Data Mining and Financial Data Analysis

Data Mining and Financial Data Analysis

Introduction:

Most marketers understand the value of collecting financial data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining - technologies and techniques for recognizing and tracking patterns within data - helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs as well as financial need. In this accessible introduction, we provides a business and technological overview of data mining and outlines how, along with sound business processes and complementary technologies, data mining can reinforce and redefine for financial analysis.

Objective:

1. The main objective of mining techniques is to discuss how customized data mining tools should be developed for financial data analysis.

2. Usage pattern, in terms of the purpose can be categories as per the need for financial analysis.

3. Develop a tool for financial analysis through data mining techniques.

Data mining:

Data mining is the procedure for extracting or mining knowledge for the large quantity of data or we can say data mining is "knowledge mining for data" or also we can say Knowledge Discovery in Database (KDD). Means data mining is : data collection , database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in database, such as

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data source may be combined.)

3. Data selection. (Where data relevant to the analysis task are retrieved from the database.)

4. Data transformation. (Where data are transformed or consolidated into forms appropriate for mining by performing summary or aggregation operations, for instance)

5. Data mining. (An essential process where intelligent methods are applied in order to extract data patterns.)

6. Pattern evaluation. (To identify the truly interesting patterns representing knowledge based on some interesting measures.)

7. Knowledge presentation.(Where visualization and knowledge representation techniques are used to present the mined knowledge to the user.)

Data Warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema and which usually resides at a single site.

Text:

Most of the banks and financial institutions offer a wide verity of banking services such as checking, savings, business and individual customer transactions, credit and investment services like mutual funds etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give one analysis known as "Evolution Analysis".

Data evolution analysis is used for the object whose behavior changes over time. Although this may include characterization, discrimination, association, classification, or clustering of time related data, means we can say this evolution analysis is done through the time series data analysis, sequence or periodicity pattern matching and similarity based data analysis.

Data collect from banking and financial sectors are often relatively complete, reliable and high quality, which gives the facility for analysis and data mining. Here we discuss few cases such as,

Eg, 1. Suppose we have stock market data of the last few years available. And we would like to invest in shares of best companies. A data mining study of stock exchange data may identify stock evolution regularities for overall stocks and for the stocks of particular companies. Such regularities may help predict future trends in stock market prices, contributing our decision making regarding stock investments.

Eg, 2. One may like to view the debt and revenue change by month, by region and by other factors along with minimum, maximum, total, average, and other statistical information. Data ware houses, give the facility for comparative analysis and outlier analysis all are play important roles in financial data analysis and mining.

Eg, 3. Loan payment prediction and customer credit analysis are critical to the business of the bank. There are many factors can strongly influence loan payment performance and customer credit rating. Data mining may help identify important factors and eliminate irrelevant one.

Factors related to the risk of loan payments like term of the loan, debt ratio, payment to income ratio, credit history and many more. The banks than decide whose profile shows relatively low risks according to the critical factor analysis.

We can perform the task faster and create a more sophisticated presentation with financial analysis software. These products condense complex data analyses into easy-to-understand graphic presentations. And there's a bonus: Such software can vault our practice to a more advanced business consulting level and help we attract new clients.

To help us find a program that best fits our needs-and our budget-we examined some of the leading packages that represent, by vendors' estimates, more than 90% of the market. Although all the packages are marketed as financial analysis software, they don't all perform every function needed for full-spectrum analyses. It should allow us to provide a unique service to clients.

The Products:

ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-size enterprises and can help make business-planning decisions by modeling the impact of various options. This is accomplished by demonstrating the what-if outcomes of small changes. A roll forward feature prepares budgets or forecast reports in minutes. The program also generates a financial scorecard of key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry by using the Risk Management Association (RMA) database. It also highlights key ratios that need improvement and year-to-year trend analysis. A unique function, Back Calculation, calculates the profit targets or the appropriate asset base to support existing sales and profitability. Its DuPont Model Analysis demonstrates how each ratio affects return on equity.

Financial Analysis CS reviews and compares a client's financial position with business peers or industry standards. It also can compare multiple locations of a single business to determine which are most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then lets them provide aggregated financial indicators of peers or industry standards, showing clients how their businesses compare.

iLumen regularly collects a client's financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client's financial performance with industry peers. The system is Web-based and can monitor a client's performance on a monthly, quarterly and annual basis. The network can upload a trial balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company's performance for the period. Analysis tools are viewed through customized dashboards.

PlanGuru by New Horizon Technologies can generate client-ready integrated balance sheets, income statements and cash-flow statements. The program includes tools for analyzing data, making projections, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and consultant editions. An add-on, called the Business Analyzer, calculates benchmarks.

