What is Data Mining? Why Data Mining is Important?

What is Data Mining? Why Data Mining is Important?

Searching, Collecting, Filtering and Analyzing of data define as data mining. The large amount of information can be retrieved from wide range of form such as different data relationships, patterns or any significant statistical co-relations. Today the advent of computers, large databases and the internet is make easier way to collect millions, billions and even trillions of pieces of data that can be systematically analyzed to help look for relationships and to seek solutions to difficult problems.

The government, private company, large organization and all businesses are looking for large volume of information collection for research and business development. These all collected data can be stored by them to future use. Such kind of information is most important whenever it is require. It will take very much time for searching and find require information from the internet or any other resources.

Here is an overview of data mining services inclusion:

* Market research, product research, survey and analysis
* Collection information about investors, funds and investments
* Forums, blogs and other resources for customer views/opinions
* Scanning large volumes of data
* Information extraction
* Pre-processing of data from the data warehouse
* Meta data extraction
* Web data online mining services
* data online mining research
* Online newspaper and news sources information research
* Excel sheet presentation of data collected from online sources
* Competitor analysis
* data mining books
* Information interpretation
* Updating collected data

After applying the process of data mining, you can easily information extract from filtered information and processing the refining the information. This data process is mainly divided into 3 sections; pre-processing, mining and validation. In short, data online mining is a process of converting data into authentic information.

The most important is that it takes much time to find important information from the data. If you want to grow your business rapidly, you must take quick and accurate decisions to grab timely available opportunities.

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Benefits of data extraction for the healthcare system

Benefits of data extraction for the healthcare system

When people think of data extraction, they have to understand that is the process of information retrieval, which extract automatically structured information from semi-structured or unstructured web data sources. The companies that do data extraction provide for clients specific information available on different web pages. The Internet is a limitless source of information, and through this process, people from all domains can have access to useful knowledge. The same is with the healthcare system, which has to be concerned with providing patients quality services. They have to deal with poor documentation, and this has a huge impact on the way they provide services, so they have to do their best and try to obtain the needed information. If doctors confront with a lack of complete documentation in a case, they are not able to proper care the patients. The goal of data scraping in this situation is to provide accurate and sufficient information for correct billing and coding the services provided to patients.

The persons that are working in the healthcare system have to review in some situations hundred of pages long documents, for knowing how to deal with a case, and they have to be sure that the ones that contain useful information will be protected for being destroyed or lost in the future. A data mining company has the capability to automatically manage and capture the information from such documents. It helps doctors and healthcare specialists to reduce their dependency on manual data entry, and this helps them to become more efficient. If it is used a data scraping system, data is brought faster and doctors are able to make decisions more effectively. In addition, the healthcare system can collaborate with a company that is able to gather data from patients, to see how a certain type of drug reacts and what side effects it has.

Data mining companies can provide specific tools that can help specialists extract handwritten information. They are based on a character recognition technology that includes a continuously learning network that improves constantly. This assures people that they will obtain an increased level of accuracy. These tools transform the way clinics and hospitals manage and collect data. They are the key for the healthcare system to meet federal guidelines on patient privacy. When such a system is used by a hospital or clinic, it benefits from extraction, classification and management of the patient data. This classification makes the extraction process easier, because when a specialist needs information for a certain case he will have access to them in a fast and effective way. An important aspect in the healthcare system is that specialists have to be able to extract data from surveys. A data scraping company has all the tools needed for processing the information from a test or survey. The processing of this type of information is based on optical mark recognition technology and this helps at extracting the data from checkboxes more easily. The medical system has recorded an improved efficiency in providing quality services for patients since it began to use data scrapping.

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Benefits of Predictive Analytics and Data Mining Services

Benefits of Predictive Analytics and Data Mining Services

Predictive Analytics is the process of dealing with variety of data and apply various mathematical formulas to discover the best decision for a given situation. Predictive analytics gives your company a competitive edge and can be used to improve ROI substantially. It is the decision science that removes guesswork out of the decision-making process and applies proven scientific guidelines to find right solution in the shortest time possible.

