Various Methods of Data Collection

Professionals in all the business industries widely use research, whether it is education, medical, or manufacturing, etc. In order to perform a thorough research, you need to follow few suitable steps regarding data collection. Data collection services play an important role in performing research. Here data is gathered with appropriate medium.

Types of Data

Research could be divided in two basic techniques of collecting data, namely: Qualitative collection of data and quantitative collection. Qualitative data is descriptive in nature and it does not include statistics or numbers. Quantitative data is numerical and includes a lot of figures and numbers. They are classified depending on the methods of its collection and its characteristics. Data collected primarily by the researcher without depending on pre-researched data is called primary data. Interviews as well as questionnaires are generally found primary data/information collection techniques. Data collected from other means, other than by the researcher is secondary data. Company surveys and government census are examples of secondary collection of information.

Let us understand in detail the methods of qualitative data collection techniques in research.

Internet Data: Here there is a huge collection of data where one gets a huge amount of information for research. Researchers remember that they depend on reliable sources on the web for precise information.
Books and Guides: This traditional technique is authentically used in today's research.

Observational data: Data is gathered using observational skills. Here the data is collected by visiting the place and noting down details of all that the researcher observes which is needed for essential for his research.

Personal Interviews: Increases authenticity of data as it helps to collect first hand information. It does not serve fruitful when a big number of people are to be interviewed.

Questionnaires: Serves best when questioning a particular class. A questionnaire is prepared by the researcher as per the need of data-collection and forwarded to responders.

Group Discussions: A technique of collecting data where the researcher notes down details of what people in a group has to think. He comes to a conclusion depending on the group discussion that involves debate on topics of research.

Use of experiments: To obtain the complete understanding researchers conduct real experiments in the field used mainly in manufacturing and science. It is used to obtain an in-depth understanding of the researching subject.

Data collection services use many techniques including the above mentioned for collection. These techniques are helpful to the researcher in drawing conceptual and statistical conclusions. In order to obtain precise data researchers combine two or more of the data collection techniques.


Article Source: http://EzineArticles.com/5906957

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

How Hedge Funds Can Use Web Scraping

How Hedge Funds Can Use Web Scraping

Web scraping or data extraction is the need of the hour to make sense of the huge and varied data being generated across multiple sources on the web. Irrespective of the sector you are working in, data extraction and mining is a crucial necessity to glean insights into consumer behavior, market forces, competitive intelligence, and price movements, and assist in management decision making.

There’s no denying the fact that numerous brands and enterprises are leveraging data extraction for further development and growth. Of late, hedge fund owners too are showing a huge affinity to utilizing the prowess of web scraping for unlocking new investment opportunities.

What we need to know is how web scraping is helping out hedge fund owners. What is it that makes web scraping essential for them and how can they use the technology to their advantage?
Fund management with web scraping

For a majority of discretionary fund managers, web scraping is a relatively new term. Although data scientists are aware of the concept, they might not have the right skills that lead to effective use of web scraping and data extraction. So, how does hedge fund management take place now? Let’s take a look at the current processes.

Most of the hedge funds have dedicated and centralized teams looking after the data extraction process. They have a group which is continuously looking for crucial data thus extracting it for more information. Once they find what they are looking for, they seek assistance from skilled data scientists who prepare comprehensive reports on the key findings. Based on these reports, managers have to take significant steps and implement crucial business strategies.

It’s here that the major problem arises. Most of these managers aren’t aware of the technicalities involved in data extraction. They don’t know what to do with these reports when it comes to devising business strategies.
The need for effective techniques

What you need is a comprehensive and integrated approach towards the entire process. Data scientists and business managers should have crystal clear understanding of web scraping thus working in tandem for better results. Here’s how they can work together:

1. Portfolio managers: PMs will need to develop a comprehensive understanding of trading strategies along with the power to explain his understandings. He should have the power to identify alpha opportunities.

2. Data scientists: Data scientists should know the art of data mining thus ingesting the findings into a database.

Simultaneous operations should take place where PMs, data scientists, and web scraping experts will take active parts. In a nutshell, business owners need highly efficient quant teams capable of extracting quant data sets.
The steps around web scraping for hedge funds

If you are managing hedge funds, data extraction and web scraping will be essential for you. Before knowing how to use this particular technique, make sure you gain information about the crucial steps that lead to web scraping.

•   Gaining access to data sets: Without the right data sets, it is impossible to perform web scraping. Data scientists and PMs must put their best efforts to find the correct information. It can come from internal divisions, external publications, or even from social media.

