… and to those who want to become one!

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During my first years of working in the area of Data Analytics, I read many books that I found very helpful in making me a better Data Analyst. Among them, 4 books stand out, which I would recommend to anyone who wants to enter this area or continue to develop.

All the books that are named here are non-tech. None of them talk about programming skills (SQL, R, Python, etc) or statistics — there are already many reading lists that I would highly recommend as this one! In my post, I would like to focus on the books that helped…

Notes from Industry

By setting up a lightweight ELT project using Google stacks

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Aside from my work, one interesting side project I’ve worked on is to help one investor of my current employer automate the performance monitoring of its portfolio companies.

Data, automation, performance monitoring —these should sound like an easy job in a world where “data is the new oil” is the new mantra and we have vast choices of data integration platform vendors on the market. However, these solutions may be too much for such a special use case. We don’t really have big data here, and data latency is not on top of our heads.

The real challenge we were…

A picture with the text “THE JOURNEY IS ON”
A picture with the text “THE JOURNEY IS ON”
Photo by Clemens van Lay on Unsplash

As a documentation lover, one of the most interesting pieces of documentation I have created at work is an instrumentation guideline on how to define and implement events to track user behaviors and use the data for better decisions.

I really enjoyed this project. On one hand, this project was a great collaboration between data, engineering, and product management. While working on it, I learned a lot from my colleagues about tracking and product analytics. …

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One of the most interesting projects that I have worked on during my time with my current employer, a German fintech Startup, is to implement a company-wide OKR (Objectives & Key Results) monitoring system in the year 2019.

The main challenges we were faced with are:

  • How should we break down the Objectives into meaningful Key Results and Health Metrics, to ensure that when we look at them every month we know very well if we are on the right track to our Objectives?
  • How should we make sure everyone in the team truly understands and owns his/her goals, so…

And how to quickly unlock insights and business value from it

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It’s time to brush up on my Python skills! 👩🏻‍💻

This week I want to go techie and share a recent Python exercise using the RFM framework. It is a method used to determine customer value by looking at three dimensions:

  • Recency: when is the last time the user takes an action (e.g., login, place an order)?
  • Frequency: how many times does the user take this action?
  • Monetary value: what is the sum of monetary value from this user throughout his/her lifetime?

My work was heavily inspired by many helpful posts on the same dataset like this one. With this…

Office Hours

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My blog journey continues!

Since I will start my MBA journey this August, I will be away from the workplace for 10 months. I definitely want to continue to work in a data-related role afterward, so I’d like to write a summary of what I found really helpful during my first years as a Data Analyst— also for my own record. There are a lot of useful resources on the Internet from which I have learned a lot. Hence, I try my best to keep this post as unique and personal as possible to reduce overlaps.

Before I dive into…

How we developed a payback calculator that won us a €69m Series C

Photo by Yifei Chen on Unsplash

During my time with my current employer, a German Insurtech startup, one of the most interesting projects is to develop a payback calculator which served as the backbone figure that helped us to close a recent €69m Series C funding round. 🥳

The payback period, the output from this payback calculator, answers the question, “If I now invest one euro into your business, how long does it take for me to earn that one euro back?”. Needless to say, it is one of the most important metrics…

Office Hours

For an effective data story presentation

In my first blog post How I do Data Storytelling, I have mentioned that one key part of a good story telling is to create a visually affordable presentation, which should be be a great complement to your verbal communication rather than distracting your audiences from it.

With this post I would like to expand on the tips that I mentioned in the previous post, and share some good practices and examples that I find really helpful in the real life of a data analyst.

Source: https://unsplash.com/photos/Ar-iTL4QKl4

This post will cover analysis reports which are usually produced in the form of essays…

During my last 5 years of working as a Business Intelligence Analyst, I have received many positive feedbacks on my data storytelling skills from both internal and external audiences.

Therefore, with this very first blog post, I would like to share four tips that I found really helpful in conducting a good data storytelling. They are:

  • Know your audiences.
  • Develop your story together with your audiences.
  • Know your data through and through.
  • Create a visually affordable presentation.

Any feedback will be appreciated!

Happy reading.

Know your audiences.

The first and the foremost principle is to have a good profiling of your audiences. Ask…

Wenling Yao

INSEAD MBA 22J | Business Intelligence | Fintech | Realist | Explorer | Make well-informed decisions every day.

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