ProfitCents by Sageworks is Web-based, so it requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also provides a wide variety of businesses analyses for nonprofits and sole proprietorships. The company offers free consulting, training and customer support. It's also available in Spanish.

ProfitSystem fx Profit Driver by CCH Tax and Accounting provides a wide range of financial diagnostics and analytics. It provides data in spreadsheet form and can calculate benchmarking against industry standards. The program can track up to 40 periods.

Source : http://ezinearticles.com/?Data-Mining-and-Financial-Data-Analysis&id=2752017

Know What the Truth Behind Data Mining Outsourcing Service

Know What the Truth Behind Data Mining Outsourcing Service

We came to that, what we call the information age where industries are like useful data needed for decision-making, the creation of products - among other essential uses for business. Information mining and converting them to useful information is a part of this trend that allows companies to reach their optimum potential. However, many companies that do not meet even one deal with data mining question because they are simply overwhelmed with other important tasks. This is where data mining outsourcing comes in.

There have been many definitions to introduced, but it can be simply explained as a process that involves sorting through large amounts of raw data to extract valuable information needed by industries and enterprises in various fields. In most cases this is done by professionals, professional organizations and financial analysts. He has seen considerable growth in the number of sectors or groups that enter my self.
There are a number of reasons why there is a rapid growth in data mining outsourcing service subscriptions. Some of them are presented below:

A wide range of services

Many companies are turning to information mining outsourcing, because they cover a wide range of services. These services include, but are not limited to data from web applications congregation database, collect contact information from different sites, extract data from websites using the software, the sort of stories from sources news, information and accumulate commercial competitors.

Many companies fall

Many industries benefit because it is fast and realistic. The information extracted by data mining service providers of outsourcing used in crucial decisions in the field of direct marketing, e-commerce, customer relationship management, health, scientific tests and other experimental work, telecommunications, financial services, and a whole lot more.

A lot of advantages

Subscribe data mining outsourcing services it's offers many benefits, as providers assures customers to render services to world standards. They strive to work with improved technologies, scalability, sophisticated infrastructure, resources, timeliness, cost, the system safer for the security of information and increased market coverage.

Outsourcing allows companies to focus their core business and can improve overall productivity. Not surprisingly, information mining outsourcing has been a first choice of many companies - to propel the business to higher profits.

Source:http://ezinearticles.com/?Know-What-the-Truth-Behind-Data-Mining-Outsourcing-Service&id=5303589

Data Extraction - A Guideline to Use Scrapping Tools Effectively

Data Extraction - A Guideline to Use Scrapping Tools Effectively

So many people around the world do not have much knowledge about these scrapping tools. In their views, mining means extracting resources from the earth. In these internet technology days, the new mined resource is data. There are so many data mining software tools are available in the internet to extract specific data from the web. Every company in the world has been dealing with tons of data, managing and converting this data into a useful form is a real hectic work for them. If this right information is not available at the right time a company will lose valuable time to making strategic decisions on this accurate information.

This type of situation will break opportunities in the present competitive market. However, in these situations, the data extraction and data mining tools will help you to take the strategic decisions in right time to reach your goals in this competitive business. There are so many advantages with these tools that you can store customer information in a sequential manner, you can know the operations of your competitors, and also you can figure out your company performance. And it is a critical job to every company to have this information at fingertips when they need this information.

To survive in this competitive business world, this data extraction and data mining are critical in operations of the company. There is a powerful tool called Website scraper used in online digital mining. With this toll, you can filter the data in internet and retrieves the information for specific needs. This scrapping tool is used in various fields and types are numerous. Research, surveillance, and the harvesting of direct marketing leads is just a few ways the website scraper assists professionals in the workplace.

Screen scrapping tool is another tool which useful to extract the data from the web. This is much helpful when you work on the internet to mine data to your local hard disks. It provides a graphical interface allowing you to designate Universal Resource Locator, data elements to be extracted, and scripting logic to traverse pages and work with mined data. You can use this tool as periodical intervals. By using this tool, you can download the database in internet to you spread sheets. The important one in scrapping tools is Data mining software, it will extract the large amount of information from the web, and it will compare that date into a useful format. This tool is used in various sectors of business, especially, for those who are creating leads, budget establishing seeing the competitors charges and analysis the trends in online. With this tool, the information is gathered and immediately uses for your business needs.

Another best scrapping tool is e mailing scrapping tool, this tool crawls the public email addresses from various web sites. You can easily from a large mailing list with this tool. You can use these mailing lists to promote your product through online and proposals sending an offer for related business and many more to do. With this toll, you can find the targeted customers towards your product or potential business parents. This will allows you to expand your business in the online market.

There are so many well established and esteemed organizations are providing these features free of cost as the trial offer to customers. If you want permanent services, you need to pay nominal fees. You can download these services from their valuable web sites also.

