After graduating from university, I started learning about analyzing data. Data is a treasure, and schema is a treasure map that I would like to explore as a hidden gem under the data. At university, Python is my primary programming language. I mostly used Python in most classes including Database Systems, Algorithm Design, Machine Learning, Artificial Intelligence, ... Therefore, I used Python to clean, prepare, and analyze data. However, I changed my mind after learning and knowing how to use Alteryx in preparing data. In this blog, I am going to write about the factors that helped me in analyzing data and how I learned Alteryx before going to The Data School.
Practice is the key and passion is the best fuel to go far.
After graduating a while from University, I took many online courses to learn about Data Science in cleaning and preparing data with Python by using libraries. In my free time, I usually go to Kaggle to find some simple datasets first. "Simple datasets" means not many columns in a dataset and easy to clean the data. I practiced cleaning, and preparing data with what I had learned. Moreover, I listed some questions that I was curious about cleaning the data. Based on those questions, I knew which fields should I keep and which fields I didn't need. That process also helped me to practice with aggregation and group by fields to answer the questions.
Practiced with simple datasets for a while, I challenged myself by looking for complicated datasets. "Complicated datasets" means many fields in a table and many tables are not joined. I used Python to join the datasets based on the matched fields. Sometimes, I had trouble exploring the data because the data now was bigger. After cleaning and joining the data, I only kept the fields I needed to answer my questions. I figured out that finding the correlation between fields also helped me very much in answering the question. I practiced using Pearson and Spearson correlation methods in Python and learned to understand the heatmap based on the correlation methods. Those correlation methods also help me to know which fields should be kept.
Many tools and languages could help to clean, prepare, and analyze data. One of the popular languages that most people use is SQL (Structured Query Language) called "Sequel". I started learning SQL by taking an online course and installing MySQL Workbench to use MySQL language. From that time, I already knew 2 languages to explore the data. Then, I challenged myself by doing the 8-week SQL Challenge. During that time, I joined the Data Analytics Apprenticeship program at COOP Careers. The apprenticeship program is a good opportunity for me to organize my knowledge and work with client projects by using SQL, and Python. At COOP Careers, I learned a new tool which is a bridge to connect me with The Data School New York. That tool is Tableau.
That is my journey before applying to The Data School New York. I am sure that everyone is wondering why the title is Journey with Alteryx to The Data School, but I did not mention any Alteryx words. I am going to talk about Alteryx in a few seconds. In summary, knowing many languages is not important. In my opinion, when understanding the logic of how to solve the problem and practicing is like a habit, I feel it would be easy to absorb the new language.
Problems and Failures are Refueling Stations to Continue
I did not know Alteryx until I joined the Meet and Greet session at The Data School New York virtually. In that session, I knew a little about using Alteryx to clean and prepare data from the Alteryx demo. However, I only focused on how to improve my Tableau dashboard at that time because Tableau dashboard is one of the requirements to apply. After the first interview round, I was curious about the advantages of using Alteryx in data analytics and how it could be better than Python. The only way to answer those questions is to try using it.
I took an online course to learn basic Alteryx. I learned some tools in each palette in Alteryx. It's enough for me to clean and prepare the data. I need a license to use Alteryx. Fortunately, I discussed what I was learning in Alteryx with Collin Smith. He showed me the SparkEd Education Program and Alteryx Community page. From those resources, I learned about Alteryx through the Interactive Lessons on the Community page. For each topic, some videos are for about 5 minutes. At the end, there is a quick quiz to review what I learned. I tried to answer the questions. If I answer wrong, I can watch the video again to understand why I got the wrong answer.
Besides learning from the Interactive Lessons, I also practiced to improve my Alteryx skills by solving the Alteryx Week Challenges. In the beginning, there were many tools in Alteryx and I didn't know which tools should I use. However, after practicing many challenges and reading the comments to see how other people solved the problem, I tried to understand why people used that tool to solve the challenge. There are many challenges that I didn't know how to solve. I downloaded the solution and explored why they chose that way to solve the challenge. Then, try thinking of another solution that could be shorter (use fewer tools than the solution) to solve the challenge.
Catch the opportunity
After practicing with Alteryx tools by solving the weekly challenges, I took all 4 Alteryx Designer Core Micro-Credential certifications. When I collected all of those certifications, I got a Designer Core Certification. At that time, I compared the advantages and disadvantages of Alteryx and Python in cleaning and preparing the data. I compared using RegEx in Python and Alteryx. However, I was impressed the most by using the Multi-Row Formula tool. That tool is so powerful to me. When I think about using Python to edit the row with conditions, it could be many lines of code. However, I only need to use 1 tool to control the previous row or the next row with my specified conditions.
Then, the final interview round came. All candidates received the same dataset to clean, prepare data, and build the dashboard. I repeat the same process that I usually work with the data. The process includes exploring the data, cleaning, and preparing the data. Then I sketched my ideas about the dashboard on paper before building visualizations on Tableau. The data I received for the final round interview was the Gift Travel Filling dataset. That dataset manages how many trips each Congressman travels in the year with departure and destination places. However, I felt confused about the data because some congressmen traveled from one state to another state on the same day. It could be many stops for the same trip, so I need to be careful in calculating the trip number. I asked Bianca Ng who volunteered to help me in the final interview round to clarify my confusion. I solved the problem by preparing the data in Alteryx with the Multi-row Formula tool. After the final interview round, I wrote a blog about how I did it on LinkedIn. You can read my blog here.
During the interview, I was so excited to talk about how I prepared the data with Alteryx. I also showed the interviewers which challenges I encountered while preparing the data. However, I spent most of my time talking about the dashboard on Tableau at the interview. Alteryx software helped me at the final interview. If not, I could not solve the problem easily in a short time. After the interview, I kept learning Alteryx with advanced tools on the Alteryx Community page. The topic that I liked the most is macro because it's very helpful in many cases. The spatial tools are also interesting when I can calculate the distance, and area from one place to another place, and many more features from spatial. That was the foundation for me to prepare for the Alteryx Advanced Certification later.
Thank you for reading my blog. That is my journey with Alteryx before flying from California to New York to join The Data School family. I remember a sentence from a podcast that said a successful person is a person who failed so many times in the past. For me, I am not afraid of getting failure. After failure, usually, there is a lesson for me to learn and move on. The next time, if I encounter a problem similar to the previous problems, I get experience in how to avoid the failure I met in the past. I hope this blog motivates you to learn and work.
See you soon in the next blog!