•   Understanding the financial drivers: You should know about the financial drivers involved in the process. Web scraping will depend on these key drivers to a great extent.

•   Quant vs. fundamental: There’s always a debate between data quants and fundamental knowledge. The prime emphasis should always be on identifying the insights, working on them, and turning them into effective actions.

With these steps in mind, you can plan the fund management process in detail thus taking the venture towards unsurpassed growth. Hedge fund owners have been relying on fundamental knowledge since a long time; it is high time they made a move and embraced web scraping.

Current positions and prospects

If market reports are anything to go by, you will come across nearly 70 hedge funds who claim to leverage big data. Once you take a closer look, the entire situation will get revealed. Only 20 amongst these 70 hedge funds work with Big Data and rely on web scraping techniques. Market reports also suggest that only a few of them are good at performing the process.

Web scraping is going to be the future! Just after a few years, hedge fund owners will have to rely on web scraping for effective fund management. Therefore, it’s high time to upgrade performances, processes, and operations. Those getting introduced to the concept for the first time should learn the art of performing web scraping and data extraction.

Building strong and effective financial models

Do you feel the existing infrastructure is enough to leverage web scraping? That’s not true, as there are numerous other aspects involved in the process. The presence of a strong and reliable financial model is of paramount significance. Financial models play a highly significant part in the utilization of technologies. If you are thinking of implementing web scraping, check the financial infrastructure and support your venture offers to you.

The third wave

Before the emergence of web scraping and data extraction, hedge fund owners relied on traditional data mining techniques. Those weren’t effective to a great extent, as they failed to offer targeted insights into the extraction process.

It’s here that the need for a third wave came up, and web scraping was what we all waited for. With this new and innovative technology, hedge fund managers will be able to utilize insights to stay ahead of the growth curve!

Final thoughts

Hedge fund management involves quite a few significant processes in order to yield the benefits expected by senior management of the company. However, if you are planning to use web scraping, it is important to know the right tips to do so. Most of the data scientists want to bridge the gap between fundamental fund management and web scraping. It is quite obvious that the latter is beneficial in the long run. With these tips and web scraping techniques in mind, you can ensure targeted hedge fund management and handling.

Source:https://www.promptcloud.com/blog/how-hedge-funds-can-use-web-scraping

The Ultimate Guide to Web Data Extraction

Web data is of great use to Ecommerce portals, media companies, research firms, data scientists, government and can even help the healthcare industry with ongoing research and making predictions on the spread of diseases.

Consider the data available on classifieds sites, real estate portals, social networks, retail sites, and online shopping websites etc. being easily available in a structured format, ready to be analyzed. Most of these sites don’t provide the functionality to save their data to a local or cloud storage. Some sites provide APIs, but they typically come with restrictions and aren’t reliable enough. Although it’s technically possible to copy and paste data from a website to your local storage, this is inconvenient and out of question when it comes to practical use cases for businesses.



Web scraping helps you do this in an automated fashion and does it far more efficiently and accurately. A web scraping setup interacts with websites in a way similar to a web browser, but instead of displaying it on a screen, it saves the data to a storage system.

Applications of web data extraction
1. Pricing intelligence

Pricing intelligence is an application that’s gaining popularity by each passing day given the tightening of competition in the online space. E-commerce portals are always watching out for their competitors using web crawling to have real time pricing data from them and to fine tune their own catalogs with competitive pricing. This is done by deploying web crawlers that are programmed to pull product details like product name, price, variant and so on. This data is plugged into an automated system that assigns ideal prices for every product after analyzing the competitors’ prices.

Pricing intelligence is also used in cases where there is a need for consistency in pricing across different versions of the same portal. The capability of web crawling techniques to extract prices in real time makes such applications a reality.

2. Cataloging

Ecommerce portals typically have a huge number of product listings. It’s not easy to update and maintain such a big catalog. This is why many companies depend on web date extractions services for gathering data required to update their catalogs. This helps them discover new categories they haven’t been aware of or update existing catalogs with new product descriptions, images or videos.

3. Market research

Market research is incomplete unless the amount of data at your disposal is huge. Given the limitations of traditional methods of data acquisition and considering the volume of relevant data available on the web, web data extraction is by far the easiest way to gather data required for market research. The shift of businesses from brick and mortar stores to online spaces has also made web data a better resource for market research.

4. Sentiment analysis

Sentiment analysis requires data extracted from websites where people share their reviews, opinions or complaints about services, products, movies, music or any other consumer focused offering. Extracting this user generated content would be the first step in any sentiment analysis project and web scraping serves the purpose efficiently.