Source:http://ezinearticles.com/?Data-Extraction---A-Guideline-to-Use-Scrapping-Tools-Effectively&id=3600918

Web Data Extraction

Web Data Extraction

The Internet as we know today is a repository of information that can be accessed across geographical societies. In just over two decades, the Web has moved from a university curiosity to a fundamental research, marketing and communications vehicle that impinges upon the everyday life of most people in all over the world. It is accessed by over 16% of the population of the world spanning over 233 countries.

As the amount of information on the Web grows, that information becomes ever harder to keep track of and use. Compounding the matter is this information is spread over billions of Web pages, each with its own independent structure and format. So how do you find the information you're looking for in a useful format - and do it quickly and easily without breaking the bank?

Search Isn't Enough

Search engines are a big help, but they can do only part of the work, and they are hard-pressed to keep up with daily changes. For all the power of Google and its kin, all that search engines can do is locate information and point to it. They go only two or three levels deep into a Web site to find information and then return URLs. Search Engines cannot retrieve information from deep-web, information that is available only after filling in some sort of registration form and logging, and store it in a desirable format. In order to save the information in a desirable format or a particular application, after using the search engine to locate data, you still have to do the following tasks to capture the information you need:

· Scan the content until you find the information.

· Mark the information (usually by highlighting with a mouse).

· Switch to another application (such as a spreadsheet, database or word processor).

· Paste the information into that application.

Its not all copy and paste

Consider the scenario of a company is looking to build up an email marketing list of over 100,000 thousand names and email addresses from a public group. It will take up over 28 man-hours if the person manages to copy and paste the Name and Email in 1 second, translating to over $500 in wages only, not to mention the other costs associated with it. Time involved in copying a record is directly proportion to the number of fields of data that has to copy/pasted.

Is there any Alternative to copy-paste?

A better solution, especially for companies that are aiming to exploit a broad swath of data about markets or competitors available on the Internet, lies with usage of custom Web harvesting software and tools.

Web harvesting software automatically extracts information from the Web and picks up where search engines leave off, doing the work the search engine can't. Extraction tools automate the reading, the copying and pasting necessary to collect information for further use. The software mimics the human interaction with the website and gathers data in a manner as if the website is being browsed. Web Harvesting software only navigate the website to locate, filter and copy the required data at much higher speeds that is humanly possible. Advanced software even able to browse the website and gather data silently without leaving the footprints of access.

Source: http://ezinearticles.com/?Web-Data-Extraction&id=575212

Web Data Extraction Services and Data Collection Form Website Pages

Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:
• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection
Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:
• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.

Source:http://ezinearticles.com/?Web-Data-Extraction-Services-and-Data-Collection-Form-Website-Pages&id=4860417

An Easy Way For Data Extraction

An Easy Way For Data Extraction

There are so many data scraping tools are available in internet. With these tools you can you download large amount of data without any stress. From the past decade, the internet revolution has made the entire world as an information center. You can obtain any type of information from the internet. However, if you want any particular information on one task, you need search more websites. If you are interested in download all the information from the websites, you need to copy the information and pate in your documents. It seems a little bit hectic work for everyone. With these scraping tools, you can save your time, money and it reduces manual work.

The Web data extraction tool will extract the data from the HTML pages of the different websites and compares the data. Every day, there are so many websites are hosting in internet. It is not possible to see all the websites in a single day. With these data mining tool, you are able to view all the web pages in internet. If you are using a wide range of applications, these scraping tools are very much useful to you.

The data extraction software tool is used to compare the structured data in internet. There are so many search engines in internet will help you to find a website on a particular issue. The data in different sites is appears in different styles. This scraping expert will help you to compare the date in different site and structures the data for records.

And the web crawler software tool is used to index the web pages in the internet; it will move the data from internet to your hard disk. With this work, you can browse the internet much faster when connected. And the important use of this tool is if you are trying to download the data from internet in off peak hours. It will take a lot of time to download. However, with this tool you can download any data from internet at fast rate.There is another tool for business person is called email extractor. With this toll, you can easily target the customers email addresses. You can send advertisement for your product to the targeted customers at any time. This the best tool to find the database of the customers.

However, there are some more scraping tolls are available in internet. And also some of esteemed websites are providing the information about these tools. You download these tools by paying a nominal amount.

Source: http://ezinearticles.com/?An-Easy-Way-For-Data-Extraction&id=3517104

Scrape amazon and price your product the right way – A use case

Scrape amazon and price your product the right way – A use case

So you built a product that you want to sell through Amazon.

How do you price your product? 

Amazon is the world’s largest online retailer. Millions of products are sold through amazon.  a lot of people make their living selling through Amazon. One of the biggest mistake people do in Amazon is that they price their product the wrong way. Sometimes they sell overpriced products, sometimes they sell the underpriced product. Both situations are toxic for the business.

