mining solutions at reasonable price.

Outsourcing information abstraction services are offered at affordable rates and it is available for wide range of data mine solutions:

• taking out business data
• service to gather data sets
• digging information of datasets
• Website data mining
• stock market information
• Statistical information
• Information classification
• Information regression
• Structured data analysis
• Online mining of data to gather product details
• to gather prices
• to gather product specifications
• to gather images

Outsource web mining solutions and data gathering solutions has been effective in terms of cost cutting, increasing productivity at affordable rates. Benefits of data mining services include:

• clear customer, service or product understanding
• less or minimal marketing cost
• exact information on sales, transactions
• detection of beneficial patterns
• minimizing risk and increased ROI
• new market detection
• Understanding clear business problems and goals

Accurate data mining solutions could prove to be an effective way to cut down cost by concentrating on right place.


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Business Intelligence & Data Warehousing in a Business Perspective

Business Intelligence

Business Intelligence has become a very important activity in the business arena irrespective of the domain due to the fact that managers need to analyze comprehensively in order to face the challenges.

Data sourcing, data analysing, extracting the correct information for a given criteria, assessing the risks and finally supporting the decision making process are the main components of BI.

In a business perspective, core stakeholders need to be well aware of all the above stages and be crystal clear on expectations. The person, who is being assigned with the role of Business Analyst (BA) for the BI initiative either from the BI solution providers' side or the company itself, needs to take the full responsibility on assuring that all the above steps are correctly being carried out, in a way that it would ultimately give the business the expected leverage. The management, who will be the users of the BI solution, and the business stakeholders, need to communicate with the BA correctly and elaborately on their expectations and help him throughout the process.

Data sourcing is an initial yet crucial step that would have a direct impact on the system where extracting information from multiple sources of data has to be carried out. The data may be on text documents such as memos, reports, email messages, and it may be on the formats such as photographs, images, sounds, and they can be on more computer oriented sources like databases, formatted tables, web pages and URL lists. The key to data sourcing is to obtain the information in electronic form. Therefore, typically scanners, digital cameras, database queries, web searches, computer file access etc, would play significant roles. In a business perspective, emphasis should be placed on the identification of the correct relevant data sources, the granularity of the data to be extracted, possibility of data being extracted from identified sources and the confirmation that only correct and accurate data is extracted and passed on to the data analysis stage of the BI process.
Business oriented stake holders guided by the BA need to put in lot of thought during the analyzing stage as well, which is the second phase. Synthesizing useful knowledge from collections of data should be done in an analytical way using the in-depth business knowledge whilst estimating current trends, integrating and summarizing disparate information, validating models of understanding, and predicting missing information or future trends. This process of data analysis is also called data mining or knowledge discovery. Probability theory, statistical analysis methods, operational research and artificial intelligence are the tools to be used within this stage. It is not expected that business oriented stake holders (including the BA) are experts of all the above theoretical concepts and application methodologies, but they need to be able to guide the relevant resources in order to achieve the ultimate expectations of BI, which they know best.

Identifying relevant criteria, conditions and parameters of report generation is solely based on business requirements, which need to be well communicated by the users and correctly captured by the BA. Ultimately, correct decision support will be facilitated through the BI initiative and it aims to provide warnings on important events, such as takeovers, market changes, and poor staff performance, so that preventative steps could be taken. It seeks to help analyze and make better business decisions, to improve sales or customer satisfaction or staff morale. It presents the information that manager's need, as and when they need it.

In a business sense, BI should go several steps forward bypassing the mere conventional reporting, which should explain "what has happened?" through baseline metrics. The value addition will be higher if it can produce descriptive metrics, which will explain "why has it happened?" and the value added to the business will be much higher if predictive metrics could be provided to explain "what will happen?" Therefore, when providing a BI solution, it is important to think in these additional value adding lines.

Data warehousing

In the context of BI, data warehousing (DW) is also a critical resource to be implemented to maximize the effectiveness of the BI process. BI and DW are two terminologies that go in line. It has come to a level where a true BI system is ineffective without a powerful DW, in order to understand the reality behind this statement, it's important to have an insight in to what DW really is.

A data warehouse is one large data store for the business in concern which has integrated, time variant, non volatile collection of data in support of management's decision making process. It will mainly have transactional data which would facilitate effective querying, analyzing and report generation, which in turn would give the management the required level of information for the decision making.

