Here we are, at the end of our training and the beginning of our journey as data analyst consultants. Seven of us started the training at the Data School 16 weeks ago. Seven people who share one thing in common: passion for data. The last 16 weeks was intense and challenging. Although it was stressful sometimes, it was lots of fun overall.
In this post I will write about my experience and the things I learned.
What did I learn?
I learnt a lot about a wide range of technologies, techniques and concepts as well as improved my soft skills.
16 weeks ago I didn’t even know this tool existed. However, soon after I started using it, I fell in love with this data transforming and analyzing software. I spent lots of nights solving challenges just for fun, but it also helped me to prepare for the exam. I became Alteryx Core Certified after 5 weeks of training.
Tableau, Tableau Prep and Tableau Server
During the last 16 weeks I used Tableau nearly every day. Our head coach Craig Dewar and Peter Goldsworthy taught us how to use parameters, parameter actions, sets, set actions, table calculations, LOD calculations and lots of tips and tricks to exploit Tableau at its full potential. At the end of week ten I became Tableau Desktop Certified Associate.
Tableau Prep is a relatively new ETL software. It allows the user to combine, shape, and clean data for analysis in Tableau. Although it is not as powerful as Alteryx, it is constantly evolving and has its own strengths and benefits. It comes free with Tableau Desktop licenses.
We learnt how to configure Tableau Server, publish datasets and dashboards, how to set permissions, schedule tasks.
Although I obtained my Power BI certification before I joined The Data School, I deepened my knowledge during our Power BI sessions, especially in the DAX (Data Analysis Expressions) area. Jonathon Cavalieri, a previous Data Schooler gave us a great session about this topic.
Other Technologies and Concepts
- Data Modelling
- Data Visualisation best practices
- Design principles
- Project Documentation
- Time Management:
We had 7 client projects during the training period. The clients varied from Sport organisations to the world largest marketing agency. The data, the business problems and requirements were all real. Project weeks were intense. We didn’t exclusively work on the projects on these weeks but we also had training in the mornings. Altogether we had roughly 20 hours to understand the business problem, understand and transform the data, create meaningful visualizations and present them to the client.
Whether it was a client project week or not, we had to work on a task and present the findings every Friday. In fact, on dashboard week we got a new dataset every morning, had to come up with a visualization, write a blog post, and present it to our peers. These projects put big pressure on us sometimes and helped us to improve our time management skills.
- Scrum Project Management
During client project weeks we used the Scrum agile project management framework. Every week someone else acted as project lead, taking on the role of a scrum master. Although I obtained my Scrum Master Certification a few months earlier, these weeks gave me the opportunity to practice it on real life projects.
- Presentation Skills
This is an area where I improved a lot. When I first started the Data School I was terrified to present even if it meant to stand up and introduce myself to a group of people. During the last 16 weeks we received training to improve our presentation skills and were given the opportunity to practice it via presenting our findings to other Data Schoolers, MIP employees and clients.
It was a very intense 16 weeks. We learnt a huge amount. I’ve became so used to learning a lot of new things every day, I noticed that I can’t lay back even on weekends anymore. It feels weird just to sit and watch a movie, like wasting time.
I enjoyed working late on projects some nights with my peers. We ordered pizzas, laughed a lot while still worked hard on the project together. It strengthened the team spirit. On Friday nights everyone stayed in the office, previous Data Schoolers and MIP employees joined us for few drinks and to play jenga, which was a great way to socialize.
It is a very supportive work environment and reassuring to know that there are lots of people I can reach out to if I ever have any problem. I feel lucky to be part of the Data School and would encourage everyone to apply who wants to start a career in data analytics.
I can’t wait to start my first placement and apply the knowledge and skills I learnt during the last few months. I realized recently how awesome it is to do something I enjoy for living. It doesn’t feel like working at all. It is like being paid for doing what I would do for fun anyway. Looking forward for the next two years of consulting and improving my skills and knowledge in the area.
I want to take this opportunity to thank Craig Dewar, Peter Goldsworthy, Peter Kokinakos, Glen Bell, Nick Duncan, Ben Szabo and everyone else from MIP and The Data School for their support and help.