When you hear the term ‘Big Data,’ it conjures images of a large data conglomerate stepping on the neck of small data. In reality, the truth is much different. While we are used to the terms “Big Pharma,” “Big Agriculture,” it is wrong to assume big data infers the same dynamic. In fact, big data simply represents data sets that are too large to be managed using typical data management techniques. Instead, you must learn to collect, analyze, and manage massive amounts of data.
For businesses that use large scale data, it can be hard to know where to begin. Data collection can include patient data in the medical field, ratings data in the entertainment industry, and sentiment analysis in marketing. Collecting information is only worthwhile if the information itself is useful and clear. Web scraping is a useful tool when it comes to managing and analyzing vast amounts of data. Once you have a data analysis routine down, you will be better equipped to make data-informed decisions and even find ways to supplement that data.
If you know the basics of large scale data analysis, then use the table of contents to discover how to properly manage massive amounts of data.
Table of Contents
What is Large Scale Data?
Large Scale Data, sometimes called Big Data, is a term used to describe large amounts of data that are hard to manage, analyze, and use. Even though having a multitude of data points can make your insights more accurate, you need to be able to handle the quantity before gleaning anything from it. Once you learn how to manage large scale data sets, you will make informed decisions, be able to better predict industry changes, and improve your product or service. Read more on how big data is impacting sustainability.
A common way of collecting large scale data is web scraping, the automatic process of extracting information from web pages. You use a scraper to parse through a certain set of data, the scraper extracts it, and then it is organized and downloaded to be shared amongst a team. Scraping works quickly unlike manual data extraction and can work with large quantities of data at once. This makes scraping perfect for small business owners that can’t afford to have an entire department dedicated to data collection. It is also useful in a myriad of industries because the process is simple and doesn’t require tons of technical knowledge, making scraping a useful skill for anyone to have.
How to Collect Large Scale Data
Web scraping is the automatic process of extracting information from web pages and exporting it into a shareable format. Because of this, web scraping is the perfect tool for collecting large data sets. Below are different ways you can use scraping tools for data extraction.
Social media is a data goldmine. When you scrape a social media profile, you get information regarding their followers, what accounts they’re following, and their interests. This data helps you understand your consumer base at a deeper level and even discover a new target audience. You can also scrape trending topics or keywords if you are looking for specific data on how social media users react to a certain topic. For example, If you are scraping social media to look for people who might be interested in your eco-friendly cleaning products, you will likely find potential customers by looking at who tweets the most about being eco-friendly or climate change policy demands.
For businesses focused on selling through eCommerce sites like eBay and Amazon, these sites are luckily full of important sales data and customer data. The vast amount of reviews under each product can be scraped to have a set of opinions on which parts of the production is lacking. You can also scrape pricing info, trending items, and product details. Not only are these sites great sources of data, but they are also constantly updating making them a source you can return to again and again to track industry changes and generate new insights.
By scraping google and google places, you can collect data on the top search results for a given keyword or scrape google places to find the top locations for a given city or keyword. For example, if I scrape for top restaurant results in Kansas City and find many of them to be barbecue spots, I may think twice about opening a competing restaurant and find a less competitive location. Because Google is a go-to search engine for many, the results are also based on millions of searches.
How to Analyze Large Data Sets
Once you collect all this data, you might be wondering what to do with it. Analyzing data takes a lot of hard work, but web scraping helps here too. Since scrapers organize the data to a certain extent, it becomes easier to analyze. Below are examples of ways to use large data sets despite the challenges.
While the world is always changing in unpredictable ways, there are certain predictions that data can indicate. Financial analytics help manage large and varied sets of data to predict trends in a given industry. By using data to forecast future trends, you can stay ahead of the competition and anticipate the desires and needs of consumers. The future is always uncertain, but web scraping gives you a small sense of what to expect. This is essential for industries like fashion or entertainment that need to be ahead of trends and also is important information for businesses trying to create new products that will attract new customers.
For individuals selling their goods online or running a small business, it can be prohibitively expensive to hire more staff. Learning how to analyze large scale data processing from web scraping on your own can help save you money. Instead of having to develop an entire data department, you can simply depend upon web scraping tools and data analytics. Additionally, for small businesses that don’t have the funds to run focus groups or more expensive forms of research, using scraping to do customer sentiment analysis or market research saves you time and money that outsourcing would require. Outside of anticipating needs, scraping can be akin to a brainstorming assistant since it helps you recognize patterns in data that help you think differently about an issue. Read our blog about using scraping to collect creative data that inspires.
Lower manufacturing costs
While you can use big data to analyze how a product you sell is doing, you can also use it to monitor the price of materials you regularly need to run your business. For example, if you decorate cotton t-shirts then the price of t-shirts is integral to your production costs. You can use scraping to find the best deals on materials, like fabric or a shirt, and also notice at what times of the year they lower or rise in price. By planning ahead with big data, you can lower your manufacturing costs permanently or when sales occur.
Web Scraping and Managing Large Scale Data
Web scraping is a great collection, analysis, and management tool for big data sets. For large corporations with departments dedicated to data, they must collect enough data to properly analyze the global market. For small businesses, collecting large sets of data gives them the most insight on how to improve gauge customer sentiment. Below read about how web scraping helps with data management.
Custom scraping solution
When companies get tired of using the same old data or the data becomes irrelevant, then it is time to create a custom scraping solution. Custom solutions are built as unique scrapers that can scrape by the millions or billions for less per scrape, making them perfect for large data. For those new to scraping, our Scraping Robot team also helps build the scarper to reflect your data needs. Our team helps you brainstorm and helps you manage proxies and developments. Therefore, the stressful aspects of web scraping are outsourced to us, giving you more time to make smart, informed decisions. If this sounds like the right choice for you, contact us to begin.
While big data is popular and useful, it can still be overwhelming to those new to the data collection world. Large scale data is practically impossible to collect and analyze without web scraping tools. Thankfully, using a web scraper not only helps you manage large data sets, it helps you gather even more data itself. By incorporating web scraping into your routine, your large data sets will feel small enough to comprehend but still large enough to provide quality feedback.
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