The reasons to have BI together with DW

At this point, it should be made clear why a BI tool is more effective with a powerful DW. To query, analyze and generate worthy reports, the systems should have information available. Importantly, transactional information such as sales data, human resources data etc. are available normally in different applications of the enterprise, which would obviously be physically held in different databases. Therefore, data is not at one particular place, hence making it very difficult to generate intelligent information. The level of reports expected today, are not merely independent for each department, but managers today want to analyze data and relationships across the enterprise so that their BI process is effective. Therefore, having data coming from all the sources to one location in the form of a data warehouse is crucial for the success of the BI initiative. In a business viewpoint, this message should be passed and sold to the managements of enterprises so that they understand the value of the investment. Once invested, its gains could be achieved over several years, in turn marking a high ROI.

Investment costs for a DW in the short term may look quite high, but it's important to re-iterate that the gains are much higher and it will span over many years to come. It also reduces future development cost since with the DW any requested report or view could be easily facilitated. However, it is important to find the right business sponsor for the project. He or she needs to communicate regularly with executives to ensure that they understand the value of what's being built. Business sponsors need to be decisive, take an enterprise-wide perspective and have the authority to enforce their decisions.

Process

Implementation of a DW itself overlaps with some phases of the above explained BI process and it's important to note that in a process standpoint, DW falls in to the first few phases of the entire BI initiative. Gaining highly valuable information out of DW is the latter part of the BI process. This can be done in many ways. DW can be used as the data repository of application servers that run decision support systems, management Information Systems, Expert systems etc., through them, intelligent information could be achieved. But one of the latest strategies is to build cubes out of the DW and allow users to analyze data in multiple dimensions, and also provide with powerful analytical supporting such as drill down information in to granular levels. Cube is a concept that is different to the traditional relational 2-dimensional tabular view, and it has multiple dimensions, allowing a manager to analyze data based on multiple factors, and not just two factors. On the other hand, it allows the user to select whatever the dimension he wish to choose for analyzing purposes and not be limited by one fixed view of data, which is called as slice & dice in DW terminology.

BI for a serious enterprise is not just a phase of a computerization process, but it is one of the major strategies behind the entire organizational drivers. Therefore management should sit down and build up a BI strategy for the company and identify the information they require in each business direction within the enterprise. Given this, BA needs to analyze the organizational data sources in order to build up the most effective DW which would help the strategized BI process.

High level Ideas on Implementation

At the heart of the data warehousing process is the extract, transform, and load (ETL) process. Implementation of this merely is a technical concern but it's a business concern to make sure it is designed in such a way that it ultimately helps to satisfy the business requirements. This process is responsible for connecting to and extracting data from one or more transactional systems (source systems), transforming it according to the business rules defined through the business objectives, and loading it into the all important data model. It is at this point where data quality should be gained. Of the many responsibilities of the data warehouse, the ETL process represents a significant portion of all the moving parts of the warehousing process.

Creation of a powerful DW depends on the correctness of data modeling, which is the responsibility of the database architect of the project, but BA needs to play a pivotal role providing him with correct data sources, data requirements and most importantly business dimensions. Business Dimensional modeling is a special method used for DW projects and this normally should be carried out by the BA and from there onwards technical experts should take up the work. Dimensions are perspectives specific to a business that could be used for analysis purposes. As an example, for a sales database, the dimensions could include Product, Time, Store, etc. Obviously these dimensions differ from one business to another and hence for each DW initiative those dimensions should be correctly identified and that could be very well done by a person who has experience in the DW domain and understands the business as well, making it apparent that DW BA is the person responsible.

Each of the identified dimensions would be turned in to a dimension table at the implementation phase, and the objective of the above explained ETL process is to fill up these dimension tables, which in turn will be taken to the level of the DW after performing some more database activities based on a strong underlying data model. Implementation details are not important for a business stakeholder but being aware of high level process to this level is important so that they are also on the same pitch as that of the developers and can confirm that developers are actually doing what they are supposed to do and would ultimately deliver what they are supposed to deliver.

Security is also vital in this regard, since this entire effort deals with highly sensitive information and identification of access right to specific people to specific information should be correctly identified and captured at the requirements analysis stage.

Advantages

There are so many advantages of BI system. More presentation of analytics directly to the customer or supply chain partner will be possible. Customer scores, customer campaigns and new product bundles can all be produced from analytic structures resulting in high customer retention and creation of unique products. More collaboration within information can be achieved from effective BI. Rather than middle managers getting great reports and making their own areas look good, information will be conveyed into other functions and rapidly shared to create collaborative decisions increasing the efficiency and accuracy. The return on human capital will be greatly increased.

