I arrived at my job as a data analyst brimming with enthusiasm, in possession of technical certifications, and ready to impress. But it didn’t take long to be put in check by reality. I made errors, glaring ones. Some kept me late at nights; others annoyed my stakeholders; and some bruised my confidence. But here’s the good news: every mistake bore a lesson that fashioned the analyst I am today. I would like to pass those lessons on to you so you don’t have to do as I did.
- 1. Ignoring The Actual Question: Why Before What
- 2. Making Things Too Complicated
- 3. No Documentation: Your Future Self Will Thank You
- 4. Skipping Data Exploration: Look Before You Leap
- 5. Failure to Validate with Stakeholders: Building With, Rather Than For
- 6. Obsessing about Tools Rather Than Skills: Tools Are Impermanent
- 7. Forget the Human Dimension: Perennially there is a story behind every number
1. Ignoring The Actual Question: Why Before What
I believed that to be a good analyst was to answer any question I was asked, quickly. I’d be asked, “What’s our sales trend for the last year?” and I’d dash off to get reports, execute queries, and report out on a pretty chart. But when I did provide it, I’d usually be told: “That’s not what I meant.”
I realized that others seldom know how to articulate the real question. Your job is to probe further. Ask: Why do you need to know this? What decision do you need to make? What problem do you need to solve? As soon as I made that shift of emphasis from the ‘what’ to the ‘why,’ everything became different. I stopped making nice-looking graphs that no one was bothered about and began to provide insights that informed decisions.
One of the marketing leads asked me previously to provide campaign conversion rates. Rather than sending numbers, I asked her why. She wanted to know whether adjustments needed to be made to budget allocations. This shifted my analysis entirely, I was comparing campaign performance, audience segment, and ROI and providing actionable recommendations rather than sending just numbers.
2. Making Things Too Complicated
In my earliest projects, I thought that complexity was an indication of brilliance. More filters, more metrics, more charting! But stakeholders became lost. One of the directors finally said to me, “This is amazing, but I have no idea what I’m looking at.” This was my wake-up call.
The best reports and dashboards are simple, focused, and clear. They provide answers to significant questions without overwhelming users. I now strive to produce just one powerful insight or a few action items. And you know what? My work gets used at last.
Scenario: Rather than a 10-slide PowerPoint filled with graphs, I presented a minimal single slide summarizing three critical metrics and what they would mean to the business. That one slide initiated a 30-minute strategic conversation — more of an impact than any report I’d ever produced.
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3. No Documentation: Your Future Self Will Thank You
Raise your hand if you have ever opened an old SQL script and exclaimed, “Who wrote this junk?” to then realize it was you.
Documentation is boring in the moment, but it’s a lifesaver later. Make good comments in your code, keep a changelog, and have a README file. Describe your assumptions, sources of data, and reasoning. If you or someone else comes to revisit the project months later, you will be thankful. I left a project in the middle of an analyst transfer once. The new analyst cycled up in days because everything was documented, and I received compliments about it from my boss. I learned then that documentation isn’t additional work; it’s just doing it well.
4. Skipping Data Exploration: Look Before You Leap
I recently dove headfirst into customer churn modeling without investigating the data. Half of the rows were duplicates and some of the most important fields were null. The model bombed.
Exploratory Data Analysis (EDA) is never optional. Look at missing values, outliers, distribution shapes, trends, and anomalies. Plot histograms. Perform summary statistics. Ask stupid questions. See your data before you model and visualize.
Example: In one of the projects, EDA uncovered that high-value customers were different from others — something that wasn’t observed by the stakeholders. This understanding transformed our overall strategy.
5. Failure to Validate with Stakeholders: Building With, Rather Than For
My career’s loneliest moment? Working three weeks on a complicated dashboard, then presenting and being told, “This isn’t exactly what we need.”
Engage with stakeholders regularly and often. Provide rough draft, mockups, and prototypes. Get input. Test assumptions. Share analysis as an iterative activity, not an individual endeavor.
Example: On a supply chain initiative, I did regular check-ins with operations managers. From them, I received feedback that helped me refine metrics, address assumptions, and prioritize what was truly important. The outcome? A dashboard they used every day.
6. Obsessing about Tools Rather Than Skills: Tools Are Impermanent
I would obsessively learn every emerging tool, Python, Tableau, dbt, Snowflake, and R. But here’s the reality check: tools change; fundamental skills remain.
Develop critical thinking and problem-solving, storytelling and communications skills. The ability to pose good questions, analyze complex problems, and communicate your findings to others—non-technical experts, in particular. This is what distinguishes outstanding analysts.
I once impressed a VP less with a slick-looking dashboard, and more by summarizing a complicated discovery in everyday language and proposing a straightforward action. He wasn’t concerned with what tool I used, he was concerned that I got it.
7. Forget the Human Dimension: Perennially there is a story behind every number
It’s simple to lose oneself in data and forget there’s a human behind every row. Working with data is about empathy, listening, and understanding individuals and what they need.
Establish relationships with others. Listen earnestly. Remain humble. Be inquisitive. Remember that the best ideas address tangible human challenges.
When interpreting employee engagement survey results, I didn’t simply report statistics…….I met with HR leaders, listened to what was challenging for them, and presented findings in language that gave voice to employees.
Summary: Errors Are the Key to Achieving Perfection
If you have made these errors, join the club. All of the analysts I respect have gone down this path. The trick is to learn, reflect, and grow.
Never lose sight of the basics. Ask smarter questions. Keep it simple. Document everything. Investigate your data. Work well with others. Master enduring capabilities. And never forget to remain human.
Your future self, and your stakeholders, will thank you.