5. Competitor analysis

The possibility of monitoring competition was never this accessible until web scraping technologies came along. By deploying web spiders, it’s now easy to closely monitor the activities of your competitors like the promotions they’re running, social media activity, marketing strategies, press releases, catalogs etc. in order to have the upper hand in competition. Near real time crawls take it a level further and provides businesses with real time competitor data.

6. Content aggregation

Media websites need instant access to breaking news and other trending information on the web on a continuous basis. Being quick at reporting news is a deal breaker for these companies. Web crawling makes it possible to monitor or extract data from popular news portals, forums or similar sites for trending topics or keywords that you want to monitor. Low latency web crawling is used for this use case as the update speed should be very high.

7. Brand monitoring

Every brand now understands the importance of customer focus for business growth. It would be in their best interests to have a clean reputation for their brand if they want to survive in this competitive market. Most companies are now using web crawling solutions to monitor popular forums, reviews on ecommerce sites and social media platforms for mentions of their brand and product names. This in turn can help them stay updated to the voice of the customer and fix issues that could ruin brand reputation at the earliest. There’s no doubt about a customer-focused business going up in the growth graph.

Source url :-https://www.promptcloud.com/blog/ultimate-web-data-extraction-guide

Six Tools to Make Data Scraping More Approachable

What is data scraping?

Data scraping is a technique in which a computer program/software extracts data from a website, so it can be used for other purposes.Scraping may sound a little intimidating, but with the help of scraping tools, the process can be a lot more approachable. The tools are used to capture data you need from specific web pages quicker and easier.

Let your computer do all the work

It takes only a few minutes for systems to recognize each others codes even in huge databases. Computers have their own language and that is why some of these tools make it easier to pull and format information in a way that is simpler for people to reuse.

Here is a list of some data scraping tools:

1.Diffbot

What makes this tool so likable is the business-friendly approach. Tools like Diffbot are perfect for searching through competitors work and the performance of your own webpage. Get product data from images, articles, discussions, web crawling tools and process websites. If you like how this sounds, see for yourself and sign up for their 14-day free trial.


2.Import.io

Import.io can help you easily get the information from the any source on the web. This tool can get your data in less than 30 seconds, depending on how complicated the data is and its structure in the website.  It can also be used for multiple URL scraping at once.

Here is one example: Which city of California based organizations try to hire the most through Linkedin? Check this list of jobs available in linkedin, download a csv file, sort from A to Z the cities and voila – San Francisco it is. Did you know that it’s for free?

3.Kimono

Kimono gives you easy access to APIs created for various web pages. No need to write any code or install any software to extract data. Simply paste the URL into the website or use a bookmark. Select how often you want the data to be collected and it saves it for you.

4.ScraperWiki

ScraperWiki gives you two choices – extract data from PDFs or build your own scraping tool in PHP, Ruby and Python language. It is meant for more experienced users and offers consulting (a paid service) if you need to learn some coding to get what you need. The first two PDF files are analyzed and reorganized for free, afterwards it’s a paid solution.

5.Grabz.it

Yes, Grabz.it does grab something. It takes information that is meaningful to you. The tool extracts data from the web, then converts videos into animated GIF that you can use on your website or application. This tool was made for those who code in ASP.NET, Java, JavaScript, Node.js, Perl, PHP, Python and Ruby languages.

6.Python

If programming is the language you love the most, then use Python to build your own scraping tool and get the data from a page you want to explore. It is particularly useful if the other tools don’t recognize the data you need.

If you haven’t used this tool before, follow this playlist of videos to learn how to use Python for web scraping:

If you want more tools, look into the Common Crawl organization. It is made for those who are interested in the data crawling world. Need a more specific tool? DMOZ and KDnuggets have lists of other tools for web data mining.

All of these tools extract information in spreadsheet formats and that is why this webinar about how to work with data in Excel can help you understand more about what to do if you desire  to supply the world with unique and beautifully data visualizations.



Source Url:-https://infogr.am/blog/six-tools-to-make-data-scraping-more-approachable/

Things to Consider when Evaluating Options for Web Data Extraction

Things to Consider when Evaluating Options for Web Data Extraction

Web data extraction possess tremendous applications in the business world. There are businesses that function solely based on data, others use it for business intelligence, competitor analysis and market research among other countless use cases. While everything is good with data, extracting massive data from the web is still a major roadblock for many companies, more so because they are not going through the optimal route. We decided to give you a detailed overview of different ways by which you can extract data from the web. This could help you make the final call while evaluating different options for web data extraction.