Managers at all levels will save their time on data analysis, and hence saving money for the enterprise, as the time of managers is equal to money in a financial perspective. Since powerful BI would enable monitoring internal processes of the enterprises more closely and allow making them more efficient, the overall success of the organization would automatically grow. All these would help to derive a high ROI on BI together with a strong DW. It is a common experience to notice very high ROI figures on such implementations, and it is also important to note that there are many non-measurable gains whilst we consider most of the measurable gains for the ROI calculation. However, at a stage where it is intended to take the management buy-in for the BI initiative, it's important to convert all the non measurable gains in to monitory values as much as possible, for example, saving of managers time can be converted in to a monitory value using his compensation.

The author has knowledge in both Business and IT. Started career as a Software Engineer and moved to work in the business analysis area of a premier US based software company.


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Data Mining: Its Description and Uses

Data mining also known as the process of analyzing the KDD which stands for Knowledge Discovery in Databases is a part of statistics and computer science. It is a process which aims to find out many various patterns in enormous sets of relational data.

It uses ways at the fields of machine learning, database systems, artificial intelligence, and statistics. It permits users to examine data from many various perspectives, sort it, and summarize the identified relationships.

In general, the objective of data mining process is to obtain info out of a data set and convert it into a comprehensible outline. Also, it includes the following: data processing, data management and database aspects, visualization, complexity considerations, online updating, inference and model considerations, and interestingness metrics.

On the other hand, the actual data mining assignment is the semi-automatic or automatic exploration of huge quantities of information to extract patterns that are interesting and previously unknown. Such patterns can be the unusual records or the anomaly detection, data records groups or the cluster analysis, and the dependencies or the association rule mining. Usually, this involves utilizing database methods like spatial indexes. Such patters could be perceived as a type of summary of input data, and could be used in further examination or, for example, in predictive analysis and machine learning.

Today, data mining is utilized by different consumer-focused companies like those in the financial, retails, marketing, and communications fields. It permits such companies to find out relationships among the internal aspects like staff skills, price, product positioning, and external aspects like customer information, competition, and economic indicators. Additionally, it allows them to define the effect on corporate profits, sales, and customer satisfaction; and dig into the summary information to be able to see transactional data in detail.

With data mining process, a retailer can make use of point-of-scale customer purchases records to send promotions based on the purchase history of a client. The retailer can improve products and campaigns or promotions that can be appealing to a definite customer group by using mining data from comment cards.

Generally, any of the following relationships are obtained.

1. Associations: Data could be mined to recognize associations.
2. Clusters: Data are sorted based on a rational relationships or consumer preferences.
3. Sequential Patters: Data is mined to expect patterns and trends in behavior.
4. Classes: Data that are stored are utilized to trace data in predetermined segments.


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Web Mining - Applying Data Techniques

Web mining refers to applying data techniques that discover patterns that are usually on the web. Web mining comes in three different types: content mining, structure mining and usage mining, each and every technique has its significance and roles it will depend on which company someone is.

Web usage mining

Web usage mining mainly deals with what users are mainly searching on the web. It can be either multimedia data or textual data. This process mainly deals with searching and accessing information from the web and putting the information into a one document so that it can be easily be processed.

Web structure mining

Here one uses graphs and by using graphs one can be able to analyze the structure and node of different websites how they are connected to each other. Web structure mining usually comes in two different ways:

One can be able to extract patterns from hyperlinks on different websites.

One can be able to analyze information and page structures which will describe XML and HTML usage. By doing web structure mining one can be able to know more about java script and more basic knowledge about web design.

Advantages

Web mining has many advantages which usually make technology very attractive and many government agencies and corporations use it. Predictive analysis ones does not need a lot of knowledge like in mining. Predictive analytics usually analyze historical facts and current facts about the future events. This type of mining has really helped ecommerce one can be able to do personalize marketing which later yield results in high trade volumes.

Government institutions use mining tools to fight against terrorism and to classify threat. This helps in identifying criminals who are in the country. In most companies is also applicable better services and customer relationship is usually applied it gives them what they need. By doing this companies will be able to understand the needs of customers better and later react to their needs very quickly. By doing this companies will be able to attract and retain customers and also save on production cost and utilize the insight of their customer requirements. They may even find a customer and later provide the customer with promotional offers to the customer so that they can reduce the risk of losing the customer.