We recently worked with a company that helps small businesses sell the products efficiently through amazon and other marketplaces. One of the key things they are doing is helping people with pricing their product the right way.

What I learned from them is that price is a relative term and a lot of people does not understand it. Pricing is a function of the positioning of  your product in the market.

We need to collect the data using  a technique called web scraping to understand how to position the product. You can get the  data in a CSV file which can be used for analysis.

1) What is the average price of a comparable product?

Understanding the pricing  strategy of your competitors products  is the first step in solving the problem. This can give you a range in which you can price your product. You can get the pricing data by scraping amazon

2) Is this a premium product?

People always pay a premium price for a premium product. What makes a product premium? – A product is considered premium only when the customer believe it is worth the price. Excellent marketing and branding are the ways to position your product as a premium product. You can get the relevant data by scraping amazon.

3) What are the problems with your competitor products?

Your competitor products might be having some defects. Or they might not be addressing a relevant problem. You have every chance of success If you are solving a problem that your competitor doesn’t. You can find these problems by analyzing the product reviews of your competitors. You can get review data by scraping amazon.

By analyzing data you can reach at a point where your profit margin looks healthy and pricing looks sensible. Buyers buy the value, not your product. Differentiate your product and position it as a superior product. Give people a reason to buy and that is the only way to succeed.

Source: http://blog.datahut.co/scrape-amazon-and-price-your-product-the-right-way-a-use-case/

Why Outsourcing Data Mining Services?

Why Outsourcing Data Mining Services?

Are huge volumes of raw data waiting to be converted into information that you can use? Your organization's hunt for valuable information ends with valuable data mining, which can help to bring more accuracy and clarity in decision making process.

Nowadays world is information hungry and with Internet offering flexible communication, there is remarkable flow of data. It is significant to make the data available in a readily workable format where it can be of great help to your business. Then filtered data is of considerable use to the organization and efficient this services to increase profits, smooth work flow and ameliorating overall risks.

Data mining is a process that engages sorting through vast amounts of data and seeking out the pertinent information. Most of the instance data mining is conducted by professional, business organizations and financial analysts, although there are many growing fields that are finding the benefits of using in their business.

Data mining is helpful in every decision to make it quick and feasible. The information obtained by it is used for several applications for decision-making relating to direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities.

Data mining services include:

•     Congregation data from websites into excel database
•     Searching & collecting contact information from websites
•     Using software to extract data from websites
•     Extracting and summarizing stories from news sources
•     Gathering information about competitors business

In this globalization era, handling your important data is becoming a headache for many business verticals. Then outsourcing is profitable option for your business. Since all projects are customized to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure can be realized.

Advantages of Outsourcing Data Mining Services:

•     Skilled and qualified technical staff who are proficient in English
•     Improved technology scalability
•     Advanced infrastructure resources
•     Quick turnaround time
•     Cost-effective prices
•     Secure Network systems to ensure data safety
•     Increased market coverage

Outsourcing will help you to focus on your core business operations and thus improve overall productivity. So data mining outsourcing is become wise choice for business. Outsourcing of this services helps businesses to manage their data effectively, which in turn enable them to achieve higher profits.

Source: http://ezinearticles.com/?Why-Outsourcing-Data-Mining-Services?&id=3066061

How Web Scraping Affects your Revenue Growth

How Web Scraping Affects your Revenue Growth

Web scraping is an indispensable resource when it comes to gaining an edge in the competition with the help of business intelligence. As more and more data gets created on the world wide web, the complexity of extracting it intensifies. Web scraping is a technology that demands an extensive tech stack, high end resources and technically skilled labour. Given this resource hungry nature, many businesses prefer outsourcing it to doing the scraping in-house. Here is a brief walk-through of web scraping so that you can get a grip on the whole process and understand how it could affect your revenue growth as a business.

Business intelligence

The competition among online businesses is at its peak. This has more to do with the ready availability of insightful data. When data acquisition at this scale wasn’t possible in the past, businesses made hit-or-miss decisions upon instincts. Now that every activity can be recorded, extracted as data and analysed to arrive at the best business decisions, companies are making the most of it to boost their revenue. This includes monitoring the activity of competitors on social media, price intelligence, sentiment analysis, gathering data for market research and much more. The use cases of web scraping in business is almost infinite. Business intelligence is extremely helpful for the survival of companies in a market that fluctuates often. Implementing a business intelligence strategy powered by web scraping can definitely give a boost to your revenue growth.
Cost centres involved in in-house Web Scraping

Web scraping, despite being a robust solution for extracting data from the web, is not going to be an easy path if your company is not technically rich already. It involves setting up resources like a tech stack and servers that can run the web crawler by a technically skilled team. Following are the primary cost centres involved in the web scraping process.

