In today‘s data-driven business landscape, organizations are increasingly turning to web scraping and external data to fuel their Business Intelligence (BI) and analytics initiatives. By leveraging web scraped data on everything from market trends and customer sentiment to competitor pricing and product details, enterprises can gain a more comprehensive and real-time view of their business environment.
However, integrating web scraped data into BI platforms is not always straightforward. Scraped data is often unstructured and can be difficult to blend with internal data sources. Additionally, web scraping at scale requires the use of IP proxies to avoid blocking by target sites and to access geographically dispersed data points.
In this article, we‘ll explore how the 20 most popular BI tools of 2021 stack up when it comes to web scraping and IP proxy capabilities. We‘ll dive deep into the features and architectures of these platforms to understand how they can ingest and make use of web scraped data to enhance enterprise analytics.
The Growing Importance of Web Scraping for BI
Before diving into the specific BI platforms, it‘s worth stepping back to consider just how critical web scraping has become for enterprise analytics. According to a recent survey by Parsehub, 67% of companies are now using web scraping to gather data for business purposes, with use cases ranging from competitor monitoring to lead generation.
Web scraping provides a treasure trove of external data that can enrich and contextualize internally-generated data. For example, by scraping social media and review sites, businesses can better understand customer sentiment about their products and services. By scraping competitor websites, they can track pricing changes, product updates, and marketing tactics.
All of this external data provides valuable fodder for BI and analytics tools, allowing organizations to make more informed and timely decisions. As Sandeep Raut, Director of Digital and Analytics at Syntel, puts it: "Enterprises are realizing that their internal data, although vast, is not enough to give a 360-degree view of their customers, competitors and the overall business environment. Web data is becoming an essential piece of the puzzle."
The Role of IP Proxies in Web Scraping for BI
Of course, web scraping at scale is not without its challenges. Websites are increasingly savvy about detecting and blocking scraper bots, particularly those that are hitting their servers with a high volume of requests.
This is where IP proxies come into play. By routing web scraping traffic through a pool of rotating IP addresses, organizations can avoid triggering anti-bot measures and ensure continuous access to target sites. IP proxies also allow companies to access geo-targeted data by leveraging IP addresses from specific countries or regions.
According to a study by Zyte (formerly Scrapinghub), 72% of web scraping professionals use IP proxies to gather data, with 46% saying they are "essential" for their scraping projects. The use of proxies is especially critical in competitive industries like e-commerce and travel, where data is time-sensitive and businesses are aggressively monitoring their rivals‘ online presence.
Now that we‘ve established the importance of web scraping and IP proxies for BI, let‘s turn our attention to the top 20 BI platforms and assess how well they support these capabilities. We‘ll use a five-point scale to rate each platform on its web scraping and IP proxy functionality, with five being the highest score.
1. Microsoft Power BI
Microsoft Power BI is a widely used business intelligence tool that allows organizations to visualize and analyze data from various sources. From a web scraping perspective, Power BI offers a built-in web connector that enables users to import data directly from web pages.
However, Power BI‘s web connector has some limitations. It struggles with complex, JavaScript-heavy websites and does not have built-in support for IP proxies. More advanced web scraping typically requires using a third-party tool or custom code in conjunction with Power BI.
- Web Scraping Rating: 3/5
- IP Proxy Rating: 2/5
2. Tableau
Tableau is another leading BI and data visualization platform known for its ease of use and vibrant community. Like Power BI, Tableau offers a native web data connector for scraping data from web pages.
Tableau‘s web connector is fairly robust, supporting both static and dynamic websites. However, it also lacks built-in IP proxy support, meaning users have to set up proxy routing externally for larger scraping jobs.
- Web Scraping Rating: 4/5
- IP Proxy Rating: 2/5
3. Qlik Sense
Qlik Sense is a powerful BI tool that leverages an associative data engine to uncover hidden insights. Qlik offers a web scraping tool called Qlik Web Connectors that can extract data from websites and feed it into the Qlik Sense platform.
Qlik Web Connectors support both static and dynamic websites and can handle authentication and pagination. However, proxy configuration is not built-in and must be set up separately.
