How To Access Great Data Sources With Web Scraping
With seemingly endless streaming options, websites, podcasts, advertisements, and news sources, the abundance of content today can be, let’s just say … overwhelming. Trust me; I’ve spent more time browsing Netflix than I’ve spent watching it. In a similar vein, if you are looking at different ways to collect information, it is easy to get lost among so many choices. However, if we know how to ask the right questions and use the right tools, we can make better use of this information and use it to help us understand the world as it is. Whether you’re running a small business or simply conducting research on peoples’ Netflix browsing perspectives, web scraping is integral to understanding and utilizing the massive data resources available worldwide.
While Scraping Robot offers specific scraping modules that you can try for free, our custom scraping solutions have an infinite number of uses. This is because web scraping allows us to tap into an infinite number of data sources on the internet, so we’re constantly discovering new ways to use that data. With so many options at your fingertips, using your imagination to find ways to access different sources will set you above the rest.
If you already know the basics of web scraping, use the table of contents below to find more information on the many ways to use the information scraping provides.
Table of Contents
How to Figure Out Which Data Analysis Sources Are Right For You
Web Scraping is the automated process of extracting and organizing information from web pages. This work can be done manually as well, but using a scraping tool speeds up the process and creates easy to share documents full of useful information.
Basically, you use a scraping tool to quickly retrieve whatever information the web page includes and then the scraper creates an organized spreadsheet with the most important data that is easy to download, share, and analyze.
Once you understand the basics of web scraping, it can be hard to understand know what sources are the best for your situation.
Navigating different data analysis sources
In most scenarios, internal data has the most impact on your goals because it comes from your own business. This includes transactional data, business reviews, and any other direct feedback from consumers. With scraping, you can compile review data into one document making it easier to recognize trends. If a donut shop got constantly negative reviews of one specific flavor, then it is easier for them to see this trend when all the data is side by side as opposed to looking through multiple sources before realizing any trends. Such data is most useful for restaurants, small businesses, and any organization that relies heavily on reviews and word-of-mouth growth. This way, you can make better-informed decisions about the future without doing copious amounts of outside research and development firms.
Social media data is crucial to surviving in any industry. Scraping profiles gives you important information about online behavior, what ads do and do not result in sales, and general thoughts within a community. If your business is active on social media, it is extremely useful to scrape your own profiles to better understand what kinds of content get the most interaction. By learning this, you can make sure to make relevant yet shareable posts moving forward with a better idea of what your viewers/customers want. While the information in this article focuses on different data resources for business, individuals seeking data for other reasons can use this information as well. For example, influencers who make money off of having popular posts can use social media data to better understand what their followers want to see. Or, you may find that you get more engagement when you share recipes or fun videos as opposed to selfies, or vice versa. Even within the personal realm, social media data can help you with a professional or personal brand.
What Are Sources of Big Data?
Big data, defined by Wikipedia, covers the ways we analyze, systemically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. There are common problems that arise with big data, which you can read about here.
Within big data, there are primary data sources and secondary data sources. Primary data sources include social data, machine data, and transactional data. Primary data sources work with data that was collected first-hand through interviews, case studies, and other primary research methods. On the other hand, secondary data sources contain information collected through government departments like housing data, election statistics, or internet searches. Therefore, secondary data sources are aggregators of data.
Primary data sources
As mentioned above, primary data sources include social data, machine data, and transactional data.
Social data is primarily derived from social media sites. This includes likes, comments, shares, follows, and uploads. Social data gives insight into consumer attitudes and behavior which are then used within marketing to anticipate consumer desires. However, not all social data is derived from social media sites. Google Trends and other similar tools can also be used as data analysis sources. With social data, you can better understand the personal preferences of people and their online behavior. Social data is also useful for tracking the popularity of sports figures, celebrities, or any other kind of personal brand.
Machine data is information that is derived from equipment, sensors, and weblogs that track user behavior. This subset of data will likely grow exponentially as there is a rise in the use of medical devices, security cameras, and satellites that collect massive amounts of data. In the restaurant industry, the rise of smart kitchen technology tracks temperatures, inventory, and energy usage automatically and alerts owners of any equipment issues before it is broken beyond repair, saving time and money.
Transactional data, as the name indicates, relates to daily purchases, invoices, storage, and deliveries. This data is especially important to analyze because the data itself is fairly meaningless without being properly organized. By better understanding how people interact with your business (what they buy, when they buy, how they buy) you can make smart decisions about how to change and grow in the future.
