Luqman Syauqi Hidayat— RevoU Instructor | Head of Data at Mamikos
Luqman Syauqi Hidayat, or usually goes by Luqman, is the Head of Data at Mamikos - a boarding house finder in Indonesia. Luqman has 8+ years of experience in data analytics and has 5+ years of experience in people management.
Luqman Syauqi Hidayat, or usually goes by Luqman, is the Head of Data at Mamikos - a boarding house finder in Indonesia.
Luqman has 8+ years of experience in data analytics and has 5+ years of experience in people management. He partnered with business and product leaders to solve problems using data and analytics. His years of experience have built him to have strong business acumen and analytical thinking.
Luqman is also experienced in working in a dynamic and fast-growing environment.
Before working with Mamikos, Luqman used to work with Gojek for five years. His achievements and contributions didn’t go unnoticed. Started as a Data Analytics Manager for Go-LIFE; he then got promoted several times and became the Head of Data (Transport Product Group).
As someone who is very experienced, Luqman believes that a good data analyst is not the one who says yes to everything but only picks things that matter.
He also believes that it’s essential to learn the fundamentals of data analytics, such as the technology, terms, and techniques from the right people before jumping into the role.
His experience working with data has given him many valuable insights that he would like to share as Revou’s Data Analytics instructor.
Join the program to learn more from Luqman!
More on Luqman
Questions & Answers
#1 Can you explain to us what your typical day looks like in your current role at Mamikos?
- 30-minutes exercise and have some quick and light breakfast
- Check email and Slack. Usually, answer them right away or put them in backlogs/ to-do lists.
After that, I check my schedule first, list down some of the items or tasks that I would like to accomplish, and book some slots between meetings for deep work.
Regular days (a lot of meetings):
- Weekly alignment with the Management and sharing some interesting insights with them
- Weekly sprint planning with the Data Team and tasks that each of one will take
- 1v1 with some peers (Head of Products) or with my team members to gather some feedback, blockers, or sometimes have a brainstorming session to propose some analytics project to the business or product team
- Progress meetings for some initiatives
- Deep work on some personal OKRs or tasks
- Do interviews for our great data team (usually in the early morning or afternoon). Yes, we’re hiring!
#2 Biggest myths and misconceptions about Data Analytics?
“More advanced analytics techniques will have more impact on the business,” and this is where people get wrong and try to overkill the problem with high-effort solutions.
Most of the time, we need to make it simple as the first step.
We need to always refer to Pareto principles, with 80% of impact coming from 20% of (simple) effort.
While to go from 80% to 100%, we probably need 80% of the high and complex effort. It can be worth it or not, depending on bandwidth, problems, and priority.
A good data analyst is not the one who says yes to everything but the one who only picks things that matter.
#3 Your proudest professional achievement at Mamikos?
- I love when the problems are solved,
- And when I can help other people grow/ achieve their goals.
The good thing is that we can marry both of them by exposing the right problem to the people in my team. And at the same time help them grow and be excited by solving the problem.
#4 Things you wish you could have learned earlier in your career?
Usually, I learn by doing.
My first time learning about Python was when I needed to automate tons of reports in Excel because of no bandwidth on doing it manually every day.
A few years later, when I look back, the code was messy (but worked).
My first time learning clustering was when I needed to do some customer segmentation at work.
And when I encountered specific technical terms, I googled right away and pretended that I already knew it.
I wish I learned the fundamental things first on data analytics, from technology, terms, and techniques and get advice from the right people.
#5 Books / Online resources you follow to remain on top of the most important industry trends and keep improving in your field (blogs, podcasts, newsletters)?
- Eric Weber: From Data to Product (I follow Eric on LinkedIn for his advice that’s relatable to me)
- Lenny's Newsletter (I follow Lenny on Twitter and yes I know he tweets mostly about Product Management. As a data person who mostly interact with Product Managers, I think we need to also learn a bit about Product Management)
- Twitter @shreyas (startup advisor for some general advice in startup world)
- Techinasia/ Daily Social for startup news in SEA.
- Towards Data Science (A Medium publication sharing concepts, ideas and codes related with data analytics and data science)
- Cassie Kozyrkov (Personal blog from Head of Decision Intelligence, Google)
#6 Your tips for someone who is interested in starting his career in Data Analytics (aside from applying to RevoU :) )?
You need to get your hands dirty.
If possible, ask your manager (or someone with authority in your current company) to change your role into data analytics.
Or, you can request to do a matrix role by helping the data analytics department in your current company while doing your business as usual.
You will need extra effort, but it will be worth it after all.
Other than that, you can also start building your portfolio by doing some side projects in data analytics.
#7 The fundamental skills a Data Analyst is expected to have?
Problem-solving skills by understanding the business, justifying the problems, and making recommendations based on data.
And, of course, some technical skills to do all of them (SQL and Python/R and some other data analytics tools).
#8 What distinguishes a good Data Analyst from a great one?
In my opinion, it’s “speed”!
The best analysts are lightning-fast coders who can surf vast datasets quickly. Their code might not be as good as software engineers, but they can do it faster with their semy-sloppy code.
Speed is their highest virtue, closely followed by the ability to identify potentially useful gems.
Learn from Luqman and other great instructors by applying to RevoU Data Analytics program
Looking to kickstart your career in Data Analytics but don’t know where to start? Apply to RevoU 13-weeks Data Analytics Program
How RevoU works:
✓ Live daily interactive online classes for 13 weeks (7–9pm WIB)
✓ Learn from the best instructors in the industry (such as Luqman)
✓ Personalised career coaching with 1:1 mentorship sessions
✓ If you are looking for a job and don’t get one at the end of the Program, the entire course is FREE
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