SQL and Data Manipulation
SQL is the lifeblood of any data role at AKKODIS. You will be tested on your ability to extract, clean, and manipulate data from relational databases efficiently. Interviewers are looking for candidates who can go beyond basic SELECT statements and comfortably navigate complex, messy datasets. Strong performance means writing optimized queries, anticipating data anomalies, and clearly explaining your logic.
Be ready to go over:
- Joins and Aggregations – Understanding the nuances of different joins and grouping data effectively.
- Window Functions – Using
ROW_NUMBER(), RANK(), and LEAD()/LAG() for advanced analytical queries.
- Data Cleaning – Handling NULL values, duplicates, and string manipulations.
- Advanced concepts (less common) – Query optimization techniques, indexing basics, and CTEs (Common Table Expressions) for structuring complex logic.
Example questions or scenarios:
- "Write a query to find the top 3 highest-grossing products in each region, accounting for ties."
- "How would you identify and remove duplicate user records based on email addresses while keeping the most recent login?"
- "Calculate the month-over-month retention rate for a given cohort of users."
Data Visualization and BI Tools
Your ability to build dashboards is only part of the equation; your ability to tell a story with data is what truly matters. AKKODIS evaluates how you design visual assets using tools like Tableau, Power BI, or Looker to make complex data accessible to business leaders. Strong candidates design with the end-user in mind, focusing on clarity, interactivity, and actionable insights.
Be ready to go over:
- Dashboard Design Principles – Choosing the right chart types and minimizing visual clutter.
- Interactive Elements – Implementing filters, parameters, and drill-down capabilities.
- Performance Optimization – Ensuring dashboards load quickly even with large underlying datasets.
- Advanced concepts (less common) – Custom calculated fields, advanced LOD (Level of Detail) expressions, and integrating predictive models into BI platforms.
Example questions or scenarios:
- "Walk me through a dashboard you built from scratch. Who was the audience, and what business decision did it drive?"
- "If a stakeholder asks for a pie chart with 20 categories, how would you advise them on a better visualization strategy?"
- "Explain how you would design a daily executive summary dashboard for a retail client's supply chain operations."
Business Case and Analytical Thinking
This area tests your ability to translate a vague business problem into a structured analytical plan. You will be evaluated on how you define metrics, design experiments, and draw conclusions. A strong performance involves taking a structured approach, asking insightful clarifying questions, and explicitly linking your data strategy to business outcomes.
Be ready to go over:
- Metric Design – Defining success metrics and counter-metrics for a new product feature.
- Root Cause Analysis – Investigating sudden drops or spikes in key performance indicators.
- A/B Testing Fundamentals – Understanding control groups, statistical significance, and test duration.
- Advanced concepts (less common) – Predictive modeling intuition, customer lifetime value (CLV) calculations, and churn prediction frameworks.
Example questions or scenarios:
- "Our client's e-commerce platform saw a 15% drop in conversion rate last week. How would you investigate this?"
- "How would you measure the success of a newly launched premium subscription tier?"
- "Walk me through how you would set up an A/B test to determine if a new checkout button increases sales."
Stakeholder Management and Behavioral Fit
Given the consultative nature of AKKODIS, your soft skills are heavily scrutinized. Interviewers want to know how you handle conflict, manage expectations, and communicate technical constraints to non-technical leaders. Strong candidates provide specific, structured examples using the STAR method (Situation, Task, Action, Result) and demonstrate empathy and professionalism.
Be ready to go over:
- Navigating Ambiguity – Delivering results when project requirements are unclear or constantly shifting.
- Pushback and Negotiation – Handling unreasonable stakeholder requests or tight deadlines.
- Cross-functional Collaboration – Working with engineers to fix data pipelines or with product managers to define KPIs.
- Advanced concepts (less common) – Leading client presentations, mentoring junior analysts, and driving data-driven culture changes within an organization.
Example questions or scenarios:
- "Tell me about a time you had to explain a complex technical finding to a non-technical executive."
- "Describe a situation where you discovered a critical error in your data right before a major presentation. What did you do?"
- "How do you handle a stakeholder who constantly changes their dashboard requirements mid-project?"
