Thursday 28 September 2017

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.


Article Source: http://EzineArticles.com/3860679

Tuesday 26 September 2017

Data Collection Techniques for a Successful Thesis

Irrespective of the grade of the topic and the subject of research you have chosen, basic requirement and process of all remains same i.e. "research". Re-search in itself means searching on a searched content and this involves some proven fact along with some practical figures reflecting the authenticity and reliability of the study. These facts and figures which are required to prove the fundamentals of study are known as "data's".

These data's are collected according to the demand of research topic and its study undertaken. Also their collection techniques vary along with the topic in detail for example if the topic is like "Changing era of HR policies", the demanded data would be subjective and its technique thus depends on the same. Whereas if the topic is like "Causes of performance appraisal", then the demanded data would be objective and in the terms of figures which shows different parameters, reasons and factors affecting performance appraisal of different number of employees. So, let's have a broader look on the different data collection techniques which gives a reliable ground to your research -

• Primary Technique - Here, the data is collected by the first hand source directly are known as primary data's. Self-analysis is a sub classification of primary data collection - As understood; here you get self-response for a set of questions or a study. For example - personal in-depth interviews and questionnaires are self-analyzed data collection techniques, but its limitation lies in the fact that self-response can be sometimes biased or even confused. On the other, hand the advantage is in the court of most updated data as it is directly collected from the source.

• Secondary Technique - In this technique the data is collected from the pre-collected resources they are called as secondary data's. Data's are collected from articles, bulletins, annual reports, journals, published papers, government and non-government documents and case studies. Limitation of these is that they may not be the updated one or may be manipulated as it is not collected by the researcher itself.

Secondary data is easy to collect as they are pre-collected and are preferred when there is lack of time whereas primary data's are tough to amass. Thus, if researcher wants to bring up to date, reliable and factual data's they should prefer primary source of collection. But, these data collection techniques vary according to problem generated in the thesis. Hence, go through the demands of your thesis first before indulging yourself into data collection.

Source: http://ezinearticles.com/?Data-Collection-Techniques-for-a-Successful-Thesis&id=9178754

Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

Source: http://ezinearticles.com/?Data-Collection,-Just-Another-Way-To-Gather-Information&id=853158

Monday 25 September 2017

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