Purna Duggirala is known to Excel users worldwide as Chandoo. His site,Chandoo.org, is my go-to Excel resource. Chandoo has a variety of Excel media from blog posts and videos to full online courses.
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He also has a podcast on how to “Become Awesome in Excel,” the tagline of his website.
An Excel podcast, you ask? How can you talk about something as inherently visual as a software program?
Actually, I have found the Chandoo podcast a perfect platform for honing my analyst skills.
For one thing, it’s versatile — I can enjoy it on my commute or at my desk as I complete daily tasks.
More crucially, thought, the podcast helps you develop what I will call “Excel meta-skills”: that is, skills about Excel skills. How can I use Excel to get a job? How can I improve what I’m doing at work? How can I lever Excel’s strengths in my career?
The audio delivery of the content forces us to step away from the spreadsheet and think more in terms of an “Excel state of mind.”
I started off with Episode 6, “How to be a Better Analyst.” This title appealed as an analyst who reads and writes often on the topic.
This episode was a great launchpad for others, which focus on specific Excel and data analysis problems.
Here are my takeaways.
1. Domain Knowledge comes first.
Yes, his whole site is about Excel. But Chandoo makes it clear that even the best Excel ninja has little to contribute without domain knowledge. The analyst needs to know about industry trends, data modelling techniques, and presentation skills. Learn these skills from following blogs, reading books, and listening to podcasts.
2. Don’t be afraid to collaborate.
Before going full-time with Excel, Chandoo was a business analyst. He was surprised by how many of his problems had been confronted and resolved by other analysts at his office.
So if you’ve got a problem, don’t be afraid to ask around. It’s unlikely that you’re the only person in the office who’s had that problem. Likewise, offer your help freely. Collaboration is the source to success today.
3. Ask “Why do you need that information?”
One of the first things my boss told me was when other departments ask me for data, I need to ask “What do you need it for?” Even then, what they think they need isn’t necessarily what they “really” need. It was my role to figure out what would actually help them.
I thought this was ridiculous. I’m not a mind reader. How do I know what they need and why?
Now I understand why this is important. You need to help people get to what they really need because they do not have your same level of familiarity with the data.
An analogy: If the physician just listened to the patient, he wouldn’t be much of a physician. However, he can’t totally disregard what the patient is saying, either. He needs to gather what the patient tells him and figure out what treatment is actually needed, not what the patient thinks.
4. Be playful.
People like to play and tinker. Add a little “recess time” to your spreadsheet.
Analysts and now even management are in the business of data exploration. It is nearly impossible to capture every relationship in your data through a static report.
That’s why Chandoo suggests adding a level of playfulness to your data. Provide ways to interact through PivotTables, form controls, or dashboards.
5. Be forward-thinking in your model.
While working on your project, think about likely next steps. Is this really going to be a one-off, or will you need to analyze future data? Will you need to drill in on one particular attribute? Build your model with these expectations in mind.
Chandoo mentions how he could anticipate what his boss would be likely to ask next and arrange his model so that he could effortlessly do this next step.
6. Always be learning.
Analysts need to keep polishing their craft. It’s easy to find the best practice for doing your work and stopping to innovate. Always have the mind to improve.
Chandoo suggests to learn one new Excel formula each week (with hundreds, this is a long-giving goal.).
7. It’s the little mistakes that count.
Usually we hear about the spreadsheet error that lost some investment bank millions in revenue. This does happen, and it is catastrophic.
Perhaps more problematic, though, are the tiny, daily mistakes in our work. Hard-coded cells, improperly-referenced cells, etc. The model’s flaw may not be devastating, but it may have real-world ramifactions.
8. Share your techniques.
Chandoo’s site started as a platform to share his Excel and data analysis tips. I have also started sharing my thoughts on similar topics. Analysts: please share your work! You will make your learning active and pick up new things when you share.
Thank you, Chandoo, for a great podcast! I hope this post encourages other data analysts to check it out, “become awesome in Excel,” and write about it.
Photo courtesy Gratisography.