So, you’re wondering what it is like to join The Data School? The Data School Downunder is the Australian branch of The Data School. It provides a four-month intensive Data Analyst training program followed by two years of data consulting projects. Read more about the Data School Downunder here. Today I will be covering the first weeks at The Data School from a firsthand perspective.

Training at The Data School is like trying to drink from a firehose in terms of data learnings. The weeks are a whirlwind of fascinating data concepts that may be entirely new to you, along with learning software you have never used before. And to top it off, every Friday afternoon, you’ll have to present to not only your peers and coaches, but also anyone else from the ever-growing Data School network within Australia who decides to join online.

Thankfully however, unlike many other first weeks in a job, it isn’t a cold, sink-or-swim environment. You are welcomed by warm and friendly coaches who want to impart their decades of knowledge to you. Furthermore, you are surrounded by fellow students. And though the other students may have extremely different prior experiences and background to you, you are all starting your data journey together.

Let me walk you through my first two weeks as one of the students in the first cohort in Brisbane. In our first 2 weeks we have focused on Tableau and Alteryx basics.

 

Week One: Orientation, Introductions to The Data School and Tableau Basics

We learnt theoretical concepts such as (but not limited to):

  • Continuous vs discrete data,
  • Normalised vs De-normalised Data tables,
  • The difference between exploratory vs explanatory dashboards,
  • Pre-attentive attributes and the importance of utilising these in our dashboard designs,
  • “Chart-junk”, what it is and how to identify and avoid it,
  • What double encoding is in terms of dashboard design,
  • What to consider and focus on in order to create an effective and useful dashboard,
  • Common dashboarding mistakes.

We also learnt more practical things such as:

  • How connect to a data source in Tableau,
  • When to use a live version or extract of your data,
  • Using filters: general, conditional and top N filters and adding filters to context,
  • The order of operations in Tableau,
  • How to create parameters and calculated fields and how to utilise these together – especially in order to create useful filters,
  • As well as, of course, how to make several different types of charts and graphs in Tableau.

 

Week Two: Alteryx and Data 101

Week two was focused on Alteryx, but the theory is not forgotten this week either.

Concepts that were covered in week two included:

  • Data 101:
    •  Data types,
    • Structured, unstructured and semi-structured data,
    • Cleaning and parsing data,
    • Table joins: left, right, inner and outer joins,
  • Alteryx tools such as (but not limited to): browse, input data, output data, text input, filter, formula, sample, select, sort, join, union, text to columns, summarize, comment, unique, record ID, date time, transpose, cross-tab,
  • How Alteryx can be used to generate reports,
  • How to deal with dates in Alteryx,
  • When and how to use the cross-tab and transpose tools (Normalised vs De-normalised Data tables).

Alteryx Designer Core Exam screenshot

Towards the end of week two; after hours of training and full days of self-led challenge attempts, our coach believed us knowledgeable and capable enough to sit the Alteryx Designer Core exam. We all decided to sit the two-hour exam on Thursday afternoon.

In a global Data School first – the entire class passed the exam within our first week of seeing Alteryx! I also surprised myself with an 82.5% result on my exam.

I feel very grateful to our coach Shane for teaching us so well and for encouraging us to sit the exam so early. Because I had never even seen Alteryx before Monday morning, I didn’t think I would be able to pass the exam of 80 questions on Thursday afternoon.

But I am very glad Shane gave us the nudge to give the exam a go as it is a big achievement (and relief!) to have it completed so early in our training.

Wrapping up my reflections on the first few weeks of the Data School… On some days, the overwhelm of learning at The Data School is very real (for me at least). But while I might feel like I am standing under a waterfall with all this data knowledge pouring down on me, I am just going to try drink in everything I can so that I can become the best Data Analyst that I can be.

 

Emma Wishart
Author: Emma Wishart