Secondary data sources
Secondary data sources cover data was collected by someone else. Most secondary sources consist of data collected in books, newspapers, censuses, governmental records, and other public records.
While the name might make secondary sources seem less useful than primary sources, this couldn’t be further from the truth. For example, scraping public records gives you more varied information at once than primary sources. Secondary sources are also better for recognizing industry trends at large because the data is collected over time and by many sources. Instead of just analyzing your own business with any internal data you create, you can extend your understanding by looking at comparable data from competitors or data collected by government agencies that relate to your field.
How To Use Different Data Sources To Your Advantage
Within this world of seemingly infinite data analysis sources, it can be hard to know how to use this information to move forward and now get overwhelmed. A good place to start is by scraping simple web pages to get a better sense of how scraping tools work and to see what kind of data you get in return. Once you feel comfortable with different scraping methods, you can let your imagination run free.
Using a web scraper, you can analyze various kinds of sources. You can scrape company websites, Amazon products, social media profiles, and more. You can also aggregate sources of data that are useful to your industry. By collecting data from various sources, you can get a bigger picture sense of changes in an industry, while also collecting data specific to the needs of the community you serve.
Scraping Robot’s Tools Help You With Different Sources Of Data
One of the best parts about web scraping services is that you can request custom scraping solutions that fit your exact needs. While the established scraping modules have a variety of uses, you are not limited to them. With the custom module request form, you can directly contact a member of the Scraping Robot team for assistance in finding the best solution for your scraping needs. They may either help you adjust an available module to your needs or create a custom one.
HTML data sources
Scraping the HTML of any website is one of the easiest ways to access data sources from just about anywhere on the internet. Once you have this information, you can analyze the results for the most relevant data. If you have experience with web development, HTML scraping is a great way to make web scraping work for you. If you’re not familiar with web development, you can try pre-built HTML scrapers for free.
While this process may seem fairly basic, its simplicity is what makes it useful for a variety of situations. For example, with this one scraper, you can scrape a competitor’s website, third-party websites with reviews on that same competitor, and aggregation sites — all with the same tool. HTML scraping is particularly useful for secondary data sources because with one scrape you can collect more data than if you went to each primary source individually.
Amazon data sources
For better or worse, Amazon scraping is an integral part of getting ahead in today’s eCommerce marketplace. I habitually check Amazon whenever I look at something online to see if they have the same product for a better price. By scraping Amazon, all you need is the product link, and you will be given pricing data.
This information is of course useful for gauging competitor prices, which can help you set a competitive price. But Amazon’s ubiquity in our society makes it one of the strongest data analysis sources right now. You can browse and compare prices for household products, books, films, electronics, and basically anything sold on Amazon. With the massive amounts of customer reviews on Amazon, it is an essential source of data for every industry.
Social media data sources
Social media sites are sources of data that provide insight into the wants and needs of consumers. By scraping social media accounts, you can discover a person’s followers, following, and other general information. This helps a business to better understand customers on a more emotional and social level than is offered by simple sales analysis.
Social media analysis extends beyond business. It is also useful for recognizing social trends that normal statistics do not pick up on. For example, you can use social media to understand how popular a certain celebrity or public figure is, analyze what kinds of posts become popular, and other metrics that help you create more engaging content. For a writer like me, social media can be a useful way to understand what news stories and topics generate the most discussion. If I can find stories that tap into the national debate, I am more likely to get my work published and shared.
While I know it can seem like data analysis is mostly for use by larger businesses, social media can be a great way for small businesses to understand the unique needs of their community and discover what content engages and supports those needs.
Final Thoughts About Data Sources
In an era where data collecting is growing and growing, it is an essential skill to understand how to navigate various data sources in order to perform the best analysis. However, it can be hard to know where to start with seemingly infinite options. With the development of big data, it is easier than ever to collect and organize massive data sets. With web scraping, you can analyze big sets of data quickly and thoroughly without weeks of manual labor.
While scraping robot’s modules are built for specific sites, there are so many ways to utilize them personally and professionally. Whether scraping primary or secondary sources, our HTML, Amazon, and social media scrapers help you understand trends within an industry or social trends at large. Above all, our custom module request allows you to unleash your creativity and suggest new ways to think about scraping data and moving forward.
The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.