1. High end servers

Web scraping is a resource intensive process. Considering the importance of uptime here, the crawlers cannot be run on average performance machines. To have the optimum uptime and avoid crashes, the crawler has to be run on high performing servers located in different parts of the world. The quality of servers is crucial to the consistency of the process. Not to mention, these high end servers makeup for a significant amount of the cost involved in web scraping.

2. Technically skilled labour

Scanning through the source code to identify appropriate tags that hold the required data points and creating a program that can automatically fetch these data points from similar pages’ at large scale requires deep programming skills. It goes without saying that employing skilled people would incur cost that could take a hit on your revenue. Ideally, you will need a team of at least 10 to run a web scraping setup in-house.       

3. An extensive tech stack

Although most of the software being used for web scraping are open source, you will find yourself investing in paid software to make certain things easier or faster. Dealing with open source software might not be as user friendly as the paid ones. In any case, having a tech stack with a lot of options is a necessary aspect of web scraping that would incur additional cost.   

4. Maintenance

Building and running the web scraping setup is only half of the story. Since websites undergo changes often, there is a possibility of the crawler setup breaking from time to time. To avoid or solve this at the earliest, a monitoring system that involves both machines and humans is necessary. Monitoring and maintenance contribute to a considerable cost in the web scraping process.
Data as a service

If data for business is your requirement, a better way to acquire it would be to depend on a company that can deliver it via the data as a service route. Web scraping companies have already set up high-end resources required to run the web crawlers that you can utilize to avail web scraping at a much lower cost than what you would incur by doing it on your own. With this, you can also save yourself from the complications and maintenance headache associated with web scraping. Moreover, with a web scraping service, you can enjoy a much higher return on investment owing to the lowered cost of data acquisition. You can use our ROI calculator to compare between the cost of going with an in-house web scraping setup and a hosted solution.

Source: https://www.promptcloud.com/blog/web-scraping-affects-revenue-growth

How to use Web Content Extractor(WCE) as Email Scraper?

How to use Web Content Extractor(WCE) as Email Scraper?

Web Content Extractor is a great web scraping software developed by Newprosoft Team. The software has easy to use project wizard to create a scraping configuration and scrape data from websites.

One day I came to see the Visual Email Extractor which is also product of Newprosoft and similar to Web Content Extractor but it’s primary use is to scrape email addresses by crawling websites you feed to the scraper. I had noticed that with the little modification in Web Content Extractor project configuration you can use it same as Visual Email Extractor to extract email addresses.

In this post I will show you what configuration makes the Web Content Extractor to extract email addresses. I still recommend Visual Email Extractor as it has lot more features then extracting email using WCE.

Here are the configuration that makes WCE to Extract Emails.

Step 1 : Open Web Content Extractor and Create New Project and Click on Next.

Step 2:  Under Crawling Rules -> Advanced Rules Tab do the following settings

Crawling Level 1 Settings

Follow Links if link text equals:
*contact*; *feedback*; *support*; *about*

for 'Follow Links if link text equals' text box enter following values:
contact; feedback; support; about

for 'Do not Follow links if URL contains' text box enter following values:

google.; yahoo.; bing; msn.; altavista.; myspace.com; youtube.com; googleusercontent.com; =http; .jpg; .gif; .png; .bmp; .exe; .zip; .pdf;

Set 'Maximum Crawling Deapth' to 2

set 'Crawling Order' to Deapth First Crawling

Tick mark below below check boxes:

->Follow all internal links

  Crawling Level 2  Settings

set 'Follow links if link text equals' to below value

*contact*; *feedback*; *support*; *about*

set 'Follow links if url contains' text box to below value

contact; feedback; support; about

set 'DO NOT follow links if url contains' text box to below value

=http

Step 3 After doing above settings now click on Next  -> in Extraction Pattern window -> Click on Define ->  in Web Page Address (URL) give any URL where email is given.  and click on  + sign right of Date Fields to define scraping pattern.

Now inside HTML Structure selects HTML check box or Body check box which means for each page it will take whole page content to parse data.

Now last settings to extract emails from page using regular expression based email extraction function.  Open Predefined Script window and select ‘Extract_Email_Addresses‘ and click on OK. and if you have used page that contains email then in Script Result’ you will be able to see the harvested email.

Hope this will help you to use your Web Content Extractor as a Email Scraper.. Share your view in comment.

Source: http://webdata-scraping.com/use-web-content-extractor-as-email-scraper/

Web Scraping – A trending technique in data science!!!

Web Scraping – A trending technique in data science!!!

