We appreciate each and every one of the many talented people who have contributed to Great Expectations’ open source project and participated in our community—10,500 members and growing!
Today, we’re profiling Abhinav Anand.
Intro & icebreakers
❓What’s your current role and organization?
Senior Software Engineer at Tiger Analytics. I am currently working on implementing data quality checks for various use cases.
🍦What’s your favorite ice cream flavor?
My favorite ice cream flavor is chocolate.
🎞️ What’s a movie you love?
It’s a Hindi movie: “Uri: The Surgical Strike.”
📚What’s an author everyone should read at least once?
“The 7 Habits of Highly Effective People” by Stephen R. Covey.
⚫⚪ Light mode or dark mode?
Dark mode
Interview
🔎 How did you discover Great Expectations? What did you do with it first?
It was actually recommended to me by one of my colleagues when we were also evaluating other data quality tools. After comparing it with the other tools, I finally ran some ad hoc checks to see how it works, and GX turned out to be exactly what I was looking for.
🌱 What are some things you find rewarding about contributing to an open source project?
Contributing to an open source project offers a unique opportunity to collaborate, learn, make an impact, and grow both personally and professionally. Open source projects often have a wide user base, and your contributions can have a tangible impact on users worldwide. It can be a rewarding experience that extends beyond the immediate contributions you make.
🧡 Is there anything about contributing to GX specifically that you enjoy?
I really enjoy answering other people's questions on Slack because it provides me with insights into how others utilize GX and the challenges they face.
🛠️ If you’ve contributed Expectations: what do your Expectations do, and what are some reasons someone would want to use them? Or what are some Expectations you’d like to contribute one day?
I haven't contributed an Expectation yet, but I would like to contribute to the profiling capabilities of GX. Specifically, I am interested in exploring the possibility of using ML to recommend a set of Expectations to users.
🏆 What contribution to GX are you most proud of and why?
Helping community members with their questions and knowing that my assistance has made a positive impact on someone is truly what makes me feel proud.
✅ What does data quality mean to you?
Data quality refers to the overall accuracy, completeness, consistency, and reliability of data. It is a measure of how well data meets the requirements and expectations for its intended purpose. Data quality is crucial because it directly impacts the effectiveness and reliability of any analysis, decision-making, and business processes that rely on that data.
Thank you Abhinav for taking the time to speak with us!
If you’re thinking about joining the GX community, there’s no time like the present. Ease in with lurking in Slack or go straight to sharing your Custom Expectations: we’re happy to have you no matter how you want to engage.
Get involved:
You can join the GX Slack here, or ask a question in Discourse.
Check out our guide for getting started with contributing.
It’s easy to share a Custom Expectation if you follow our step-by-step process.
To contribute a package, start with this how-to, so everything is as easy as possible.
