The Google Scraper API is an application programming interface (API). It enables users who want to collect data from Google’s search engine results pages (SERPs) to programmatically communicate with a service provider’s Google scraping tools. First, the user creates and sends a query that contains information on the URLs from which the scraping tools should extract data. Then, the provider’s scraping infrastructure collects this data and sends it to the user via the API. Businesses can use this data for big data analytics and business intelligence.
Features of a Google Scraper API
A Google Scraper API has the following distinctive value-generating features:
- It is primarily designed to extract data from the Google SERPs
- The solution integrates proxies and proxy management tools, enabling it to retrieve accurate city-level data; in fact, a reputable provider should have proxies from tens of countries, enabling you to gather localized search results from these jurisdictions
- It can collect both paid and organic search results
- The Google Scraper API can collect data from SERP features such as the local pack, which contains listings of local businesses and hotels
- A quality Google Scraper API is equipped with an auto-retry function that resends the search query and reattempts the data extraction if the first attempt fails
- This solution can scrape data from multiple SERPs at a time without getting blocked
- The Google Scraper API has data parsing capabilities, enabling it to convert unstructured data to a structured format
- It can deliver the data via different avenues, e.g., through an API or by sending it to cloud storage
These features make the Google Scraper API a useful data collection tool for big data analytics and business intelligence.
Google Scraper API in Big Data Analytics
Big data analytics is a process that involves the collection, examination, and analysis of massive volumes of data. It is often carried out to identify underlying trends and patterns within the data and unearth valuable insights that can enable companies to make better decisions. From this description, the initial step is data collection, which leads us to the sources of big data.
Sources of Big Data
There are three main sources of big data, namely:
- Social (human) – data generated directly by users through content posted online, such as social media posts, blog posts, reviews, and videos
- Machine (sensors) – data that is collected by sensors found in Internet of Things (IoT) devices, mobile phones, medical equipment, cameras, etc.
- Transactional data – this relates to data that results from the purchase of products and services. For example, it is gathered from invoices, payment orders, e-receipts, or historical records.
Search data is also emerging as a key source of big data. But of these three main sources above, social data stands out because it does not require a lot of capital expenditure. Additionally, it can be utilized by businesses during the formative stages, even before they can acquire customers. The accessibility of social and search data stems from the fact that it can be collected from search engines using SERP scraper APIs like the Google Scraper API.
Role of Google Scraper API in Big Data Analytics
The Google Scraper API is designed to extract real-time localized search results data. It utilizes an extensive pool of proxy servers that prevent IP blocks and relies on advanced web scraping technology developed by the service provider. As a result, it can seamlessly collect large volumes of data for keywords that pertain to a business’s operations.
What’s more, the Google Scraper API converts the unstructured HTML data on the SERP to a structured format that can be easily examined and analyzed. In fact, it can send this data directly to analysis software via an API or a cloud storage bucket. This way, it further boosts big data analytics.
Google Scraper API in Providing Business Intelligence
Just as big data analytics is integral to helping companies make better decisions, so too is business intelligence (BI). BI refers to the process of collecting and analyzing data and subsequently presenting it in easy to understand format and disseminating the insights from this analyzed data to employees of an organization. In this regard, BI combines data mining, data collection, analytics, and presentation. And much like big data analytics, the foundational step is data collection, which is where the Google Scraper API comes in.
You can use this important solution to collect vast amounts of search results data from thousands of SERPs. In addition, you can also retrieve data from the various SERP features such as rich snippets, video carousels, dedicated ad spaces, featured snippets, local packs, and more. In fact, thanks to the Google Scraper API’s use of proxies, it can collect real-time localized search results data.
Conclusion
Business owners can use the Google Scraper API to collect data that they can analyze and use the insights generated to make informed business decisions. Simply put, this tool can be deployed in big data analytics and business intelligence. Click this link now for further reading on Google Scraper API.