Web scraping as a market segment is trending to be an emerging technique in data science to become an integral part of many businesses – sometimes whole companies are formed based on web scraping. Web scraping and extraction of relevant data gives businesses an insight into market trends, competition, potential customers, business performance etc.  Now question is that “what is actually web scraping and where is it used???” Let us explore web scraping, web data extraction, web mining/data mining or screen scraping in details.

What is Web Scraping?

Web Data Scraping is a great technique of extracting unstructured data from the websites and transforming that data into structured data that can be stored and analyzed in a database. Web Scraping is also known as web data extraction, web data scraping, web harvesting or screen scraping.

What you can see on the web that can be extracted. Extracting targeted information from websites assists you to take effective decisions in your business.

Web scraping is a form of data mining. The overall goal of the web scraping process is to extract information from a websites and transform it into an understandable structure like spreadsheets, database or csv. Data like item pricing, stock pricing, different reports, market pricing, product details, business leads can be gathered via web scraping efforts.

There are countless uses and potential scenarios, either business oriented or non-profit. Public institutions, companies and organizations, entrepreneurs, professionals etc. generate an enormous amount of information/data every day.

Uses of Web Scraping:

The following are some of the uses of web scraping:

•     Collect data from real estate listing
•     Collecting retailer sites data on daily basis
•     Extracting offers and discounts from a website.
•     Scraping job posting.
•     Price monitoring with competitors.
•     Gathering leads from online business directories – directory scraping
•     Keywords research
•     Gathering targeted emails for email marketing – email scraping
•     And many more.

There are various techniques used for data gathering as listed below:

•     Human copy-and-paste – takes lot of time to finish when data is huge
•     Programming the Custom Web Scraper as per the needs.
•     Using Web Scraping Softwares available in market.

Are you in search of web data scraping expert or specialist. Then you are at right place. We are the team of web scraping experts who could easily extract data from website and further structure the unstructured useful data to uncover patterns, and help businesses for decision making that helps in increasing sales, cover a wide customer base and ultimately it leads to business towards growth and success.

We have got expertise in all the web scraping techniques, scraping data from ajax enabled complex websites, bypassing CAPTCHAs, forming anonymous http request etc in providing web scraping services.

Source: http://webdata-scraping.com/web-scraping-trending-technique-in-data-science/

Calculate your ROI on Web Scraping using our ROI Calculator

Calculate your ROI on Web Scraping using our ROI Calculator

Staying atop the competition is a vital thing for the survival and growth of businesses these days. Ever since big data came into the picture, web scraping has become something businesses from every industry has to invest in. If your company is not in a technically advanced industry, web scraping could even be a nightmare to start with. Wondering if going with in-house web scraping is right for you? In house or outsourcing, in the end it’s all about the returns on investment.

ROI Calculator

Considering the numerous factors that determine how much web scraping can cost you, it’s not easy to calculate the ROI on your in-house web scraping.

In house web scraping is certainly a challenging process. If you plan on going down this way, here is a brief list of prerequisites.

Engineers

Technically skilled labour is an essential requirement for web scraping. Since, web scraping techniques are complicated, it needs good programming skills to write, run and maintain the scraping bots. The cost of labour can be one of the drawbacks with doing in house web scraping.

Hardware Resources

Web scraping is a resource hungry process which requires high end servers and lots of bandwidth. Without the adequate resources, you might end up losing important data. The cost of quality servers could easily make you want to reconsider doing web scraping on your own. Not to mention the doubling up of these resources in order to keep the data intact, espcially if you’re looking at large scale.

Maintainability and ukeep of your tech stack

Once you have your servers and other technical components setup, the real deal only starts. You have to ensure availability of your servers, data backups, restoring previous states, failovers, among many other complications associated with managing servers and fixing them up when something goes wrong. You need to allocate resources (both people and hardware) to take care of the above.

Time

Time is something that we cannot really include in the equation when it comes to calculating the returns. But it is definitely a factor that defines if web scraping in house is worth it. Although web scraping is the fastest way to acquire data, the initial setup and maintenance are time consuming and complicated. This could easily lead to conflicts when you have to distribute your time between web scraping and other business activities that are crucial for your company.

Try the ROI Calculator

We came up with an ROI calculator to easily calculate your returns on investment with our web scraping services. Using this, you could easily compare the cost of in house web scraping with PromptCloud’s dedicated web scraping services. Find out how much you can save by going the PromptCloud way.

Source: https://www.promptcloud.com/blog/calculate-roi-on-web-scraping

How to use Social Media Scraping to be your Competitors’ Nightmare

How to use Social Media Scraping to be your Competitors’ Nightmare

Big data and competitive intelligence have been in the limelight for quite some time now. The almost magical power of big data to help a company make just the right decisions have been talked about a lot. When it comes to big data, the kind of benefits that a business can get totally depends upon the sources they acquire it from. Social media is one of the best sources from where you can get data that helps your business in a multitude of ways. Now that every business is deep rooted on the internet, social media data becomes all the more relevant and crucial. Here is how you can use data scraped from social media sites to get an edge in the competition.