Predictive analytics can be helpful in answering questions like:

-  Who are most likely to respond to your offer?
-  Who are most likely to ignore?
-  Who are most likely to discontinue your service?
-  How much a consumer will spend on your product?
-  Which transaction is a fraud?
-  Which insurance claim is a fraudulent?
-  What resource should I dedicate at a given time?

Benefits of Data mining include:

-  Better understanding of customer behavior propels better decision
-  Profitable customers can be spotted fast and served accordingly
-  Generate more business by reaching hidden markets
-  Target your Marketing message more effectively
-  Helps in minimizing risk and improves ROI.
-  Improve profitability by detecting abnormal patterns in sales, claims, transactions etc
-  Improved customer service and confidence
-  Significant reduction in Direct Marketing expenses

Basic steps of Predictive Analytics are as follows:

-  Spot the business problem or goal
-  Explore various data sources such as transaction history, user demography, catalog details, etc)
-  Extract different data patterns from the above data
-  Build a sample model based on data & problem
-  Classify data, find valuable factors, generate new variables
-  Construct a Predictive model using sample
-  Validate and Deploy this Model

Standard techniques used for it are:

-  Decision Tree
-  Multi-purpose Scaling
-  Linear Regressions
-  Logistic Regressions
-  Factor Analytics
-  Genetic Algorithms
-  Cluster Analytics
-  Product Association

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

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

Who can use Data Scraping Services?

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

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

Web Data Extraction

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

Data Collection

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

Email Extractor

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

Screen scrapping

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

Data Mining Services

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

Web spider

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

Web Grabber

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

Web Bot

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

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Data Mining Introduction

Data Mining Introduction

Introduction

We have been "manually" extracting data in relation to the patterns they form for many years but as the volume of data and the varied sources from which we obtain it grow a more automatic approach is required.

The cause and solution to this increase in data to be processed has been because the increasing power of computer technology has increased data collection and storage. Direct hands-on data analysis has increasingly been supplemented, or even replaced entirely, by indirect, automatic data processing. Data mining is the process uncovering hidden data patterns and has been used by businesses, scientists and governments for years to produce market research reports. A primary use for data mining is to analyse patterns of behaviour.

It can be easily be divided into stages

Pre-processing

Once the objective for the data that has been deemed to be useful and able to be interpreted is known, a target data set has to be assembled. Logically data mining can only discover data patterns that already exist in the collected data, therefore the target dataset must be able to contain these patterns but small enough to be able to succeed in its objective within an acceptable time frame.

The target set then has to be cleansed. This removes sources that have noise and missing data.

The clean data is then reduced into feature vectors,(a summarized version of the raw data source) at a rate of one vector per source. The feature vectors are then split into two sets, a "training set" and a "test set". The training set is used to "train" the data mining algorithm(s), while the test set is used to verify the accuracy of any patterns found.

Data mining

Data mining commonly involves four classes of task:

Classification - Arranges the data into predefined groups. For example email could be classified as legitimate or spam.
Clustering - Arranges data in groups defined by algorithms that attempt to group similar items together
Regression - Attempts to find a function which models the data with the least error.
Association rule learning - Searches for relationships between variables. Often used in supermarkets to work out what products are frequently bought together. This information can then be used for marketing purposes.

Validation of Results

The final stage is to verify that the patterns produced by the data mining algorithms occur in the wider data set as not all patterns found by the data mining algorithms are necessarily valid.

If the patterns do not meet the required standards, then the preprocessing and data mining stages have to be re-evaluated. When the patterns meet the required standards then these patterns can be turned into knowledge.

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Searching the Web Using Text Mining and Data Mining

Searching the Web Using Text Mining and Data Mining

There are many types of financial analysis tools that are useful for various purposes. Most of these are easily available online. Two such tools of software for financial analysis include the text mining and data mining. Both methods have been discussed in details in the following section.

