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.
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.
Tennis is a big part of my personal life. Playing competitive level matches since 2006, I have won a few tournaments in the “club” level. Ironically, I have never played in a doubles tournament ( never a fan of doubles game, and often complain about not even getting sweaty), nor have I played in a game organized by the companies I worked for (tennis might be such a “minority” sport that didn’t get much attention).
I broke both rules last week.
It was the 1st “3M Open” tennis tournament – featured only doubles matches. One of my colleagues in the lab signed me up for it. We have played together a few times in the past but never played doubles as partners. For both of us, the original goal was very clear –
“Enjoy the sunshine and have some fun. “
In the end, we brought the “3M cup” back home by winning three straight matches in a row. When I look back today, the experience was 100% memorable. But “fun” is not the appropriate word. Instead, it is more of the mix of drama, pressure, heartbreak, teamwork, and a sense of relief.
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.
I have finally earned my certification practicing digital analytics from digital analytics association this week. I was so pumped and barely had any sleep the night after I got it.
In this post, I will share what is this certification and different options, why getting certified in digital analytics is important to me, and how I pass the exam test (without violating the confidentiality agreement.)
I am very happy to come back to this topic, after started this blog by writing about Facebook metrics 6 months ago.
Just a little side note – I used to code a lot at 16 years old – never found much fun and gave up once I made it to college. Ironically, this time I had a lot of joy learning Python to connect to Facebook API for “insights” in the past few months.
The business case here is straightforward: We need to understand how we are doing in social media channel from the metrics perspective. As I addressed in my previous post, the data exporting feature of Facebook business manager is simply not good enough.
Using Python, I was able to directly call Facebook’s Graphic API, and retrieve the metrics – impressions, likes, shares, comments, link clicks etc – of each individual posts as far as 2 years ago, to a CSV file. Then I can port it with Microsoft PowerBI and do all kinds of analysis and visualization.
What I like this the most, is by having this Python code in place, I can bypass the traditional “Extract, Transform and Load” process of using the data warehouse. As a proud “full stack” analyst, I want my “data to insights” journey as simple as possible. Also, I can’t afford the typical 1 day of delay (of data warehousing), as a social media post can go viral and suddenly receive 100 “likes” in 4 hours.
Now let me explain how it works in a bit more geeky way…
As a self-claimed NTRP 4.0 tennis player, I am really proud of my passion for tennis. But I am writing this post not for sharing my passion and achievement of winning a tournament, but three pieces of learning I took away from it. Hopefully, they are helpful to my audience, no matter as a tennis fan or not.
In the last couple of years, I have been asked numerous times for a “dashboard”. In reality I was asked a chart showing “what is my project (‘s KPI) doing”. I usually performed a few data pukes and provided one PowerPoint slide, once the KPI is clearly defined, and the source data is in a “reasonable-messy” format. I was not impressed by the business reality of over-used term “dashboard”.
“What is a dashboard”
In my opinion, a true “dashboard” should serve beyond “what”, but also “why”.
I love new technology stuff. That is why I bought the Apple Watch 2 series 2 the day when it was launched. Mostly attracted by its waterproof feature for swim tracking, I was so pumped and even lined up in the retail store to get it on the first day.
Now I have been using it for almost 5 months and recorded 29 swimming workout. I’d conclude that it is a worthwhile purchase, as it helped me monitor and improve swim performance. Although the journey is not a smooth as I expected, let me share my experience.