Keeping watch on your competitors

Social media is the best place to watch your competitors’ activity and take counter initiatives to keep up or take over them. If you want to know what your competitors are up to, a social media scraping setup for scraping the posts that mention your competitors’ brand/product names can do the trick. This can also be used to learn a thing or two from their activities on social media so that you can take respective measures to stay ahead of them. For example, you could know if your competitor is running a special promotional offer at the moment and come up with something better than theirs to keep up. This can do wonders if you are in a highly competitive industry like Ecommerce where the competition is intense. If you are not using some help from web scraping technology to keep a close watch on your competitors, you could easily get left over in this fast-paced business scene.

Solving customer issues at the earliest

Customers are vocal about their experience with different products and services on social media sites these days. If you have a customer whose issue was left unsolved, there is a good chance that he/she will take it to the social media to vent the frustration. Watching out for such instances and giving them prompt support should be something you should do if you want to retain these customers and stop them from ruining your brand’s image. By scraping social media sites for posts that mention your product/service, you can easily find out if there are such grievances from customers. This can make sure to an extent that you don’t let unhappy customers stay that way, which eventually hurts your business in the long run. Customers can make or break your company, so using social media scraping to serve the customers better can help you succeed eventually.

Sentiment analysis

Social media data can play a good job at helping you understand user sentiments. With the help of social media scraping, a business can get the big picture about general perception of their brand by their users. This can go a long way since this level of feedback can help you fix unnoticed issues with your company and service quickly. By rectifying them, you can make your brand more appealing to the customers. Sentiment analysis will provide you with the opportunity to transform your business into how customers want it to be. Social media scraping is the one and only way to have access to this user sentiment data which can help you optimize your business for the customers.

Web crawling for social media data

When social media data possess so much value to businesses, it makes sense to look for efficient ways to gather and use this data. Manually scrolling through millions of tweets doesn’t make sense, this is why you should use social media scraping to aggregate the relevant data for your business. Besides, web scraping technologies make it possible to handle huge amounts of data with ease. Since the size of data is huge when it comes to business related requirements, web scraping is the only scalable solution worth considering. To make things even simpler, there are reliable web scraping solutions that offer social media scraping services for brand monitoring.

Bottom line

Since social media has become an integral part of online businesses, the data available on these sites possess immense value to companies in every industry. Social media scraping can be used for brand monitoring and gaining competitive intelligence that can be used to optimize your business model for maximum effectiveness. This will in turn make your company stand out from the competition and the added advantage of insights gained from social media data will help you to take over your competitors.

Source: https://www.promptcloud.com/blog/social-media-scraping-for-competitive-intelligence

ERP Data Conversions - Best Practices and Steps

ERP Data Conversions - Best Practices and Steps

Every company who has gone through an ERP project has gone through the painful process of getting the data ready for the new system. The process of executing this typically goes through the following steps:

(1) Extract or define

(2) Clean and transform

(3) Load

(4) Validate and verify

This process is typically executed multiple times (2 - 5+ times depending on complexity) through an ERP project to ensure that the good data ends up in the new system. If the data is either incorrect, not well enough cleaned or adjusted or loaded incorrectly in to the new system it can cause serious problems as the new system is launched.

(1) Extract or define

This involves extracting the data from legacy systems, which are to be decommissioned. In some cases the data may not exist in a legacy system, as the old process may be spreadsheet-based and has to be created from scratch. Typically this involves creating some extraction programs or leveraging existing reports to get the data in to a format which can be put in to a spreadsheet or a data management application.

(2) Data cleansing

Once extracted it normally reviewed is for accuracy by the business, supported by the IT team, and/or adjusted if incorrect or in a structure which the new ERP system does not understand. Depending on the level of change and data quality this can represent a significant effort involving many business stakeholders and required to go through multiple cycles.

(3) Load data to new system

As the data gets structured to a format which the receiving ERP system can handle the load programs may also be build to handle certain changes as part of the process of getting the data converted in to the new system. Data is loaded in to interface tables and loaded in to the new system's core master data and transactions tables.

When loading the data in to the new system the inter-dependency of the different data elements is key to consider and validate the cross dependencies. Exceptions are dealt with and go in to lessons learned and to modify extracts, data cleansing or load process in to the next cycle.

(4) Validate and verify

The final phase of the data conversion process is to verify the converted data through extracts, reports or manually to ensure that all the data went in correctly. This may also include both internal and external audit groups and all the key data owners. Part of the testing will also include attempting to transact using the converted data successfully.

