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.

The next article of this series will give more details about how such softwares and uncover some myths on web harvesting.


Article Source: http://EzineArticles.com/expert/Thomas_Tuke/5484

Data Collection - Make a Plan

Planning for the data collection activity provides a stable and reliable data collection process in the Measure phase.

A well-planned activity ensures that your efforts and costs will not be in vain. Data collection typically involves three phases: pre-collection, collection and post-collection.

Pre-collection activities: Goal setting and forming operational definitions are some of the pre-collection activities that form the basis for systematic and precise data collection.

1.  Setting goals and objectives: Goal setting and defining objectives is the most important part of the pre-collection phase.

It enables teams to give direction to the data to be collected. The plan includes description of the Six Sigma project being planned. It lists out specific data that is required for the further steps in the process.

If there are no specific details as to the data needs, the data collection activity will not be within scope - and may become irrelevant over a period of time.

The plan must mention the rationale of data being collected as well as the final utilization.

2.  Define operational definitions: The team must clearly define what and how data has to be collected. An operational definition of scope, time interval and the number of observations required is very important.

If it mentions the methodology to be used, it can act a very important guideline to all data collection team members.

An understanding of all applicable information can help ensure that there no misleading data is collected, which may be loosely interpreted leading to a disastrous outcome.

3.  Repeatability, stability and accuracy of data: The repeatability of the data being collected is very important.

This means that when the same operator undertakes that same activity on a later date, it should produce the same output. Additionally, it is reproducible if all operators reach the same outcome.

Measurement systems should be accurate and stable, such that outcomes are the same with similar equipment over a period of time.

The team may carry out testing to ensure that there is no reduction in these factors.

Collection Activity

After planning and defining goals, the actual data collection process starts according to plan. Going by the plan ensures that teams achieve expected results consistently and accurately.

Training can be undertaken so as to ensure that all data collection agents have a common understanding of data being collected. Black Belts or team leaders can look over the process initially to provide any support needed.

For data collection over a longer period, teams need to ensure regular oversight to ensure that no collection activities are overlooked.

Post collection activities

Once collection activities are completed, the accuracy and reliability of the data has to be reviewed.

Source: http://ezinearticles.com/?Data-Collection---Make-a-Plan&id=2792515

How Web Crawling Can Help Venture Capital Firms

Venture capital firms are constantly on the lookout of innovative start-ups for investment. Whether you provide financial capital to early-stage start-ups in IT, software products, biotechnology or other booming industries, you will need the right information as soon as possible. In general, analysing media data to discover and validate insights is one of key areas in which analysts work. Hence, constantly monitoring popular media outlets is one of the ways VCs can deploy to spot trends. Read on to understand how web crawling can not only speed up this whole process but also improve the workflow and accuracy of insights.

What is web crawling

Web crawling simply refers to the use of automated computer programs to visit websites and extract specific bits of information. This is the same technology used by search engines to find, index and serve search results for user queries. Web crawling, as you’d have guessed is a technical and niche process. It takes skilled programmers to write programs that can navigate through the web to find and extract the needed data.

There are DIY tools, vertical specific data providers and DaaS (Data as a service) solutions that VC firms can deploy for crawling.  Although there is the option of setting up an in-house crawling setup, this isn’t recommended for Venture Capital firms. The high tech-barrier and complexity of web crawling process can lead to loss of focus for the VC firms. DaaS can be the ideal option as it’s suitable for recurring and large-scale requirements which only a hosted solution can offer.

How web crawling can help Venture Capital firms

Crawling start-up and entrepreneurship blogs using a web crawling service can help VC firms avail the much-needed data that they can use to discover new trends and validate their research. This can complement the existing research process and make it much more efficient.

1. Spot trends

Spotting new trends in the market is extremely important for venture capital firms. This helps identify the niches that have high probability of bringing in profit. Since investing in companies that have higher chances of succeeding is what Venture capital firms do, the ability to spot trends becomes an invaluable tool.

Web crawling can harvest enough data to identify trends in the market. Websites like Techcrunch and Venturebeat are great sources of start-up related news and information. Media sites like these talk about trending topics constantly. To spot trends in the market, you could use a web crawling solution to extract the article title, date and URL for the current time period and run this data through an analytics solution to identify the most used words in the article titles and URLs. Venture capital firms can then use these insights to target newer companies in the trending niches. Technology blogs, forums and communities can be great places to find relevant start-ups.

2. Validate findings

The manual research by the analysts needs to be validated before the firm can go ahead with further proceedings. Validation can be done by comparing the results of the manual work with the relevant data extracted using web crawling. This not only makes validation much easier but also helps in the weeding out process, thus reducing the possibilities of making mistakes. This can be partially automated by using intelligent data processing/visualisation tools on top the data.

3. Save time

Machines are much faster than humans. Employing web crawling to assist in the research processes in a venture capital firm can save the analysts a lot of time and effort. This time can be further invested in more productive activities like analytics, deep research and evaluation.

Source:-https://www.promptcloud.com/blog/web-crawling-for-venture-capital-firms