web scraped data

How To Make The Most Out Of Web Scraped Data

In today’s article we’re gonna discover how you can make the best use of web scraped data. Because it’s one thing to grab data from any website. But it’s a whole another story to get the most out of this kind of data. The data you can scrape from the internet is messy and unusable for other applications. That’s why it’s super important to make sure you know what are the stages of processing scraped data so you’ll always get 100% value out of your data.

Essentially, what I wanna talk about here is three stages: raw data, manipulated data and data intelligence. When you scrape data and you don’t need or don’t want further processing you are leveraging the first stage. On the second stage you realize that modifying the data could be more efficient and helpful for you than raw datasets. Finally on the third stage you create high level reports that ultimately shape the way you make decisions in your business. Now let’s dig deeper into these levels!

Raw data

This is the stage that you’ve already reached if you scraped data from any website. In the web scraping world, raw data means unprocessed data directly from a website. Many times, on this level the data is messy and impossible to work with. Though it’s definitely true that sometimes you ain’t need no more. You don’t need to either clean data or normalize. You might just wanna get the raw data from the web into a spreadsheet or something like that. If this is the goal, staying on the first level and not processing the data further is totally fine.

raw data

An example would be when you don’t really need to do anything with the data after scraping it is when you generate leads through web scraping. If you’re very lucky you can scrape pretty much clean contact information from the web so you don’t have to validate or clean them. Also if you don’t need the data to be read by some software then staying on the raw data level is gonna work out for you. Unprocessed data is unusable for most softwares.

Manipulated data

Data manipulation could involve cleaning, filtering, deduplication and a bunch of other stuff. In this phase, our goal is to make the data usable for other softwares – not just humans. Going back to the lead generation example, many times we do need to clean and validate contact information so we can actually use it. Normalization is also a key here because when we scrape from different sources, the data is – more often than not – in different formats. In order to work with it further we need to use the simplest format for each field so it can be stored properly in the database.

data manipulation

Data manipulation can be done in two ways. First, you can choose to process data right after scraping it – inside your scraper. Using a web scraping framework like Scrapy makes it super convenient. Another way to process data is to store the scraped raw data in a database then use ETL techniques to clean and apply business rules. I prefer the first version because that way we don’t have to store redundant information and get rid of the mess as soon as possible.

Data intelligence

This is my favourite part. This is where magic happens. After we gathered data and properly processed it we have the chance to gain insights. What does that mean? Not just looking at the pure data itself but rather realizing how powerful it is to drive our business. Creating high level reports out of pure data is the way to make data-driven decisions. We can talk about real time or historical reports as well.

data intelligence

Pie charts, bar charts, line charts… you name it. Whatever that makes it easier for us to understand what’s behind the data. This phase is about transforming data into valuable and actionable information. Whether it’s for research purposes or competitor monitoring, data intelligence is the most significant step if you really wanna make use of web data.

Wrap up

Raw data: Zero further processing. Just raw data from the web. Leverage this stage only if a human will read the data and he/she will surely recognize what’s going on.

Manipulated data: This stage involves a mix of data processing techniques like cleaning, normalization, deduplication, matching… Probably because we have an application that needs to read this data correctly and it’s not possible to pass messy, unorganized data into another system. Manipulation also makes it easier for humans to learn from the data.

Intelligence: If you can reach this stage with your scraped data that’s huge! It means you found a way to make the best use of web data. Data intelligence enables you to quickly see through the market, recognize patterns, opportunities and ultimately make smarter, data-driven decisions.