Recently, discussions emerged about an alleged leak of Google ranking-related data during the U.S. holidays. Initial posts, particularly by Rand Fishkin, seemed to confirm long-held beliefs about Google’s ranking systems. However, it’s crucial to examine the context and implications of this data more closely.
Context Matters: Document AI Warehouse
The leaked data is related to a public Google Cloud platform called Document AI Warehouse, which is designed for analyzing, organizing, searching, and storing data. This context was highlighted in a Facebook post, suggesting the “leaked” data is an internal version of the publicly available Document AI Warehouse documentation.
DavidGQuaid tweeted:
“I think it’s clear it’s an external-facing API for building a document warehouse as the name suggests.”
This statement challenges the notion that the leaked data represents internal Google Search information. As it stands, the leaked data appears similar to what is publicly available on the Document AI Warehouse page.
Leak of Internal Search Data?
The original post on SparkToro does not explicitly state that the data comes from Google Search. Instead, it mentions that the claim was made by the individual who provided the data to Fishkin. Fishkin, known for his meticulous writing, clearly attributes the claim to his source without affirming it himself.
Fishkin writes:
“I received an email from a person claiming to have access to a massive leak of API documentation from inside
Google’s Search division.”
Fishkin further clarifies that while the email claimed the documents were confirmed as authentic by ex-Google employees, there is no direct evidence to support that they originated from Google Search.
Ex-Googlers’ Take on the Data
Fishkin consulted three ex-Googlers, who indicated that the data resembled internal Google information but did not explicitly confirm it originated from Google Search. Their responses included:
- “I didn’t have access to this code when I worked there. But this certainly looks legit.”
- “It has all the hallmarks of an internal Google API.”
- “It’s a Java-based API. And someone spent a lot of time adhering to Google’s own internal standards for documentation and naming.”
- “I’d need more time to be sure, but this matches internal documentation I’m familiar with.”
- “Nothing I saw in a brief review suggests this is anything but legit.”
Keeping an Open Mind
Given the unconfirmed nature of the data, it’s essential to remain open-minded. The data might not be directly related to Google Search, and using it to validate pre-existing beliefs can lead to confirmation bias. Confirmation bias is the tendency to interpret new evidence as confirmation of one’s existing beliefs or theories.
Brenda Malone, a Freelance Senior SEO Technical Strategist, shared her experience:
“I personally know, from actual experience, that the Sandbox theory is wrong. I just indexed in two days a personal blog with two posts. There is no way a little two-post site should have been indexed according to the Sandbox theory.”
Five Key Considerations About the Leaked Data
- Context: The exact context of the leaked data remains unknown. Is it related to Google Search, or does it serve another purpose?
- Purpose: It’s unclear whether the data is used for actual search results or for internal data management.
- Confirmation: Ex-Googlers did not confirm the data is specific to Google Search, only that it resembles internal Google information.
- Open Mind: Avoid using the data to confirm long-held beliefs, which can lead to confirmation bias.
- External API: Evidence suggests the data may be related to an external-facing API for building a document warehouse.
Expert Opinions on the "Leaked" Documents
Ryan Jones, an experienced SEO professional with a strong understanding of computer science, provided insights into the data leak:
“We don’t know if this is for production or for testing. My guess is it’s mostly for testing potential changes. We don’t know what’s used for web or for other verticals. Some things might only be used for a Google home or news etc. We don’t know what’s an input to an ML algo and what’s used to train against. My guess is clicks aren’t a direct input but used to train a model how to predict clickability (outside of trending boosts). I’m also guessing that some of these fields only apply to training data sets and not all sites.”
DavidGQuaid also tweeted:
“We also don’t know if this is for Google search or Google cloud document retrieval. APIs seem pick & choose – that’s not how I expect the algorithm to be run – what if an engineer wants to skip all those quality checks – this looks like I want to build a content warehouse app for my enterprise knowledge base.”
Is the "Leaked" Data Related to Google Search?
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus neCurrently, there is no definitive evidence that the leaked data is from Google Search. The ambiguity surrounding its purpose suggests it may be linked to an external-facing API for building a document warehouse rather than directly influencing Google Search rankings. Thus, it is prudent to approach the data with caution and avoid drawing premature conclusions.c ullamcorper mattis, pulvinar dapibus leo.
