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/

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

Data Extraction/ Web Scraping Services

Making an informed business decision requires extracting, harvesting and exploiting information from diverse sources. Data extraction or web scraping (also known as web harvesting) is the process of mining information from websites using software, substantiated with human intelligence. The content 'scraped' from web sources using algorithms is stored in a structured format, so that it can be manually analyzed later.

Case in Point: How do price comparison websites acquire their pricing data? It is mostly by 'scraping' the information from online retailer websites.

We offers data extraction / web scraping services for retrieving data for advanced data processing or archiving from a variety of online sources and medium. Nonetheless, data extraction is a time consuming process, and if not conducted meticulously, it can result in loads of errors. A leading web scraping company, we can deliver required information within a short turnaround time, employing an extensive array of online sources.

Our Process Of Data Extraction/ Web Scraping, Involves:

- Capturing relevant data from the web, which is raw and unstructured
- Reviewing and refining the obtained data sets
- Formatting the data, consistent with the requirements of the client
- Organizing website and email lists, and contact details in an excel sheet
- Collating and summarizing the information, if required

Our professionals are adept at extracting data pertaining to your competition, their pricing strategy, gathering information about various product launches, their new and innovative features, etc., for enterprises, market research companies or price comparison websites through professional market research and subject matter blogs.

Our key Services in Web Scraping/ Database Extraction include:

We offer a comprehensive range of data extraction and scraping services right from Screen Scraping, Webpage / HTML Page Scraping, Semantic / Syntactic Scraping, Email Scraping to Database Extraction, PDF Data Extraction Services, etc.

- Extracting meta data from websites, blogs, and forums, etc.
- Data scraping from social media sites
- Data quarrying for online news and media sites from different online news and PR sources
- Data scraping from business directories and portals
- Data scraping pertaining to legal / medical / academic research
- Data scraping from real estate, hotels & restaurant, financial websites, etc.

Contact us to outsource your Data Scraping / Web Extraction Services or to-  learn more about our other data related services.

Source Url :-http://www.data-entry-india.com/data-extraction-web-scraping-services.html

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