The features of Text Mining It is a way by which information of high-quality can be derived from a text. It involves giving structure to the input text then deriving patterns within the data that has been structured. Finally, the process of evaluating and interpreting the output is undertaken.

This form of mining usually involves the process of structuring the text input, and deriving patterns within the structured data, and finally evaluating and interpreting the data. It differs from the way we are familiar with in searching the web. The goal of this method is to find unknown information. It can be done with analyses in topics that that were not researched before.

What is Data Mining? It is the process of the extraction of patterns from the data. Nowadays, it has become very vital to transform this data into information. It is particularly used in marketing practices as well as fraud detection and surveillance. We can extract hidden information from huge databases of information. It can be used to predict future trends as well as to aid the company business to make knowledgeable quick decisions.

Working of data mining: Modeling technique is used to perform the operation of such form of mining. For these techniques, you must need to be fully integrated with a data warehouse as well as financial analysis tools. Some of the areas where this method is used are:

 - Pharmaceutical companies which need to analyze its sales force and to achieve their targets.
 - Credit card companies and transportation companies with sales force.
 - Also large consumer goods companies use such mining techniques.
 - With this method, a retailer may utilize POS or point-of-sale data of customer purchases in order to develop  strategies for sale promotion.

The major elements of Data mining:

1. Extracting, transforming, and sending load transaction data on the data warehouse of the server system.

2. Storing and managing the data in for database systems that are multidimensional in nature.

3. Presenting data to the IT professionals and business analysts for processing.

4. Presenting the data to the application software for analyses.

5. Presentation of the data in dynamic ways like graph or table.

The main point of difference between the two types of mining is that text mining checks the patterns from natural text instead of databases where the data is structured.

Data mining software supports the entire process of such mining and discovery of knowledge. These are available on the internet. Data mining software serves as one of the best financial analysis tools. You can avail of data mining software suites and their reviews freely over the internet and easily compare between them.

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Data Mining

Data Mining

Data mining is the retrieving of hidden information from data using algorithms. Data mining helps to extract useful information from great masses of data, which can be used for making practical interpretations for business decision-making. It is basically a technical and mathematical process that involves the use of software and specially designed programs. Data mining is thus also known as Knowledge Discovery in Databases (KDD) since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

Data mining is gaining a lot of importance because of its vast applicability. It is being used increasingly in business applications for understanding and then predicting valuable information, like customer buying behavior and buying trends, profiles of customers, industry analysis, etc. It is basically an extension of some statistical methods like regression. However, the use of some advanced technologies makes it a decision making tool as well. Some advanced data mining tools can perform database integration, automated model scoring, exporting models to other applications, business templates, incorporating financial information, computing target columns, and more.

Some of the main applications of data mining are in direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. The different kinds of data are: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining.

Some of the most popular data mining tools are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, Gaussian Baves classification, cross-validation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-Means and hierarchical clustering, Markov models, support vector machines, game tree search and alpha-beta search algorithms, game theory, artificial intelligence, A-star heuristic search, HillClimbing, simulated annealing and genetic algorithms.

Some popular data mining software includes: Connexor Machines, Copernic Summarizer, Corpora, DocMINER, DolphinSearch, dtSearch, DS Dataset, Enkata, Entrieva, Files Search Assistant, FreeText Software Technologies, Intellexer, Insightful InFact, Inxight, ISYS:desktop, Klarity (part of Intology tools), Leximancer, Lextek Onix Toolkit, Lextek Profiling Engine, Megaputer Text Analyst, Monarch, Recommind MindServer, SAS Text Miner, SPSS LexiQuest, SPSS Text Mining for Clementine, Temis-Group, TeSSI®, Textalyser, TextPipe Pro, TextQuest, Readware, Quenza, VantagePoint, VisualText(TM), by TextAI, Wordstat. There is also free software and shareware such as INTEXT, S-EM (Spy-EM), and Vivisimo/Clusty.

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