Data is available
A common misconception is you’ll always have data you need to do your analysis. You may think this is a given but even large companies where the data infrastructure is mature doesn’t house all the data necessary. Data can be scattered across databases or have no common keys to join together. I worked for a company that didn’t store email campaign data in the database. Every time I did a campaign analysis someone on the email team had to manually extract a list of emails for me.
Data is clean
When you first take classes in data analytics you’re provided with clean data for assignments and don’t have to account for outliers, missing, or bad data. In the real world, data is dirty and a lot of your time is going to be spent cleaning data before you can start your analysis. There can be issues with ETL pipelines where data is delayed or incomplete and you have to remember to check for this or you can end up with bad results.
You only do data analysis
Data can be in Excel files that you have to spend hours combining together and loading into the database before starting an analysis. The company can have no data engineers to help build ETL pipelines to automate loading data into the database. You may have to build and troubleshoot ETL pipelines if you need the data and no one is available to help.
You can work in isolation
You may think a data analyst runs SQL queries and build dashboards all day. In reality there are meetings and questions from stakeholders that can happen throughout the day. Being in a data analytics role requires you to interact with many people. You need to have good communication skills to explain the results to stakeholders for them to make decisions. If you like to work in isolation and rarely talk to others you’ll need to learn how to work with people and improve your communication skills to become an effective data analyst.
You only have one manager
I bet no one told you that data analytics is also a customer service job. As a data analyst I answer to my stakeholders and their feedback directly impacts my performance review. My manager creates the team’s project roadmap and helps prioritization between groups in the organization but the stakeholders are my customers. If stakeholders are unhappy with my performance then my goal for an above expectation rating will not happen.
All of my work is important
Expect a portion of your data analysis, models, and dashboards to never be used. This can happen for many reasons. You didn’t provide any actionable insights the stakeholder can act on now, the dashboard has become moot because the business pivoted another direction, or your stakeholder just forgot or weren’t aware you created it. I’ve developed dashboards my stakeholder forgot about and generated machine learning models that were never used. Don’t take offense if this happens to you because the majority of your work will be valued and not go to waste.
Data analytics is in high demand and finding a job shouldn’t be hard
It’s difficult to find a data analytics job without any experience. According to this report conducted for IBM on page 7 it states “81% of all DSA ( data science and analytics ) job postings request workers with at least three years of prior work experience. The strong demand for experienced candidates, combined with the strong growth of many DSA roles, creates a chicken-and-egg problem within the DSA job market.” Find data internships, make connections, and research ways to stand out to employers to make it easier to land your first data analytics job.