Select Your Analytics Adventure – Analytics On-boarding

Lower the barriers to productivity by employing a “Choose your own adventure” approach to on-boarding your new analytics team members.

By Laura Ellis

Getting new team members on your analytics squad is a great theoretical concept. It brings the hope of more hands on deck and fresh takes on your business problems. Conversely, it comes with a heavy tax for both the on-boarding team and the new hire. It can be daunting to onboard a new team member. It’s overwhelming for the employee who is already in the weeds to spend time ramping up the new person. Additionally, it can be confusing and intimidating for a new hire to navigate the learning required.

Choose Your Own Adventure - 2 options

To create this achievable but still productive first project, we need to identify the necessary components that a successful analyst needs to understand. In my opinion, a productive analyst needs to understand the business, the data and the tools.

Ellis Biz Data Tools


Your new hire may have a general concept of your business but they likely do not know all of the ins and outs. While we all like to jump right into the analysis, no amount of technical skills can replace a practical understanding of the business. Without this, you are likely to misunderstand problem areas, include faulty logic and misinterpret results. However, learning "the whole business" uniformly is not practical. So, for this first adventure, you'll want to choose a small portion of the business to investigate. To put it in perspective, for our first adventures, I choose a product that represents less than 1% of our product portfolio.


Even if your new hire is a SQL wizard, they are certainly not knowledgeable about your warehouse schema. The last thing you want to do is give them full access, throw them a data dictionary and tell them to start learning. To really focus on just getting an understanding of your data objects, I'd start them with a strategically selected view. You'll want the data set to be somewhat contained, so they don't have to navigate a large number of new data objects and their relationships. At the same time, you'll want it to be an important part of your data set so that they can capitalize on their learnings later. In our teams' adventures, we focus the new hires on a view of consumption for the above-selected product in our portfolio.


Your new hire may or may not know your toolset. If you're lucky they do, but often times this is not the case. Especially when you are working with a cutting edge or non-standard tool stack. I suggest that in the first adventure you not even specify which tools to use. Focus strictly on the business and the data. Let them use a tool they are comfortable with. You can build an understanding of the tools in your next adventures. For example, we set up our first adventures with the toolset of their choice. In the second adventure, they will often replicate their first analysis on our chosen toolset.


Using the above approach to select the project scope, I formulated our new hires first adventure. I consolidated it into a letter/project write up to give them on their first day. I've included the letter below. The raw copy is available for download on my github repo. Please feel free to use or adapt this content. If you do employ a similar approach, please let me know how it goes! So far, we've had some excellent results, but we are always looking for ways to improve.

Ellis Letter


Thank you again for reading through my write up on our "Choose your own adventure" approach to on-boarding.  Please share your thoughts with me in the comments or on twitter.

Again, the document is available on my github repo.  If you have trouble downloading the file from github, go to the main page of the repo and select "Clone or Download" and then "Download Zip".

Bio: Laura Ellis is a data geek, passionate about revealing stories within the numbers! She's been in the data field for 13+ yrs working on DBs, BI, data science and real-time event streaming. She leads the user analytics group at IBM Cloud. While she focuses on a range of areas, her passion is DataViz and storytelling.