Different routes you can take to web data

Although different solutions exist for web data extraction, you should opt for the one that’s most suited for your requirement. These are the various options you can go with:

1. Build it in-house

2. DIY web scraping tool

3. Vertical-specific solution

4. Data-as-a-Service

1.   Build it in-house

If your company is technically rich, meaning you have a good technical team that can build and maintain a web scraping setup, it makes sense to build a crawler setup in-house. This option is more suitable for medium sized businesses with simpler requirements when it comes to data. However, building an in-house setup is not the biggest challenge- maintaining it is. Since web crawlers are really fragile and are vulnerable to the changes on target websites, you will have to dedicate time and labour into the maintenance of the in-house crawling setup.

Building your own in-house setup will not be easy if the number of websites you need to scrape are high or the websites aren’t using simple and traditional coding practices. If the target websites use complicated dynamic code, building your in-house setup becomes a bigger hurdle. This can hog your resources especially if extracting data from the web is not a competency of your business. Scaling up with your in-house crawling setup could also be a challenge as this would require high end resources, an extensive tech stack and a dedicated internal team. If your data needs are limited and the target websites simple, you can go ahead with an in-house crawling setup to cover your data needs.

Pros:

- Total ownership and control over the process
- Ideal for simpler requirements

2.   DIY scraping tools

If you don’t want to maintain a technical team that can build an in-house crawling setup and infrastructure, don’t worry. DIY scraping tools are exactly what you need. These tools usually require no technical knowledge as such and can be used by anyone who is good with the basics. They usually come with a visual interface where you can configure and deploy your web crawlers. The downside however, is that they are very limited in their capabilities and scale of operation. They are an ideal choice if you are just starting out with no budgets for data acquisition. DIY web scraping tools are usually priced very low and some are even free to use.

Maintenance would still be a challenge that you have to face with the DIY tools. As web crawlers are susceptible to becoming useless with minor changes in the target sites, you still have to maintain and adapt the tool from time to time. The good part is that it doesn’t require technically sound labour to handle them. Since the solution is readymade, you will also save the costs associated with building your own infrastructure for scraping.

With DIY tools, you will also be sacrificing on the data quality as these tools are not known for providing data in a ready to consume format. You will either have to employ an automated tool to check the data quality or do it manually. With these downsides apart, DIY tools can cater to simple and small scale data requirements. 

Pros:

- Full control over the process
- Prebuilt solution
- You can avail support for the tools
- Easier to configure and use

3.   Vertical-specific solution

You might be able find a data provider catering to only a specific industry vertical. If you could find one that has data for the industry that you are targeting, consider yourself lucky. Vertical specific data providers can give you data that is comprehensive in nature which improves the overall quality of the project. These solutions typically give you datasets that are already extracted and is ready to use.

The downside is the lack of customisation options. Since the provider is focusing on a specific industry vertical, their solution is less flexible to be altered depending on your specific requirements. They won’t let you add or remove data points and the data is given as is. It will be hard to find a vertical-specific solution that has data exactly the way you want. Another important thing to consider is that your competitors have access to the same data from these vertical-specific data providers. The data you get is hence less exclusive, but this may or may not be a deal breaker depending upon your requirement.

Pros:

- Comprehensive data from the industry
- Faster access to data
- No need to handle the complicated aspects of extraction

4.   Data as a service (DaaS)

Getting the required data from a DaaS provider is by far the best way to extract data from the web. With a data provider, you are completely relieved from the responsibility of crawler setup, maintenance and quality inspection of the data being extracted. Since these are companies specialised in data extraction with a pre-built infrastructure and dedicated team to handle it, they can provide this service to you at a much lower cost than what you’d incur with an in-house crawling setup.

In the case of a DaaS solution, all you have to do is provide them with your requirements like the data points, source websites, frequency of crawl, data format and the delivery methods. DaaS providers have high end infrastructure, resources and expert team to extract data from the web efficiently.

They will also have far superior knowledge in extracting data efficiently and at scale. With DaaS, you also have the comfort of getting data that’s free from noise and is formatted properly for compatibility. Since the data goes through quality inspections at their end, you can focus only on  applying data to your business. This can greatly reduce the workload on your data team and improve the efficiency.

Customisation and flexibility are other great advantages that come with a DaaS solution. Since these solutions are meant for the large enterprises, their offering is completely customisable for your exact requirements. If your requirement is large scale and recurring, it’s always best to go with a DaaS solution.

