Google Adds New Structured Data Properties to Estimated Salary Dev Page

Google updated its structured data development page to add two new properties to the Occupation structured data and the OccupationAggregationByEmployer structured data. The two properties are “JobBenefits” and “industry.”

According to Google’s developer page:

_Occupation__ structured data allows salary estimate providers to define salary ranges and region-based salary averages for job types, details about the occupation such as typical benefits, qualifications, and educational requirements._

_OccupationAggregationByEmployer__ structured data allows salary estimate provides to aggregate occupations by factors such as experience levels or hiring organization.”_

Estimated salaries can appear in the job experience on Google Search and as a salary estimate rich result for a given occupation.

Google added documentation for the optional jobBenefits and industry properties. While those properties are optional, they will nevertheless generate rich results.

The new structured data properties may also help Google to better understand the web page and rank it appropriately.

The update is documented on Google’s Estimated Salary structured data development support page.

The two properties added to Google’s documentation are optional. That means Google won’t see it as an error if it’s missing.

The new structured data properties are easy to understand the meaning.

The first one, JobBenefits, is for describing any benefits that are given to a person in the job position being described.

Related: Extra Structured Data Could Be Useful for SEO

Google’s developer page describes it like this:

“The description of benefits that are associated with the job.”

The second one, industry, communicates to Google what industry the web page is making reference to.

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Google Adds New Structured Data Properties to Estimated Salary Dev Page

AI & Data Science India Salary Study - 2021

The annual Analytics India Salary report presented by AIM and AnalytixLabs is the only annual study in India that delves into salary trends and provides a comprehensive view of the changing landscape of analytics salaries. The report, now in its seventh year, look at the distribution of average salaries across several categories including years of experience, metropolitan regions, industries, education levels, gender, tools, and skills.

The Data Analytics function is experiencing significant growth and development in terms of skills, capabilities, and funding. Last year, despite the pandemic, the Indian start-up industry witnessed $836.3 million investment, almost a 10% (9.7%) increase than the previous year. Also, more than one in five (21%) analytics teams across firms in India witnessed a growth in the last 12 months and the post-pandemic job market saw an upswing of data science jobs. The development of the data science domain is evidenced by the high salaries drawn by analytics professionals across the organization, with Analytics professionals doing relatively well in spite of the pandemic.

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This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

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Nothing is more powerful than data democracy, where anyone in your organization can regularly make decisions informed with data. As part of enabling this, we need to be able to visualize data in a way that brings it to life and makes it more accessible. I’ve recently been learning how to do this and wanted to share some of the cool ways you can do this in Google Data Studio.

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