A very common scenario one comes across while performing data analysis is wanting to compute a basic count of some event—such as visits, searches, or purchases—split by a single dimension—such as country, device, or marketing channel. Amazon Redshift provides an off-the-shelf window function called ratio_to_report which basically solves what we are trying to accomplish. Running this function gives us the exact same output as the previous query, but with half the lines of code, and a more readable result.
The phrase “data quality” is frequently—and often ambiguously—thrown around many data analytics organizations. It can be used as an object of concern, an excuse for a failure, or a goal for future improvement.
We’d all love 100% accuracy, but in the era of moving fast and breaking things, don’t we want to sacrifice a little accuracy in the name of speed? After all, isn’t it often better to make fast decisions with imperfect information and adjust course if necessary at a later point?
Once a year I try to reevaluate my “personal tech stack” to see if I am using fundamental tools as effectively as possible. Not just bigger tools such as todo lists, calendars, and note-taking, but also the smaller utility apps that get used so frequently they blend into our daily work routine. Our fluency with the tools we use every day is the foundation of personal productivity, so it makes sense to optimize even small interactions such as switching between windows. With that in mind, here are three key Mac apps that make me a tiny bit more efficient but do so very frequently.
I’m always hesitant to tell people that I work as a data scientist. Partially because it’s too vague of a job description to mean much, but also partially because it feels hubristic to use the job title “scientist” to describe work which does not necessarily involve the scientific method.
Data is a collection of facts. Data, in general, is not the subject of study. Data about something in particular, such as physical phenomena or the human mind, provide the content of study.
Anki 2.1+ now has built-in support for MathJax. This is now the best approach to math typesetting, since it removes the dependency on LaTeX being installed on your computer. Besides being a pain in the ass to configure, this also required a bunch of configurations that you had to keep track of if you regularly use multiple computers with Anki. As a bonus, the MathJax syntax is cleaner, and you can now edit expressions on AnkiDroid and they will render immediately.
A good chunk of the job of being a PM or analyst involves spending time analyzing patterns of user behaviour, often to answer specific questions. Over time though, we build up mental models and heuristics which allow us to use our prior knowledge to answer questions more quickly.
More knowledge is good, right? On one hand, past experience calibrates our sense of prior probability, which allows us to make better decisions in noisy contexts.
Remote Research lays out a comprehensive framework for starting to conduct research studies at your company, and is useful for beginners or for filling in the gaps in your mental model. However it seems more targeted towards large companies with established UX practices than towards startups. If you are executing alone—perhaps as a one-man UX team—you may still feel a gap between theory and execution.
I finished reading Web Form Design recently on the recommendation of a mentor. The author makes a good case about web forms being a high leverage area to invest design efforts. The combination of forms being mandatory, complex, and not particularly sexy, results in an experience that is often the worst part of a user’s interaction with your product. He then breaks down the form into the building blocks of Labels, Input Fields, and Actions, then lays out best practices for each. Here are a few snippets from the book that resonated with me.
There are plenty of technical guides online about tracking user behaviour using GTM. But I haven’t found as much about dealing with the organizational challenges that may arise when making changes to tracking.
One of my main projects at Carmudi was improving our tracking. The key challenge was that I was not building tracking entirely from scratch. We already had a buggy tracking implementation that was feeding data into some of the most important reports in the organization.
One of the consistent must-reads that has remained in my RSS feed over the years is Seth Godin’s blog. Seth consistently puts out a stream of incredibly wise thoughts. I have found that some of his posts resonate with me even more when I re-read them at a later point in my life/career. Here are some of my favourite Seth Godin posts, as they relate to the role of Product Manager.