Pros:

- Completely customisable for your requirement
- Takes complete ownership of the process
- Quality checks to ensure high quality data
- Can handle dynamic and complicated websites
- More time to focus on your core business

Source:https://www.promptcloud.com/blog/choosing-a-data-extraction-service-provider

3 Advantages of Web Scraping for Your Enterprise

In today’s Internet-dominated world possessing the relevant information for your business is the key to success and prosperity. Harvested in a structural and organized manner, the information will help facilitate business processes in many ways, including, but not limited to, market research, competition analysis, network building, brand promotion and reputation tracking. More targeted information means a more successful business and with the widespread competition in place, the strive for better performances is crucial.

The results of data harvesting prove to be an invaluable assistance in the age when you have the need to be informed and if you want to stand your chance in the highly competitive modern markets. This is the reason why web data harvesting has long become an inevitable component of a successful enterprise and it is a highly useful tool in both kick-starting and maintaining a functioning business by providing relevant and accurate data when needed.

However good your product or service is, the simple truth is that no-one will buy it if they don't want it or believe that they don't need it. Moreover, you won't persuade anyone that they want or need to buy what you're offering unless you clearly understand what it is that your customers really want. This way, it is crucial to have an understanding of your customers’ preferences. Always remember - they are the kings of the market and they determine the demand. Having this in mind, you can use web data scraping to get the vital information and be able to make the crucial, game-changing decisions to make your enterprise the next big thing.

Enough about how awesome web scraping is in theory! Now, let’s zoom in on 3 specific and tangible advantages that it can provide for your business, helping You benefit from them.

1. Provision of huge amounts of data

It won’t come as a surprise to anyone that there is an overflowing demand for new data for businesses across the globe. This happens because the competition increases day by day. Thus, the more information you have about your products, competitors, market etc. the better are your chances of expanding and persisting in the competitive business environment. This is a challenge but your enterprise is in luck because web scraping is specifically designed to collect the data which can be later used to analyse the market and make the necessary adjustments. But if you think that collecting data is as simple as it sounds and there is no sophistication involved in the process, think again: simply collecting data is not enough. The manner in which data extraction processes flow is also very important; as mere data collection itself is useless. The data needs to be organized and provided in a useable format to be accessible to wide masses. Good data management is key to efficiency. It’s instrumental to choose the right format, because its functions and capacities will determine the speed and productivity of your efforts, especially when you deal with large chunks of data. This is where excellent data scraping tools and services come in handy. They are widely available nowadays and are able to satisfy your company’s needs in a professional and timely manner.

2.  Market research and demand analyses

Trends and innovations allow you to see the general picture of your industry: how it’s faring today, what’s been trendy recently and which ones faded quickly. This way, you can avoid repeating mistakes of unsuccessful businesses, as well as, foresee how well yours will do, and possibly predict new trends.

Data extraction by web crawling will also provide you with up-to-date information about similar products or services in the market. Catalogues, web stores, results of promotional campaigns – all that data can be harvested. You need to know your competitors, if you want to be able to challenge their positions on the market and win over customers from them.

Furthermore, knowledge about various major and minor issues of your industry will help you in assessing the future demand of your product or service. More importantly, with the help of web scraping your company will remain alert for changes, adjustments and analyses of all aspects of your product or service.

3.  Business evaluation for intelligence

We cannot stress enough the importance of regularly analysing and evaluating your business. It is absolutely crucial for every business to have up-to-date information on how well they are doing and where they are amongst others in the market. For instance, if a competitor decides to lower the prices in order to grow their customer base you need to be prepared whether you can remain in the industry despite lowering prices. This can only be done with the help of data scraping services and tools.

Moreover, extracted data on reviews and recommendations from specific websites or social media portals will introduce you to the general opinion of the public. You can also use this technique to identify potential new customers and sway their opinions in your favor by creating targeted ads and campaigns.

To sum it up, it is undeniable that web scraping is a proven practice when it comes to maintaining a strong and competitive enterprise. Combining relevant information on your industry, competitors, partners and customers with thought-out business strategies and promotional campaigns, as well as, market research and business analyses will prove to be a solid way of establishing yourself in the market. Whether you own a startup or a successful company, keeping a finger on the pulse of the ever-evolving market will never hurt you. In fact, it might very well be the single most important advantage that will differentiate you from your competitors.

Source Url :- https://www.datahen.com/blog/3-advantages-of-web-scraping-for-your-enterprise