The topmost success factors or best practices to execute a successful conversion I would prioritize as follows:

(1) Start the data conversion early enough by assessing the quality of the data. Starting too late can result in either costly project delays or decisions to load garbage and "deal with it later" resulting in an increase in problems as the new system is launched.

(2) Identify and assign data owners and customers (often forgotten) for the different elements. Ensure that not only the data owners sign-off on the data conversions but that also the key users of the data are involved in reviewing the selection criteria's, data cleansing process and load verification.

(3) Run sufficient enough rounds of testing of the data, including not only validating the loads but also transacting with the converted data.

(4) Depending on the complexity, evaluate possible tools beyond spreadsheets and custom programming to help with the data conversion process for cleansing, transformation and load process.

(5) Don't under-estimate the effort in cleansing and validating the converted data.

(6) Define processes and consider other tools to help how the accuracy of the data will be maintained after the system goes live.

Source: http://ezinearticles.com/?ERP-Data-Conversions---Best-Practices-and-Steps&id=7263314

How to Scrape a Website into Excel without programming

How to Scrape a Website into Excel without programming

This web scraping tutorial will teach you visually step by step how to scrape or extract or pull data from websites using import.io(Free Tool) without programming skills into Excel.

Personally, I use web scraping for analysing my competitors’ best-performing blog posts or content such as what blog posts or content received most comments or social media shares.

In this tutorial,We will scrape the following data from a blog:

    All blog posts URLs.
    Authors names for each post.
    Blog posts titles.
    The number of social media shares each post received.

Then we will use the extracted data to determine what are the popular blog posts and their authors,which posts received much engagement from users through social media shares and on page comments.

Let’s get started.

Step 1:Install import.io app

The first step is to install import.io app.A free web scraping tool and one of the best web scraping software.It is available for Windows,Mac and Linux platforms.Import.io offers advanced data extraction features without coding by allowing you to create custom APIs or crawl entire websites.

After installation, you will need to sign up for an account.It is completely free so don’t worry.I will not cover the installation process.Once everything is set correctly you will see something similar to the window below after your first login.

Step 2:Choose how to scrape data using import.io extractor

With import.io you can do data extraction by creating custom APIs or crawling the entire websites.It comes equipped with different tools for data extraction such as magic,extractor,crawler and connector.

In this tutorial,I will use a tool called “extractor” to create a custom API for our data extraction process.

To get started click the “new” red button on the right top of the page and then click “Start Extractor” button on the pop-up window.

After clicking  “Start Extractor” the Import.io app internal browser window will open as shown below.

Step 3:Data scraping process

Now after the import.io browser is open navigate to the blog URL you want to scrape data from. Then once you already navigated to the target blog URL turn on extraction.In this tutorial,I will use this blog URL bongo5.com  for data extraction.

You can see from the window below I already navigated to www.bongo5.com but extraction switch is still off.

Turn extraction switch “ON” as shown in the window below and move to the next step.

Step 4:Training the “columns” or specifying the data we want to scrape

In this step,I will specify exactly what kind of data I want to scrape from the blog.On import.io app specifying the data you want to scrape is referred to as “training the columns”.Columns represent the data set I want to scrape(post titles,authors’ names and posts URLs).

In order to understand this step, you need to know the difference between a blog page and a blog post.A page might have a single post or multiple posts depending on the blog configuration.

A blog might have several blog posts,even hundreds or thousands of posts.But I will take only one session to train the “extractor” about the data I want to extract.I will do so by using an import.io visual highlighter.Once the data extraction is turned on the-the highlighter will appear by default.

I will do the training session for a single post in a single blog page with multiple posts then the extractor will extract data automatically for the remaining posts on the “same” blog page.
Step 4a:Creating “post_title” column

I will start by renaming “my_column” into the name of the data I want to scrape.Our goal in this tutorial is to scrape the blog posts titles,posts URLs,authors names and get social statistics later so I will create columns for posts titles,posts URLs,authors names.Later on, I will teach you how to get social statistics for the post URLs.

After editing “my_column” into “post_title” then point the mouse cursor over to any of the Posts title on the same blog page and the visual highlighter will automatically appear.Using the highlighter I can select the data I want to extract.

You can see below I selected one of the blog post titles on the page.The rectangular box with orange border is the visual highlighter.

The app will ask you how is the data arranged on the page.Since I have more than one post in a single page then you have rows of repeating data.This blog is having 25 posts per page.So you will select “many rows”.Sometimes you might have a single post on a page for that case you need to select “Just one row”.

Source: http://nocodewebscraping.com/web-scraping-for-dummies-tutorial-with-import-io-without-coding/

Three Common Methods For Web Data Extraction

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it into a database.

Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416