- Web Scraping Rating: 4/5
- IP Proxy Rating: 2/5
4. SAS Visual Analytics
SAS Visual Analytics is a robust BI solution with advanced data analysis and visualization capabilities. SAS offers a tool called SAS Data Crawler for web scraping and incorporates machine learning to help structure scraped data.
SAS Data Crawler has good proxy support, allowing users to input their proxy settings directly in the tool. It can handle both static and dynamic websites but may struggle with highly complex JavaScript sites.
- Web Scraping Rating: 4/5
- IP Proxy Rating: 4/5
5. IBM Cognos Analytics
IBM Cognos Analytics is a comprehensive BI suite that supports the full spectrum of analytics, from simple reporting to advanced data science. Cognos offers a few different options for incorporating web scraped data.
First, Cognos Analytics integrates with IBM Watson Discovery, a powerful AI tool that can scrape both internal and external data sources. Watson Discovery handles document ingestion, natural language processing, and knowledge graph creation, making it a good fit for unstructured web data.
For more traditional web scraping, Cognos also offers a REST API that can be used to pull in data from web pages. However, this requires custom development and does not have built-in proxy support.
- Web Scraping Rating: 3/5
- IP Proxy Rating: 2/5
6. Information Builders WebFOCUS
Information Builders WebFOCUS is a BI and data analytics platform known for its scalability and performance. Like Cognos, WebFOCUS offers a few different ways to integrate web scraped data.
WebFOCUS can ingest data from RSS and Atom feeds natively, which provides an easy way to incorporate data from news sites and blogs. For more custom web scraping jobs, WebFOCUS offers an Adapter for Web Services that can make HTTP requests to web pages and APIs.
The Adapter for Web Services supports proxy configuration, allowing WebFOCUS to run larger scraping jobs without hitting IP-based rate limits. However, it may require some technical expertise to set up and configure.
- Web Scraping Rating: 4/5
- IP Proxy Rating: 4/5
Web Scraping and IP Proxy Ratings for Additional Top BI Tools
- MicroStrategy: Web Scraping (4/5), IP Proxy (3/5)
- Domo: Web Scraping (3/5), IP Proxy (2/5)
- Looker: Web Scraping (4/5), IP Proxy (3/5)
- Sisense: Web Scraping (4/5), IP Proxy (2/5)
- Yellowfin: Web Scraping (3/5), IP Proxy (2/5)
- TIBCO Spotfire: Web Scraping (4/5), IP Proxy (2/5)
- Oracle Analytics Cloud: Web Scraping (3/5), IP Proxy (3/5)
- SAP BusinessObjects: Web Scraping (3/5), IP Proxy (2/5)
- Alteryx: Web Scraping (3/5), IP Proxy (2/5)
- Zoho Analytics: Web Scraping (3/5), IP Proxy (1/5)
- Logi Analytics: Web Scraping (3/5), IP Proxy (2/5)
- BOARD: Web Scraping (2/5), IP Proxy (1/5)
- Pyramid Analytics: Web Scraping (3/5), IP Proxy (2/5)
- Dundas BI: Web Scraping (3/5), IP Proxy (2/5)
Conclusion
As the volume and variety of data continues to explode, organizations are increasingly looking beyond their own four walls to external data sources to fuel BI and analytics. Web scraping has emerged as a powerful technique for gathering this external data at scale.
However, integrating web scraped data into BI platforms is not always a straightforward process. As we‘ve seen, the level of web scraping and IP proxy support varies widely across the leading BI tools. Some, like SAS Visual Analytics and Information Builders WebFOCUS, offer fairly robust web scraping capabilities with good proxy support. Others, like Microsoft Power BI and Tableau, have more limited web scraping functionality and lack built-in proxy configuration.
Ultimately, organizations looking to leverage web scraping for BI need to carefully evaluate their platform options to ensure they can support their data collection and integration needs. In many cases, it may be necessary to use third-party web scraping tools or develop custom connectors to fully harness the power of web data for analytics.
Regardless of the specific technical approach, one thing is clear: external data from the web will play an increasingly pivotal role in the future of business intelligence. As organizations seek to gain an edge in an ever-more competitive landscape, those that can effectively collect, integrate, and analyze web data will be well-positioned for success.