Category: Digital Analytics

Tennis score tracking and exported data analysis with Apple Watch using Swing App

Tennis score tracking and exported data analysis with Apple Watch using Swing App

During the winter of 2018-2019, I was able to take my tennis tracking journey into a new level.  By now most of my tennis hitting partners are calling me a “data nerd”, clicking my watch like crazy during the game. But when I show them the stats after the game, they all (seem to be) impressed.

I did the following two new things in particular:

  1. Used the “Point by Point + ” score tracking in the Swing App to track all the points I have played. In total, I tracked 18 matches over the last 4 month, all of them were single matches and played in 1 hour.
  2. Exported the captured data into spreadsheets. By analyzing the data set, I was able to identify some of the limitations, as well as some opportunities to further enhance the analytics experience.

Before we dive in, if you are interested in knowing the tennis tracking tools and methodology, or a high-level overview, you can check my 1st blog post of this series: Tennis tracking after 18 month of usage. Or if you prefer to track drills instead of match, you can check out my last post on advanced tennis shots tracking.

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Tracking tennis swing with Apple Watch (Series 4) and the updated Swing App

Tracking tennis swing with Apple Watch (Series 4) and the updated Swing App

It has been 9 months since I first shared experience to track tennis performance with Apple Watch.   Backing up by popular demand(Surprised so many visitors found this blog from search engine all over the world), I’d like to take it further with a more in-depth review, of my own experience tracking and analyzing my tennis workout with the Swing app.  

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Advanced Analytics with Swimming data from Apple Watch

Advanced Analytics with Swimming data from Apple Watch

This blog post is aiming to provide a step-by-step guide to perform advanced analytics on swimming data, captured by Apple watch.  Microsoft PowerBI and Python on Jupyter Notebook are the primary tools to prepare, analyze and visualize the data.

You will learn how to export the workout data efficiently to your PC, make necessary data transformation, and understand what metrics and dimensions are available.  Then I will walk you thru how to analyze the data to answer typical questions related to why certain behaviors happened.   You will then see my preliminary attempt to use advanced analytics tools to predict future swimming performance.

Most importantly, you will find quite a few reference articles related to this topic, hopefully fulfilling your intellectual curiosity.

It is also the #3 articles of a series, the previous articles can be found here:

#1: How to use Apple Watch to monitor and improve swim performance

#2: Improving swimming performance with Apple Watch(WatchOS 4)

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7 steps to be a life-long learner – Exam isn’t the destination

7 steps to be a life-long learner – Exam isn’t the destination

The “life-long learner” is a pretty sexy title.

Over the past few years, I have received feedbacks, from both trusted and the anonymous sources, that self-improving seems to be one of my characters.

As a normal human being, I was flatted;  As an analyst, I can’t control the skepticism: Is this a filtered bubble?

What does it really take, to become “life-long” learner? – Let me tell you my version:

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Why you should use Apple Watch to track and analyze sleep

Why you should use Apple Watch to track and analyze sleep

Sleep tracking isn’t new. But what’s unique about using Apple Watch?

General Introduction

Sleep is the single most important activity for a normal human being, measured by time spent. Having a good night of sleep usually means a jump start of the day. On the flip side, bad sleep (or no sleep at all) will lead to serious implication – both physically and mentally.

In this blog post, I am happy to share my story of using the Apple Watch + 3rd Party App to better measure the sleep.  Hopefully, it will inspire you to pick up a few things here and there and take action to make your own sleep better.

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Three lessons learned from 5 years analytics experience in a Fortune 100 company

Three lessons learned from 5 years analytics experience in a Fortune 100 company

 

I have recently wrapped up 5 years (4 years + 9 months to be exact) of analytics career in a Fortune 100 company. In this precious in-between moments, I’d like to take the time to reflect on 3 lessons learned as an analytics professional in the digital marketing industry.

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PowerQuery and PowerPivot, the two new powerful features for the latest Excel

PowerQuery and PowerPivot, the two new powerful features for the latest Excel

You are a proficient Microsoft Excel user – vlookup is an appetizer, pivot-table is the main course, and VBA/Macro is your dessert.   And your company just gave you an upgraded Microsoft 365 subscription, and a brand new version of Excel is just being served.  You are wondering – “What’s new?”

As an analyst living and breathing with Excel, PowerPivot and PowerQuery are the two killer features, period.  I’d like to share my story on how you can save time and make your spreadsheet work more efficient.

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Year-end reflections from Toronto local chapter events, Digital Analytics Association

Year-end reflections from Toronto local chapter events, Digital Analytics Association

2017, I have been benefited greatly from the digital analytics association(DAA), including the eMetrics and certified web analyst destination, and five local chapter events in Toronto. This post breaks down these events I went to, what are they, how do they help me, and why they matter to me during the career development for a digital analyst.

Being a part of a bigger community

 

Earlier in my career, maybe 10 years ago, I had a similar feeling surrounded by a group of peers, sharing similar interests – tennis. We achieved great things together – workshops, tournaments, etc.  That experience not only shaped my life-long hobby,  but also gave me an opportunity to meet, work and have fun with a few friends that I am still contacting with now.

Back in 2017, I have a similar feeling – “being a part of something big”, after attending 5 local Toronto chapter events from DAA. 

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Improving swimming performance with Apple Watch (Watch OS 4)

Improving swimming performance with Apple Watch (Watch OS 4)

Back in February in my first post of using Apple Watch to track swim, I wrote about the metrics available and usage in the Apple Watch, a handful of data quality challenges, and my plan of using data captured to improve performance.  After logging another 22 workouts since Mar 2017, I would like to give an update, and also share a few more new interesting lessons learned.

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Building a “digital dashboard” – Part 2 Technical side using Microsoft PowerBI

Building a “digital dashboard” – Part 2 Technical side using Microsoft PowerBI

Introduction

I have been using Microsoft product for over 20 years, starting with MS-DOS, and Windows 3.1. Microsoft PowerBI is my favorite software so far: It is simple, updated frequently, and has the right amount of configuration to “get things done”. The user community used to be small back in 2015, but it is catching up quickly with the forum, free resource (YouTube search “PowerBI”) and paid resource (high-quality material like SQLBI and PowerPivotPro) .

At the same time, as an analytics practitioner, I also understand it is vitally important to keep a mindset of “software independent”. What matters the most is the ability to deliver high-quality deliverable in the most efficient way. A technology tool like PowerBI can help to achieve that, however, we need to be cautious of falling in love with the software, not your own craft and the value delivered.

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