Disadvantages

The worst thing that is a threat to mining is invasion of privacy. Privacy in is usually considered lost when documents of one person is obtained, disseminated or used especially when it occurs without the presence of the person who came up with the data itself. Companies collect data for various reasons and purposes. Predictive analytics is usually an area that deals mainly with statistical analysis. Predictive analytics work in different ways deal with extracting information from the data that is being used and it will predict the future trends and the behavior patterns. It is vital for one to note that that accuracy will depend on the level of the business and the data understanding of the personal user.



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How Data Entry Outsourcing Can Benefit You

The debates on outsourcing go on, and though opponents come down heavy on it, the benefits are too many to be ignored. Data entry is a task that is widely outsourced. Managing data is not a trifling task for big organizations. Proper management of information is crucial for their efficient functioning. Organizations have to manage large volumes of data every day. Outsourcing helps manage such information. This article looks at how data entry outsourcing services can benefit you, and improve your productivity and return on investment.

Core Benefits

Efficient data entry services ensures your organization improved information systems, better customer satisfaction, readily available information, and records in keeping with necessary standards. All this saves time and money, and improves your productivity and efficiency. The data entry outsourcing services provided by an experienced outsourcing company offers many advantages:

Professional expertise: Outsourcing the job allows you to benefit from the expertise of professional operators working with advanced technology to ensure efficient solutions.

Save time and gain a competitive edge: Outsourcing services minimize your administrative workload. It also gives your employees more time to focus on other important tasks. This would definitely help you gain a competitive edge.

Improve productivity and revenue: Outsourcing services are consistent and uninterruptible. Regular monitoring is also possible.

Cut infrastructure costs: Professional data entry services can considerably reduce your operating overhead costs. Outsourcing completely overrules the need to invest in computer systems and other infrastructure, manpower and resources needed to do the job in-house.

Streamline documentation tasks: Well-organized data processing solutions of reliable BPO companies enables you to streamline your routine documentation workflow.

Maintain accurate information systems: Outsourcing enables you to maintain error-free and up-to-date official records. This facilitates easy access to and retrieval of relevant information at any time. You can avoid data back logs and get you records in easy-to-use electronic formats or as hard copies.

Benefit from disaster recovery: As all the data management is with proper back-up, you are ensured of disaster recovery solutions in case of data loss.

Security: All your data is secure as reliable service providers have security measures in place to prevent hacking.

Professional Data Processing Solutions

Many established companies in the US are equipped with advanced technology and experienced professionals with excellent skills in keyboard handling and handwriting recognition. These experts can process both numeric and alphanumeric data with great speed and accuracy. They provide proficient solutions for handwritten materials, texts, books, surveys, medical claims, insurance claims, medical billing forms, legal documents, images, practice forms, product details, scanned images, and more. The benefits you are assured of with these professional data entry services are:

• 99% accuracy rate
• Multi-level quality checking
• Safe and convenient file transfer options
• Stringent data confidentiality and security
• Customized turnaround time
• Competitive pricing, with cost savings up to 40 percent
• Continuous technical support
• Free trials

Select an Established Outsourcing Partner

In summary, professional data entry outsourcing services help streamline your workflow and ensure benefits in terms of business efficiency, costs, time, resources and effort. A web search can lead you to a reliable service provider.


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Data Mining - Retrieving Information From Data

Data mining definition is the process of retrieving information from data. It has become very important now days because data that is processed is usually kept for future reference and mainly for security purposes in a company. Data transforms is processed into information and it is mostly used in different ways depending on what information one is extracting and from where the person is extracting the information.

It is commonly used in marketing, scientific information and research work, fraud detection and surveillance and many more and most of this work is done using a computer. This definition can come in different terms data snooping, data fishing and data dredging all this refer to data mining but it depends in which department one is. One must know data mining definition so that he can be in a position to make data.

The method of data mining has been there for so many centuries and it is used up to date. There were early methods which were used to identify data mining there are mainly two: regression analysis and bayes theorem. These methods are never used now days because a lot of people have advanced and technology has really changed the entire system.

With the coming up or with the introduction of computers and technology, it becomes very fast and easy to save information. Computers have made work easier and one can be able to expand more knowledge about data crawling and learn on how data is stored and processed through computer science.

