Deloitte Recent Interview Questions for Data Analyst Position November 2024

Deloitte Recent Interview Insights for a Data Analyst Position (0-3 Years)

When preparing for an interview with a firm like Deloitte, particularly for a data analyst role, it's crucial to combine technical proficiency with real-world experiences. Below are my personalized insights into common interview questions.

1. Tell us about yourself and your current job responsibilities.

Hi, I’m [Your Name], currently working as a Sr. Data Analyst with over 3.5 years of experience. I specialize in creating interactive dashboards, analyzing large datasets, and automating workflows. My responsibilities include developing Power BI dashboards for financial and operational reporting, analyzing trends in customer churn rates, and collaborating with cross-functional teams to implement data-driven solutions.

Here’s a quick glimpse of my professional journey:

• Reporting financial metrics using Power BI, Excel, and SQL.
• Designing dashboards to track sales and marketing KPIs.
• Teaching data analysis concepts to aspiring analysts.

2. Can you share some challenges you encountered in your recent project involving Power BI dashboards, and how did you resolve them?

In a recent project, I encountered performance issues with a Power BI dashboard due to high data volume and multiple calculated columns. The refresh time was significantly delayed.
Solution:

• Optimized data models by reducing cardinality and using summarized data tables.
• Replaced calculated columns with measures whenever possible.
• Utilized incremental data refresh and partitioning for improved performance.

3. What distinguishes a KPI (Key Performance Indicator) from a dimension?

A KPI is a quantifiable metric that measures performance over time (e.g., revenue, churn rate). It answers what’s happening.
A dimension is descriptive data used to slice and dice metrics (e.g., region, product category). It provides context to KPIs.

4. Write a SQL query to find the third highest salary from an employee table with the following columns: EID, ESalary.

sql

SELECT MAX(ESalary) AS ThirdHighestSalary
FROM Employee
WHERE ESalary < (
    SELECT MAX(ESalary) 
    FROM Employee 
    WHERE ESalary < (SELECT MAX(ESalary) FROM Employee)
);

5. Create a SQL procedure using ESalary as a parameter that selects all EIDs from the Employee table where ESalary is less than 50,000.

sql

CREATE PROCEDURE GetEmployeesBelowSalary(IN salary_limit INT)
BEGIN
    SELECT EID 
    FROM Employee 
    WHERE ESalary < salary_limit;
END;

6. For the Employee table, retrieve all EIDs with odd salaries and join this with another table, empdetails, to obtain EDOB.

sql

SELECT e.EID, ed.EDOB
FROM Employee e
JOIN empdetails ed ON e.EID = ed.EID
WHERE e.ESalary % 2 = 1;

7. How would you use the LEAD or LAG function in SQL to compare week-over-week data? Using LAG:

sql

SELECT 
    Week, 
    Sales, 
    LAG(Sales) OVER (ORDER BY Week) AS PreviousWeekSales,
    (Sales - LAG(Sales) OVER (ORDER BY Week)) AS WeekOverWeekChange
FROM SalesData;

This compares sales for the current week with the previous week.

8. Can you explain how you would create a DAX measure in Power BI to calculate the year-over-year growth for a specific metric?

DAX

YoY Growth = 
DIVIDE(
    [Current Year Metric] - [Previous Year Metric], 
    [Previous Year Metric], 
    0
) * 100

This calculates the percentage change between the current and previous year metrics.

9. Identify a unique chart type in Power BI that differs from standard charts and explain its purpose.

A Decomposition Tree is a unique chart type in Power BI. It allows users to visually break down a metric (e.g., sales) by various dimensions (e.g., region, product, time). It’s perfect for root cause analysis and exploring data hierarchies.

10. Describe how you would implement a time intelligence feature in Power BI to analyze sales trends over different time periods.

• Create a Date Table with all possible date hierarchies.
• Use DAX functions like TOTALYTD, DATESYTD, or SAMEPERIODLASTYEAR for time intelligence measures.
  Example:

DAX

YTD Sales = TOTALYTD(SUM(Sales[Amount]), Date[Date])

This allows comparison of sales across months, quarters, or years dynamically