Mustika Aprilianti, or usually goes by Mustika, is currently the Senior Business Intelligence at Mekari- Indonesia's Software-as-a-Service (SaaS) company. She has been with Mekari since November 2019 and started as a Business Intelligence, then Data Scientist, and now Senior Business Intelligence.
As the Senior Business Intelligence, her responsibilities include but are not limited to building data products, such as reports, dashboards, or data automation. She also thinks those data products are not the medium to show her competencies but her good intentions toward her users to meet their data needs.
As a person who is an expert in Data Analytics, Mustika believes that it's essential to have both understandings of data and business as a data analyst. Without understanding the business, it will just hinder our development phase. If we understand both aspects, solving data problems in the company will be so much easier.
Questions & Answers
#1 Can you explain to us what your typical day looks like in your current role at Mekari?
I would like to divided my typical day into 3 parts:
- Meeting with the data team and do the alignment, we usually share the progress of our work and also its drawbacks or bottlenecks if there is any
- Maintaining and improving the data warehouse
- Check the data bug and align the metrics definition along with the business users
- Put the task on to do list
After Lunch Break
- Focus on the task related with the OKR (initiatives project, data automation, etc)
- Meeting with the business stakeholders regarding their data needs (BAU request)
- Tableau sharing session
- Response the data questions in the personal chat or group chat
- Response the email
- Review the progress of the task
#2 Biggest myths and misconceptions about Data Analytics?
I think the biggests myth I would like to convey is:
“To solve the data problems you must use the fancy tools or methods”
Based on my experience, not all data problems must be solved with the advanced tools or the newest techniques. We might solve the issue with a simple solution, such as excel formulas or a few rows of query.
Rather than focus too much on the tools or the methods, as a data specialist we have to fully understand the problem first before coming up with the solution.
If we waste our time comparing the best tools or the best methods, we may not solve the correct problems and also we might lose our context about the business problem itself, because we just see the problem only from our perspectives, not from the whole perspective.
At the end of the day, the business users won’t care about the tool/the methodology, but they care whether their problems can be solved or not.
Tools and ideas are great but understanding the context is the most important :)
#3 Your proudest professional achievement at Mekari?
I would say my proudest achievement is when I can solve many issues and help many users solve their data problems.
I believe the data products which we delivered to the users, such as reports, dashboards, or data automation are not the medium to show our competences but to show our good intentions toward them to meet their data needs.
#4 Things you wish you could have learned earlier in your career?
Early in my career, I used to ignore the basic of data analysis, which is the business understanding. I thought that the basic was not needed and it just delayed our development phase because we focused too much on it.
But otherwise, when we don’t fully understand yet about the business context, we will trap in the cyclic zone until the business requirement has met.
After that, I learned that knowing the basics is the best way to start our analysis.
#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)?
For Data :
For Others :
- Abby Covert (I really love her writing about information architecture)
- The Little Book of Ikigai - Ken Mogi
- Practical Empathy - Indi Young
#6 Your tips for someone who is interested in starting his career in Data Analytics (aside from applying to RevoU :)?
Learning and understanding the basic first before jump into the advanced/ fancy techniques, which are:
- Data Understanding - How much do we know about our data?
- Business Understanding - How is the business model?
If we could strengthen these two skills, I think we can solve most of the data problems in the company
#7 The fundamental skills a Data Analyst is expected to have?
- Listening to others
To give the data solution, the first thing we must understand is the problem. To understand the problem, we need to know the users' perspective. Knowing the users’ perspective involves empathy and empathy requires listening.
- Problem Solving
Giving the mere solution is not the final result of the data analysis, but how we can give the right solution for the correct problems to our users. It requires problem solving skills.
#8 What distinguishes a good Data Analyst from a great one?
A great data analyst is someone who can inspire and influence others to become an analyst. This is the easiest way to know that the others have recognized your work and contribution.
Learn from Mustika 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 Mustika)
✓ 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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