Computer science is a course that sharpens one skill and expands more about data crawling and the definition of what data mining means. By studying computer science one can be in a position to know: clustering, support vector machines and decision trees there are some of the units that are found on computer science.

It's all about all this and this knowledge must be applied here. Government institutions, small scale business and supermarkets use data.

The main reason most companies use data mining is because data assist in the collection of information and observations that a company goes through in their daily activity. Such information is very vital in any companies profile and needs to be checked and updated for future reference just in case something happens.

Businesses which use data crawling focus mainly on return of investments, and they are able to know whether they are making a profit or a loss within a very short period. If the company or the business is making a profit they can be in a position to give customers an offer on the product in which they are selling so that the business can be a position to make more profit in an organization, this is very vital in human resource departments it helps in identifying the character traits of a person in terms of job performance.

Most people who use this method believe that is ethically neutral. The way it is being used nowadays raises a lot of questions about security and privacy of its members. Data mining needs good data preparation which can be in a position to uncover different types of information especially those that require privacy.

A very common way in this occurs is through data aggregation.

Data aggregation is when information is retrieved from different sources and is usually put together so that one can be in a position to be analyze one by one and this helps information to be very secure. So if one is collecting data it is vital for one to know the following:

    How will one use the data that he is collecting?
    Who will mine the data and use the data.
    Is the data very secure when am out can someone come and access it.
    How can one update the data when information is needed
    If the computer crashes do I have any backup somewhere.

It is important for one to be very careful with documents which deal with company's personal information so that information cannot easily be manipulated.

Victor Cases has many hobbies and interests. As well being a keen blogger and article writer for many sites, he has also recently created a site focusing on data mining definition. The site is constantly being updated and has articles such as data mining to read.


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Web Data Extraction Services

Web Data Extraction from Dynamic Pages includes some of the services that may be acquired through outsourcing. It is possible to siphon information from proven websites through the use of Data Scrapping software. The information is applicable in many areas in business. It is possible to get such solutions as data collection, screen scrapping, email extractor and Web Data Mining services among others from companies providing websites such as Scrappingexpert.com.

Data mining is common as far as outsourcing business is concerned. Many companies are outsource data mining services and companies dealing with these services can earn a lot of money, especially in the growing business regarding outsourcing and general internet business. With web data extraction, you will pull data in a structured organized format. The source of the information will even be from an unstructured or semi-structured source.

In addition, it is possible to pull data which has originally been presented in a variety of formats including PDF, HTML, and test among others. The web data extraction service therefore, provides a diversity regarding the source of information. Large scale organizations have used data extraction services where they get large amounts of data on a daily basis. It is possible for you to get high accuracy of information in an efficient manner and it is also affordable.

Web data extraction services are important when it comes to collection of data and web-based information on the internet. Data collection services are very important as far as consumer research is concerned. Research is turning out to be a very vital thing among companies today. There is need for companies to adopt various strategies that will lead to fast means of data extraction, efficient extraction of data, as well as use of organized formats and flexibility.

In addition, people will prefer software that provides flexibility as far as application is concerned. In addition, there is software that can be customized according to the needs of customers, and these will play an important role in fulfilling diverse customer needs. Companies selling the particular software therefore, need to provide such features that provide excellent customer experience.

It is possible for companies to extract emails and other communications from certain sources as far as they are valid email messages. This will be done without incurring any duplicates. You will extract emails and messages from a variety of formats for the web pages, including HTML files, text files and other formats. It is possible to carry these services in a fast reliable and in an optimal output and hence, the software providing such capability is in high demand. It can help businesses and companies quickly search contacts for the people to be sent email messages.

It is also possible to use software to sort large amount of data and extract information, in an activity termed as data mining. This way, the company will realize reduced costs and saving of time and increasing return on investment. In this practice, the company will carry out Meta data extraction, scanning data, and others as well.


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Utilize Online Data Entry Services From India For Extended Profits

Numerous companies are seeking help for data entry services in order to better manage their company database. Many changes and innovations have taken place in this field that has greatly facilitated and accelerated often tedious and time consuming processes. There are a multitude of data entry companies offering useful solutions to businesses of all types. Hiring an online data entry company in India is an economical option. These outsourcing companies provide high quality work to businesses around the world.

Many firms have started passing their data entry work on to third party firms in an effort to save on overhead costs. The burden of employing a full time data entry associate on a salary basis and providing them with all the benefits of regular employees is immense, whether the work load is large of small for a particular month. Hiring a consultant will enable you to only incur costs when necessary.

