- Analytics Wisdom
- Posts
- #14 Average Day In A Data Analyst’s Life
#14 Average Day In A Data Analyst’s Life
Day to day work, Scoping projects, Stakeholder meetings
📊 Average Day In A Data Analyst’s Life
Effectively a data analyst’s day-to-day work is divided into 3 parts, scoping out upcoming projects, meetings with stakeholders, and hands-on work. Here's a detailed look at each of these aspects:
Scoping Out Upcoming Projects
Understanding the Problem: The first step is to understand the problem that needs to be solved. This involves gathering initial information and clarifying the project's objectives.
Exploratory Data Analysis (EDA): This phase includes a preliminary analysis of the available data to understand its structure, quality, and potential insights. EDA helps in identifying patterns, and anomalies, and forming initial hypotheses.
Action Steps: The data analyst creates a list of action steps based on the EDA. This plan outlines the tasks and methods that will be used to address the problem, ensuring a structured approach to the project.
Meetings with Stakeholders
Collaboration with Other Teams: Data analysts frequently meet with colleagues from different departments. These meetings are crucial for understanding the specific problems other teams are facing or for receiving new project assignments.
Problem Articulation: During these discussions, the data analyst articulates the problem in detail, breaking it down into manageable parts that can be addressed analytically.
Presenting Ongoing Work: Analysts present their current work, hypotheses, and initial findings. This is an opportunity to explain the progress, methods used, and expected outcomes. Feedback from stakeholders helps refine the analysis and ensure alignment with business goals.
Hands-On Work
Data Manipulation and Analysis: This is the core of a data analyst's job, involving extensive use of tools like SQL, PostgreSQL, and data visualization tools such as Metabase and BI platforms. Analysts extract, clean, and analyze data to uncover insights.
Developing Solutions: Based on the analysis, the data analyst develops solutions to the outlined problems. This could involve creating reports, dashboards, or models that provide actionable insights.
Iterative Refinement: The process is often iterative, with continuous refinement of the analysis and solutions based on feedback and new data
Types of Projects
The nature of projects a DA works on can vary widely but is generally aligned with the company's key performance indicators (KPIs) for the specific quarter. For instance, if a KPI is to reduce costs, a project might involve identifying the top revenue-consuming sources or calculating the average non-headcount cost per department. These projects directly support the company’s strategic goals by providing data-driven insights and recommendations.
This concludes the main areas of focus that were asked to be covered by the audience. In my last newsletter edition I wrote a sample data analyst resume that you can refer to while writing your own. I’ll link the pdf here too.
|
📈 Try Applying An Analyst’s Skills in Stock Picking
Steal our best value stock ideas.
PayPal, Disney, and Nike all dropped 50-80% recently from all-time highs.
Are they undervalued? Can they turn around? What’s next? You don’t have time to track every stock, but should you be forced to miss all the best opportunities?
That’s why we scour hundreds of value stock ideas for you. Whenever we find something interesting, we send it straight to your inbox.
Subscribe free to Value Investor Daily with one click so you never miss out on our research again.
🔥 Hot Data Jobs Right Now! All REMOTE!
Senior Data Analyst, Subscriptions + Finance
Annual Salary: $130K-150K
Company: GamechangerSenior Business Systems Analyst, 3rd Party Data
Annual Salary: $106K-153K
Company: SquareSenior Analytics Engineer, Ads + Marketing
Annual Salary: $150K-190K
Company: GamechangerData Analyst - Digital Design Center
Annual Salary: $150K-175K
Company: DandyData Analyst
Annual Salary: $119K-147K
Company: Headway
📰 Data Tools, Articles and Resources
Tips on Enhancing Your Data Analyst Resume
Building Dashboards That Tell Stories
Machine Learning 101 for Data Analysts