Jason Lu
Jason finished his bachelor degree in Monash University with a double major in Finance and Statistics. He gained some experience and developed skills dealing with real-world data from his previous job as a Business Analyst. Jason decided to join the Data School to start a new chapter of his career as he wants to continue studying about data and learn more practical skills.
During leisure time, Jason enjoys playing badminton and volleyball. If Jason could only choose one meal for the rest of life, he would prefer noodles beacuse different veggies and meats can add variety making it an extremely a fancy meal!
Multiple selections for analytical apps
Analytical apps in Alteryx are useful for allowing the user to select the parameters which they need and grab snippets of the data. Here is a blog highlighting the uses of analytical apps. Here is how to make a list box with multiple selections. Step 1: Filter To...
Dashboard Week – Boston 311 Service
Today's dashboard project is based on the Boston 311 Service request data from their website here. The data came in a very clean format so no work was required in Alteryx. I decided to challenge myself by creating a machine learning model to predict whether a service...
Dashboard Week Day 3 – MoMA
The task today was to analyse the data from the Museum of Modern Art from Zenodo. Unlike the previous Youtube Trending challenge, this task required much more cleaning and joining before the data could be used. See Annie's blog here to see she managed the...
Dashboard Week – Youtube Trending
Today's dashboard task was to analyse data for videos that trended on youtube in the last year and a half. The trending video's data was from Kaggle (https://www.kaggle.com/rsrishav/youtube-trending-video-dataset). I used this data to create a dashboard with the aim...
Classification for predictive analytics
What is classification? In machine learning, classification models play a major role in data analytics. Classification models will try to draw conclusions using observed values. For example, given a set of data, the model can try to predict whether something is a...
What can go wrong in a client project?
No client project ever progresses smoothly. Every client project will have its own set of unique complications and obstacles. Here are 5 of the most common problems and possible solutions. 1. Vague requirements: Ask lots of questions Explore the data together with the...
30+ Questions to ask the Client for a successful project
Before the meeting Before the meeting, background research must be conducted. First, look up the client on Linkedin. You will be able to gain an understanding of what they do and know what questions they will and will not be able to help with. Exploring the data and...
6 Simple Steps to Parsing JSON from APIs
1. Retrieve the URLs and necessary tokens and keys. This is the first and most crucial step of the whole process and will establish the difficulty of the task ahead. Every API will have its own unique documentation. Some are clearer than others, some will require keys...
Are colour blind viewers seeing the same?
Are all your dashboards looking bright and vibrant? Do they immediately catch the attention of anyone scrolling through? Something that draws your attention may not for others. Not everyone sees colours in the same way. In fact, 1 in 12 men and 1 in 200 women are...
How I used Fuzzy Matching.
How I used Fuzzy Matching. When working with the dataset containing all Formula One driver names, all foreign names which contained letters with accents appeared as weird symbols. ä -> ä ö ->ö This issue can be fixed by applying a replace formula on each one...