Data is a very important part of any business. Therefore it is critical that it is handled with experienced hands and skills. Well managed data can be used in an endless number of ways to better plan and manage the undertakings of a business. As a part of data entry services, data conversion is gaining popularity. The companies are using the latest techniques and tools for designing data entry solutions. In order to make data useful for anyone, its conversion is important. Data that requires a longer duration of processing time should be outsourced for better efficiency of information flow.

Different types of businesses make use of these services. They primarily have an immense database to manage, for which to India is a cost effective option. For instance, pharmaceutical companies, educational institutes, law firms, E-Commerce sites, and others make use to data entry services for higher profits.

Outsourced data entry services have been very beneficial for companies by increasing sales, yet lowering labor expenses. They help in expanding the client base internationally, which enables global access to international customers with ease. Generally the data that is complex and takes longer processing times should be outsourced for better, timelier results. Some businesses can even take advantage of data conversion, document processing, and catalog development if they need it.

There are many advantages of outsourcing data entry services to developing countries like India. Here the workforce is cheap yet highly skilled. Thus, businesses can get better quality of work at relatively lower prices in comparison to companies in developed countries. There are a tremendous number of data entry service providers. One of these firms will be a great tool to take your business to the next level.



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Why Outsource Data Entry Services?

All large business and organizations are faced with the task of processing huge amounts of data on a daily basis. The data to be processed may range from indexing of vouchers and documents to collecting of information from customers and vendors. In order to save on the huge amount of time, energy and monetary resources which go into data entry, businesses world wide have discovered the multiple benefits of outsourcing their Data Entry Services to India. Along with quick turn around time, reliability of data accuracy and confidentiality of all client databases, outsourcing Data Entry Services to India also proves to be extremely cost-effective.

What are the kinds of Services that can be outsourced?

Most outsourcing companies provide custom made Data-Entry Services depending on the client's specifications. A few of them provided by Indian Outsourcing Companies are;

- Data entry from product catalogs to web based systems
- Entry from hard/soft copy to any preferred database format
- Insurance claims processing
- Image Entry
- Data mining and warehousing
- Data cleansing
- Entry from hospital records, patient notes and accident reports
- From e-book and e-magazine publications on the Internet
- Entry for mailing lists
- PDF document indexing
- Online data capture services
- Online order entry and follow up services
- Creating new databases and updating of existing databases for banks, airlines, government agencies
- direct marketing services and service providers
- Web based indexed document retrieval services, tools and support
- Entry of legal documents
- Indexing of vouchers and documents
- Hand written ballot/cards entry
- Online completion of surveys and responses of customers for various companies
- Business card indexing
- Custom data export/import interfaces with audits
- Bonded mail handling cash, credit and check processing
- Entry of Questionnaires
- Entry of Company Reports
- From Printed / Handwritten Source
- From Yellow Pages / White Pages
- Entry of Dictionaries, Manuals and Encyclopedia
- Entry of Surveys

What is the process?

Since most Indian companies hire only competent and highly qualified staff, outsourcing Data Entry Services to India ensures that the client is fully satisfied with the end result. Added to this the client's data confidentiality and security is viewed as extremely important. Each project goes through a specific data entry service plan that aims to fulfill the exact need of the customer and the error rate is always kept below 2-3%. The process is as follows:

- Data is processed, scanned and uploaded on to secure FTP online server
- Data is subsequently accessed over VPN and downloaded
- Data is individually indexed and sorted into private work folders
- Data is entered into specific applications as per client's requirements
- Data is checked and assessed for errors
- Data is finally sent to the customers

What are the benefits of outsourcing Services?

Oversees companies outsourcing their Data Entry Services to India have the assurance that their projects will be delivered on time with the highest levels of data quality and accuracy. The cost competitive prices, highly qualified employees, fast turnaround time and data security offered by outsourcing vendors, make sure that all of the client's objectives and goals are met. Outsourcing of these Services to India has been proven to be an advantageous choice for businesses worldwide.

Outsource2india provides Outsourcing Services and Solutions, Data Entry Services data processing services, data management, Business and Knowledge Process Outsourcing, Call Center Services, Healthcare Services, Engineering Services, Software Services, Digital Image Editing Services, Research & Analysis Services, Creative Services, Web Analytics Services, etc.



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